SITALWeek #376

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

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In today’s post: the battle of the bots has begun as AI morphs from a simple tool to a broad startup-enabling platform; fuel users at the head of the power law lack viable EV options; we are running out of time for the human brain to build up defenses against the Internet before technology leaps forward; and a look back at structural changes to the media industry in 2022.

Stuff about Innovation and Technology
Fossil Fuel Superusers

More than 30% of gasoline in the US is consumed by only 10% of drivers. Largely comprising rural residents, often behind the wheel of trucks and SUVs, this group may be tough for EV manufacturers to win over given that affordable EVs capable of repetitive, long-range driving under harsher conditions haven’t been prioritized. The early EV adopters, primarily affluent suburban dwellers with low mileage requirements, were low-hanging fruit for the EV industry; however, replacement of this cohort’s ICE vehicles has moved us only incrementally towards carbon reduction goals. Convincing the gasoline superusers to convert will likely require significant investments in charging infrastructure, longer life/range batteries, marked reductions in vehicle/maintenance costs, and more form factors (e.g., heavy duty vans, trucks, etc.).

BillBot Battle

Customer service technology is becoming sufficiently sophisticated that chatbots can often seamlessly replace human representatives. Now, AI startup DoNotPay offers a chatbot that consumers can use to negotiate the costs of their services with customer service agents. DoNotPay is built with GPT-3 from OpenAI (home of ChatGPT). It seems we are all set for an arms race between opposing AI chatbots negotiating whether we can save a few bucks on our cell phone bill. If we give these AI tools enough logical reasoning and resources, the bots might collude to form a true-life Skynet, ultimately waging war on humans! In all seriousness, this is a great example of how quickly chat engines (and their image- and video-generative AI cousins) are becoming platforms for many more companies to build on top of. One of the richest areas of investment will likely be using these engines to replace a broad spectrum of office-based jobs.

Butter Battle Book

Every time a new technology comes along, it takes a while for humans to adapt to it. This is especially true for various forms of media and communication, as we (or our ancestors) have had to adjust to the various ways our brain is manipulated by print, radio, and television (broadly, video is a particularly convincing medium to which we are still adapting). The Internet, of course, has challenged our senses more than any prior technology. Our propensity – indeed, our programming from natural selection – is to believe. We seem to want to believe every story we are told (unless another story told us not to believe it!). Of course, our brains are also wired for skepticism; however, flexing the skepticism muscle seems to take more energy than passive acceptance. This mental default has been hijacked by the Internet, social networking, apps, etc. And, because we are glued to our screens and constantly inundated with stories and soundbites, our brain is perpetually in reactionary mode, leaving little breathing room for the consideration and understanding that are key to adaptation. During this process of assimilation, we are most vulnerable to savvy and/or unscrupulous people who take advantage of the new technology-driven forms of communication. This happened perhaps most infamously with the amplified rallies and radio broadcasts of the German Reich, which initially might have carried more weight with listeners (like a voice from God) – until we eventually realized amplified sound transmitted over space has no special power. Sometimes, adaptation requires a generation or two growing up natively with a new technology. Unfortunately, we currently exist within a particularly challenging era where new forms of communication are evolving at a rate that far eclipses our generational timeframe. Not only is humanity struggling to comprehend that social media is no different than print, radio, or television – i.e., it’s all just stories with very little truth – but we also have to contend with AI manipulation of images, audio, and video obliterating the line between reality and fiction. If our skeptical muscles can’t reassert themselves and help us realize that, for example, some capricious billionaire leveraging the technology of a social media company might not be an instrument for truth and reason, we could hit a point of no return. This dire scenario will become fractionally more likely if we fail to dial down our credence in digital information before the world shifts to augmented reality, which will make what’s “real” even harder to discern. As I wrote in Meta-mess:

The stakes are high in the transition from screen to spatial computing because every shift in technology – from print, radio, TV, Internet, and smartphones, to altered reality – brings with it a faster pace of disruption that, increasingly, far outpaces humanity's ability to co-evolve. We have not come close to adapting to living alongside the Internet, and yet we are hurtling toward an even more disruptive technology shift. If you spend much time learning about ancient Greece, you realize that while the color palette and mediums of discourse have changed, everything else with humans has pretty much been status quo for millennia. Whether it's Plato’s world, Shakespearean times, the Renaissance, the Enlightenment, or modern day, we worry about the same things. We dream, fight, love, hate, resent, envy, and argue the same ideological questions. The Enlightenment's scientific revolution marked one of the only material changes in the last 3,000 years in human thinking, when it became possible to say “I don’t know” and then investigate why things are the way they are. While this is a Euro-centric example, diverse cultures around the globe have followed sufficiently similar paths such that all humanity shares common, basic parameters for interacting with new technology – namely, a few early adopters tend to wield dominant control over a spellbound (or brainwashed) audience before reverence dissipates, diversity reasserts itself, and usage slowly evolves to benefit the masses. What has changed the most over history is how quickly the new medium (i.e., technology platform, from stone tablets to VR goggles) for communicating ideas and artistic expression can have a viral impact (especially while still in the hands of a few dubious autocrats). Globally, it's not how, but what, we choose to communicate that matters as we go from screens to glasses. If we aren’t careful, we will continue to amplify all the worst of humanity's past, both ancient and recent, instead of shining a light on the best of our traits.

The heart of the social media problem is the broad erosion of trust that has resulted in structural stupidity. The only way I see to disentangle this mess is for things to get so crazy, so unbelievable, and so outrageous that we have to confront the fact that none of it is real (hopefully without anyone getting hurt!). Once our culture has internalized the truth that the newest technologies are just more tools, we can hopefully slip back into something more resembling reality. However, with AI outpacing our biological adaptability, I am not sure whether we will gain the upper hand or crack apart. It’s a race between human cognition and AI. I feel like the little boy on the last page of Dr. Seuss’ Butter Battle Book as he hangs anxiously from a tree waiting to see which side will drop the Big-Boy Boomeroo, “a gadget that’s Newer than New. It is filled with mysterious Moo-Lacka-Moo”:

“Grandpa” [the boy] shouted, “Be careful! Oh Gee!

Who’s going to drop it?

Will you...? Or, will he...?”

“Be patient,” said Grandpa. “We’ll see.

We will see...”

Year-End Review, Part 1

Over the next couple of weeks, I’ll be pulling together some SITALWeek topics and themes from the past year. Today, I’ll kick off this trip down memory lane with excerpts from prior posts on the evolving media landscape along with a few related tidbits and some quotes that stuck with me. As I reflect on the evolution of my thoughts on the enormous trillion-dollar media industry, 2022 appears to have been a pivot point. I’ve only included a small portion below of what I wrote on the industry, but I can see myself confronting a prediction that was becoming increasingly tenuous. As a long-time media investor, I thought for decades that long-form, premium, scripted content would always be valuable; however, in the face of near ubiquitous content in all forms, I had to let go of the former safety of that prediction. The pandemic accelerated a transition from abundant time and scarce content to scarce time and near-infinite content. Near the end of 2020, I made the point that we needed digital DJs to curate content for us; however, I should have focused more on why we were in need of such master organizers. Back in 2021, I described why content was unlikely to follow a winner-takes-most power law. I started talking about YouTube’s glut of content, and how they were beginning to rival Hollywood in terms of content spend. Last year also saw TikTok’s meteoric rise. I can see the initial seeds of my growing skepticism – along with my reluctance to accept that surging content in all forms might be more than a passing fad. In 2022, the data became much more clear: we went from having ample time for media (of all forms) to a battle for attention. Consumer preferences have continued to evolve toward shorter, less professional content, and we are now adrift in a sea of infinite, low-value content with a legion of advertisers desperately seeking our attention. And, as I’ve covered in recent months, generative AI is set to exponentially add to the content clutter. As investors, we try to hold our beliefs as loosely as possible and, like good Bayesians, adapt our views as new data become available. My views on content have certainly evolved over the past 24 months, and I suspect they will continue to do so as we face an ever growing mountain of content. Here is a brief walk through some of the posts related to media, advertising, and our broader relationship with evolving technology.

Spiraling Content Meets Maxed-Out Attention (#330 January 16th, 2022)

Last week, The Tonight Show Starring Jimmy Fallon did a comedy bit called “Tonight Show Polls” (where the answers are jokes), and one of the questions was: “What are you watching on Netflix?” The answer was: “10% Queer Eye, 10% Emily in Paris, and 80% My own reflection while I scroll through TikTok”. It’s funny because it’s true. I’ve been thinking lately about the ever-approaching zero-sum moment when we max out our consumption limit for the exploding menu of entertainment options. The pandemic pushed our nicotine-like phone addiction to even greater highs, to the point where I routinely see people on their phones in rather mind-boggling situations. Could we possibly spend more time watching all of the various screens around us? Until we have AR glasses that we look through every waking moment, it feels like we are getting to the point where growth in minutes spent staring at screens each day will slow. Thus, we are getting closer to that point where, in order to spend more time on social media, gaming, or streaming video, we’ll need to shift away from one to another. Multitasking has its limits.

As our attention to screens has grown, so too has the amount of money spent on streaming, gaming, and influencer/creator content that, like a siren smoking a cigarette, calls to us whenever we have a flicker of boredom. The Hollywood studios are projected to spend $115B in 2022 on video content, which becomes $140B when you add in sports broadcast rights. Disney’s spending is estimated to be up 32% y/y for 2022 and 65% from 2020. Netflix is anticipated to spend $17B this year, up 25% from last year and 57% from 2020. Video gaming is approaching a $200B/year industry, and, while I haven’t seen a good estimate of what fraction is spent on game production across mobile, desktop, and console, I would estimate a total somewhere in the $75B range. YouTube is likely paying out around $20B to content creators this year (see YouTube Rivals Studios). Then, there are payments to creators on Twitch and other social networks as well as a long tail of regional and specialty content around the world, which is easily in the tens of billions of dollars. I am sure someone with more data than me has a better guess, but I’d say that $250B in annual content costs is not a stretch by any means (and this even excludes much of the content spend in China)...

The TikTokification of Consumption Habits (#353 July 10th, 2022)

Professional content, like movies, series, music albums, etc., is generally created with some hope of monetizable longevity. If you spend $100M on a movie today, you want to maximize the duration of returns, as with any investment. The 1986 original Top Gun is still paying large backend dividends to its owners and creators, and that was even before the major success of the $1B-grossing sequel. If content has only short-tail relevance, however, it should be worth far less (i.e., demanding a steeper markdown when you discount future cash flows back to today’s value). The current problem with expected returns for content is the vast proliferation of all types of media – from TikTok to video games to you name it. When divvying up the finite time we have available to consume various content forms, the denominator has dramatically increased. And, because content is getting shorter, it no longer becomes embedded into our common cultural lexicon to the same degree as it used to (see Digital Tribalism for more on this theme). The faster we binge or scroll through content, the more forgettable it becomes – with little time to process or appreciate, it evaporates before it can enter our long-term memory. Yet, producers are largely continuing to follow the old forecasts for future windfalls, spending more and more on content despite its risk of diminished value over time. Following in the footsteps of Netflix, the other Hollywood studios are shifting business models to streaming and copying the strategy of more upfront payments and very little, if any, backend.

There were two recent interviews of media execs that got me thinking again about content’s discount rate: Jason Blum from Blumhouse (a successful next-generation Hollywood production company) appeared on a Puck podcast, and producer/investor Jeff Sagansky was interviewed for Deadline. They both argued that talent is losing out on lucrative backends as a result of streaming’s new upfront-weighted business model. But, that view seems increasingly anachronistic as it becomes clearer that the backend might be worth far less in a world of exploding media and entertainment choices. Indeed, it’s entirely possible that even the upfront is significantly overpriced. The heart of the question is: how much is the value of content being diluted by the infinite proliferation of options? Sure, someone could make another Seinfeld or Friends today that becomes a culture carrier for a generation, but those odds seem to be getting exponentially longer...

In Disney+Ads (#338 March 13th, 2022), I explored the likely outcome that Netflix would launch ads (before it was announced), the importance of first-party data for advertisers, and the likely rise in preference for ad-supported services given their overall win-win nature. Further, in Bundling is King (#359 August 20th, 2022), I noted that YouTube is in a pole position to bundle: In a world where both content and its distribution are ubiquitous, neither side of the scale can be the proverbial “king”. Content is being overvalued by the creators and producers, and distributors are equally overvaluing their role in mediating the relationship between creators and consumers. The value in media now lies with the company that can create the highest non-zero-sum bundle of content (likely with both ad-supported and premium options as well as music and perhaps even gaming) and cheaply distribute it to the widest audience globally... Further, in Gaming Weakness (#356 July 31st, 2022), I looked at declines in console and mobile gaming as consumers parsed more and more choices for entertainment.

In Dylan on TikTok (#370 November 6th, 2022), I gave two of his quotes to help us think about this time of disruption in media and technology:

To the question: “Are you worried that in 2020 we’re past the point of no return? That technology and hyper-industrialization are going to work against human life on Earth?” Dylan replied: “Sure, there’s a lot of reasons to be apprehensive about that. There’s definitely a lot more anxiety and nervousness around now than there used to be. But that only applies to people of a certain age like me and you, Doug. We have a tendency to live in the past, but that’s only us. Youngsters don’t have that tendency. They have no past, so all they know is what they see and hear, and they’ll believe anything. In 20 or 30 years from now, they’ll be at the forefront. When you see somebody that is 10 years old, he’s going to be in control in 20 or 30 years, and he won’t have a clue about the world we knew. Young people who are in their teens now have no memory lane to remember. So it’s probably best to get into that mind-set as soon as we can, because that’s going to be the reality. As far as technology goes, it makes everybody vulnerable. But young people don’t think like that. They could care less. Telecommunications and advanced technology is the world they were born into. Our world is already obsolete.”

And, Dylan said: “Today it is commonplace to stream a movie directly to your phone. So, when you are watching Gloria Swanson as faded movie star Norma Desmond proclaim from the palm of your hand ‘I am big, it’s the pictures that got small’, it contains layers of irony that writer/director Billy Wilder could never have imagined. Of course someone streaming something to their phone is most likely watching something shorter and faster-paced on TikTok. Certainly not anything in black and white with a running time of 110 minutes. Every generation gets to pick and choose what they want from the generation that came before with the same arrogance and ego-driven self importance that the previous generations had when they picked the bones of the ones before them.”

Lastly, in “We Stay for the Replay” (#371 November 13th, 2022), I quoted Tom Junod’s take on our current relationship with media, and the world at large:

“We invest endless faith in the power of technology to deliver clarity. But what it delivers is uncertainty, along with the prayer that better technology might yet yield better results...We watch football because the questions it requires us to answer are much easier than the questions required by politics and religion and law and science, not to mention real life. But the questions are increasingly becoming the same. How do we know what we know? How can we believe what we see? In football as in politics and in politics as in football, we come for the game; we stay for the replay. We watch the replay over and over, in the hope of resolution, but resolution is as hard to come by now as it was in the first instant replay, the one filmed by Abraham Zapruder in 1963. And that's why we have no choice but to keep on watching.”

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #375

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: an exposition on the latest AI tools and how they push us to rethink our role and shift our focus to higher order thinking, creativity, editing, and questioning; a jaunty poem on ants; lasers; generative proteins; workplace psychedelic therapy; and, much more below...

Stuff about Innovation and Technology
Real Genius Ray-Gun
One of my favorite movies is Real Genius starring Val Kilmer. This 1980s pop sci-fi classic features a band of gifted college misfits who realize they are inadvertently working on a high-power laser that is going to be used for military purposes, like assassinating people from miles away. There may not be a movie that has more characters I identify with than Real Genius: Lazlo Hollyfeld, Chris Knight, Mitch, Jordan, and maybe even Professor Hathaway. IEEE reports that big lasers are back. Lockheed Martin recently delivered a 300-kW fiber laser to the US Army. Unlike their chemical-based predecessors, fiber lasers, which use optical fibers to direct a beam of white light, are lighter and less flammable. The lasers could be used to take out missiles, drones, airplanes, or, when a prank is called for, pop a house-sized pan of popcorn from space. In other cool laser news, scientists have demonstrated a 100-gigabit-per-second ground-to-drone link using a fiber laser and tracking system. This tech could eventually lead to 1-terabit-per-second connections from low-earth orbiting satellites and ground systems. The tracking equipment is sophisticated and expensive (for example, a custom $200,000 PlaneWave 27” optical telescope), but it could perhaps be mass-market produced for less if the use cases prove out.

AI Patent Workarounds
Back in #360, I speculated that generative AI tools could potentially help researchers find new proteins or drugs. Technology Review reports that effort is well underway with several new programs at various labs and startups: “These protein generators can be directed to produce designs for proteins with specific properties, such as shape or size or function. In effect, this makes it possible to come up with new proteins to do particular jobs on demand. Researchers hope that this will eventually lead to the development of new and more effective drugs. ‘We can discover in minutes what took evolution millions of years,’ says Gevorg Grigoryan, CEO of Generate Biomedicines.” In one example, researchers at the University of Washington had their AI system generate a protein that would bind to parathyroid hormone, which regulates blood calcium levels. In the lab, the synthesized protein bound the hormone more tightly than any other protein generated by computational methods (as well as existing drugs). It's not hard to imagine a near future where AI is leveraged to redesign or replicate existing drugs in novel ways to work around patents from the start. These techniques won't just apply to pharma, but will be leveraged to decipher many highly complex products and "secret sauce" recipes in the manufacturing and technology sectors. This is the heart of the semiconductor cold war with China, as these chips are used for such purposes. Despite US efforts to curtail China chip access, the AI horse has probably already left the barn.

Miscellaneous Stuff
Psychedelic Benefit Plans
I’m a fan of Dr. Bronner’s (the forward-thinking soap company), and I was unsurprised to see that the nearly 75-year-old business is the first customer of Enthea, a startup that enables self-insured employers to offer psychedelic-based medical care. The initial focus covers ketamine therapy for depression. With increasing legalization and normalization of psychedelics, including psilocybin, for medical use, the world might be a very different place over the next ten to twenty years.

Stuff about Geopolitics, Economics, and the Finance Industry
Redefining Usefulness in the AI Age
It was hard to miss all of the stories last week touting the improvements in OpenAI’s latest natural language interface, ChatGPT. A key advance appears to be its ability to make analogies. I asked ChatGPT to make an analogy between complex adaptive systems and ants, and here’s the output:
A complex adaptive system, such as a colony of ants, is composed of many individual components (ants) that are constantly interacting with each other and their environment. Just like ants work together to build nests, forage for food, and defend their colony, the various components of a complex adaptive system work together to adapt and evolve in response to changing conditions. Both ants and complex adaptive systems exhibit emergent behavior, which is the ability to generate novel and intelligent solutions to problems without being explicitly programmed to do so. In this sense, complex adaptive systems can be thought of as being similar to a colony of ants, where the collective behavior of the system arises from the interactions of its individual components.

That’s not bad, but how about something a little more abstract, like “why should a company emulate an ant colony?” to which I got this response:
There are a few reasons why a company may want to emulate an ant colony:
1. Efficiency: Ants are known for their ability to work together effectively to accomplish complex tasks, such as building nests, foraging for food, and defending their colony. By emulating this type of collective behavior, a company may be able to improve its efficiency and productivity.
2. Adaptability: Ant colonies are able to adapt and evolve in response to changing conditions in their environment. This allows them to survive and thrive even in challenging circumstances. By emulating this ability to adapt, a company may be able to better navigate changing market conditions and respond to new challenges.
3. Intelligence: Ants are able to generate complex and intelligent solutions to problems without being explicitly programmed to do so. This emergent behavior is a result of the interactions between individual ants in the colony. By emulating this type of collective intelligence, a company may be able to generate creative solutions to problems and make more informed decisions.
Overall, emulating an ant colony can help a company to be more efficient, adaptable, and intelligent, which can provide a competitive advantage in the market.

Hmmm, that’s interesting, because it’s not that far off from some of the key points we made about complex adaptive systems, ants, and companies in our 2014 paper Complexity Investing. As a follow up, I asked ChatGPT to write a poem about ants, complex adaptive systems, resilience, optionality, and adaptability:

In the bustling colony of ants
A system complex and adaptive
Emerges from interactions
Of countless components interactive

With resilience and optionality
They adapt and evolve
To changing conditions
In their environment, resolve

They build nests and forage for food
Defend their home and kin
All while exhibiting
Emergent behavior within

Intelligent solutions
Generated from within
A community of workers
Working as one, begin

A model for us all
To emulate and earn
The power of adaptability
And the strength in unity we yearn.

Again, not terrible for a cursory first pass. And, like any tool, there’s a certain learning curve and artistry for creating prompts, as Ethan Mollick explains (I spent less than 30 seconds combined on the prompts for all three of the above examples). It’s hard to know just how generally “intelligent” the program is and what’s behind its answers. However, there’s mounting evidence of a breakthrough happening now (or on the horizon) that will have profound ramifications for society, at least more so than poetic ant analogies. In #332, I argued that tens of billions of dollars have been funneled into the AI language processing arms race “because personal chatbot companions are likely to emerge as the center of everything we do in the digital and real worlds. As aware agents that know you well and have access to your accounts, messages, and apps, chatbots are ideally positioned to displace the tools we use today like Google search and other habitual apps.” I am increasingly convinced this hypothesis is true – and could happen much sooner than anticipated. Collectively, there’s been numerous salient advances in large language models (LLMs) and AI assistants, including generative AI, AI coding companions, AI authoring tools, AI homework helpers, and assistants for specific use cases. It seems inevitable, with the rapid development of open-source chat interfaces based on LLMs like ChatGPT (which isn’t necessarily “open” given OpenAI’s reliance and partnership with Microsoft), that we are right on the cusp of these emerging trends converging into AI assistants tuned for various functions. In reality, AI models are just another software tool; however, their self-learning capability means that, instead of waiting months/years to upgrade from 1.0 to 2.0, the models are upgrading themselves by the second. So, we should expect AI tools to effect long-term job creation/evolution and economic growth (as we’ve experienced with workplace software), but the changes are likely to be strikingly profound and entail significantly more near-term disruption. In particular, we are likely to experience a step function increase in productivity, largely for white-collar information-based jobs, that will create many redundancies. But how significant and widespread is that effect likely to be?

We have some insight into how pervasive this newfangled AI is with data from McKinsey’s recently released marketing report, which suggests that, while the percentage of companies using some form of AI has been flat at around 50% for the last five years, those who were early and heavy users are pulling ahead of the competition with AI-driven revenues (we would expect McKinsey to say this given they are trying to sell AI consulting, but there seems to be some truth behind it). The top categories of AI used by companies, according to McKinsey, were process automation, machine vision, and natural language processing. Widespread use and financial benefits will only boost the speed of AI learning and evolution. Combined with the latest increases in LLM functionality, we could see huge productivity gains, resulting in a potential wave of job eliminations for many folks whose daily work routines can be learned and copied by AI. It’s unlikely to be restricted to mundane tasks because these systems will become increasingly contextually aware as they learn, allowing them to perform higher order, and, in many cases, creative endeavors. The increase in productivity presents a special Catch-22 for OpenAI-Microsoft, which depends in large part on selling their cloud software to office workers. Perhaps AI productivity tools will end up being value priced, i.e., as a meaningful percentage of the labor cost they displace (we’ve seen a similar trend in robot pricing). 

I covered some of the challenges facing humans in the AI Age in John Henry vs. Lee Se-dol a few months ago. With the impending tide of human-vs.-machine moments, it’s existential that we avoid feeling useless. The Dali Lama nailed this idea that automation threatens the feeling of being “needed” in his 2016 NYT op-ed: “This helps explain why pain and indignation are sweeping through prosperous countries. The problem is not a lack of material riches. It is the growing number of people who feel they are no longer useful, no longer needed, no longer one with their societies.” We built decades-long careers, we thought we were irreplaceable, and, then, along came golf carts to replace caddies, passive ETFs to replace active investors, and robots to replace line workers. A study of the impact of rising automation in China found that, among expected outcomes like decreased employment and wages, the rise of robots even negatively impacted birth rates. That’s likely because decreased earnings make it more challenging to cover the expenses of raising a child; but, maybe it also has something to do with feeling less needed (which is not the conclusion of the study; I am just trying to come up with a theory that AI might not propose!). I’ve also written a couple of times about declining college admissions, which seem to go beyond the waning of the college-age population. It’s possible that kids realize that many colleges/trade schools largely prepare students for jobs that will be taken over by technology and automation, so why bother? And, the NYT reports that there are ~200,000 men aged 35-44 in the US who have not reentered the post-pandemic labor force, (which corresponds to a ~1% participation gap between men aged 35-44 [~22M total] and women/other age groups). A primary cause, they posit, is a series of destabilizing forces, from globalization to economic crises; but, perhaps this group of people has also been hardest hit by a sense of lost usefulness. (As a side note, those figures suggest that there is a potential labor pool for reshoring to help stabilize manufacturing and supply chains made fragile by globalization, if these workers can be effectively recruited back into the labor force.) 

One of the broader consequences of the rising intelligence of AI models is that humans will be able to (and, indeed, need to) move to a higher level of abstraction, reasoning, and creativity. All tools that replace manual labor and/or thinking allow us to focus on the next level of challenges and problems to be solved. Indeed, AI implementation may enable an entirely new level of innovative idea generation and assist in bringing those ideas to fruition. The AI Age is essentially once again changing the game of what it means to be human, so the burden is now on us to figure out where to look next to move the species forward. When the cart and wheel became ubiquitous, not only did we spend less time lugging things around on our shoulders, we also invented entirely new ways of living, like farming instead of hunting/gathering, and a slew of creative and academic endeavors (e.g., formalized writing systems, poetry, metalworking, mathematics, astronomy, you name it). Regarding the AI Age we now find ourselves entering, I think humans can focus attention on developing/honing three major skills: 1) determining which questions to ask rather than trying to answer existing questions (note that in my ChatGPT examples above, I first needed to know about all of those topics to ask the questions); 2) editing and curating will be much more important to parse the explosion of AI-generated answers/creations and determine what is of practical value (see last week’s Edit Everything); and 3) improve decision making processes by incorporating the surplus of new AI generated content and tools (#1 and #3 are subjects I address here). 

I’ve covered a lot here in an attempt to connect LLM evolution to job losses to birth rates to usefulness and what it means to be human in the AI Age. Right or wrong, this theory might be a unique synthesis of seemingly disconnected data; or, perhaps with the correct prompt, ChatGPT would spin a similar tale.

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #374

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: I explore lessons from the magician's "force", alongside a key mechanism of standup comedy, to inform decision making; a robot that can paint; aging and de-aging software and the future of personal identity; a close look at the single-family rental market over the last few years reveals some inconvenient truths about the digital transition of the economy; more companies no longer require college degrees; living and spending time alone is trending with several ramifications; and, much more below...

Stuff about Innovation and Technology
Painting Companion
PACO is a painting robot from French company Les Companions. About the size of a large commercial floor polisher, the robot (video) can operate on flat surfaces, applying paint using an airless sprayer on an articulating arm as it moves around a room. Designed to help painters focus on less repetitive tasks, the robot is guided by a 3D model of the rooms it will be painting. The FT reports that the company is partnering with Akzo Nobel’s Dulux paint brand to potentially commercialize the robot to help ease the labor shortage from the growing scarcity of painters. This proof-of-concept will be even more exciting once it can negotiate ladders and scaffolding, or paint happy little trees.

Indiana Jones and the Engine of FRAN
Disney’s new age-altering AI engine FRAN (Face Re-aging Network) can automatically age or de-age an actor in video footage, which may come in handy if recently returned CEO Bob Iger wants to stay on another twenty years. Harrison Ford is de-aged in the upcoming fifth Indian Jones movie (Disney has not yet disclosed whether they used FRAN or another tool for that). While there is still a bit of an uncanny valley to these types of techniques, we should get used to seeing more such altered videos. In Nathan Fielder’s The Rehearsal (see Analog VR in #363), he replaces the mirrors in his house with rather jarring screens that automatically age his “reflection” as he attempts to create a detailed, real-world simulation of aging. Mirror, mirror on the wall... And, as AR glasses become mainstream later this decade and FRAN-like technology is perfected, we can all appear as whatever age we want. Of course, it’s not just age, we can simply appear as anyone (or anything) in real-time AR/video given the current stage of AI tools, and we can even make ourselves sound like anyone else. Artist Holly Herndon created an AI model of her voice that is able to sing anything in her exact style, in part to highlight the Pandora’s Box of legal implications when precise models of you are in the wild for anyone to use. If you want to explore a particularly provocative representation of these trends, I recommend the 2013 movie The Congress (currently streaming on Hulu in the US). In the film, Robin Wright plays a version of herself who sells her digital rights away, which contractually forbids her from acting in person. The film's digital representations of the celebrities eventually allow people to feel what it’s like to actually be the actors when combined with a specially designed, pharmaceutical grade hallucinogenic drug.

“Alexa, Make Me a Story”
Amazon has a new Alexa-based app for kids that allows them to create their own animated stories. Available on Amazon’s Echo Show device, “Create with Alexa” asks a child a series of questions and then creates an animated video, complete with narration and soundtrack. The app is somewhat basic, but the extremely rapid advances in large language models and generative AI could result in high quality productions, or even complete virtual worlds, with a simple prompt in the very near future.

Digital Landlords
Investors bought a record number of homes to rent out during the pandemic, but, for the last two quarters, their real estate purchases have significantly declined, according to Redfin. The vast majority of investor-owners of residential real estate are mom-and-pop landlords, but, during the pandemic, large companies leveraged data and tactics to buy homes faster – in many cases edging out would-be first-time homeowners. Meanwhile, the industry of owning large rental portfolios is fast adopting technology to replace various jobs previously performed by humans. One example, Imagine Homes, uses automation and tech tools of various types to lease 1,500 homes with very few employees or physical offices, according to Vice. The app scans your face to check your identity to allow you access to see a potential rental, and paperwork and other interactions are all automated. This digitalization of home buying and renting is an example of the technologically driven advantage of scale creating a power law. This results in a small number of large companies with robust technology tools and more selection (e.g., renters can stay with the same agency as they upgrade/downsize or move locations) and a long tail of “boutique” landlords. Large investors also enjoy the benefits of scale by borrowing at lower rates than individual buyers. Leveraging data in the pandemic may have contributed to the real estate bubble in two ways. First, a growing number of institutional buyers were using similar pools of information to drive purchasing decisions, which may have put them in competition with each other. Second, rental pricing software used by many apartment building operators may have driven up rents, which would have then impacted regional rents, as well as single-family home prices, to some degree. The artificially higher rents, combined with low cost to borrow and the shared trove of data, were all likely factors in the prices investors were willing to pay – or, rather, overpay – for homes. The DoJ has opened an investigation into the Thoma-Bravo-owned RealPage apartment pricing tool, which may be a form of collusion (for more on that topic, along with the amplified impact of algorithms on the economy, see Algorithmic Distortion of Apartment Rents Fuels Interest Rate Hikes). And, investor withdrawals could potentially swing the market the other way, forcing the sale of single-family homes at reduced prices. Last week, the giant $69B Blackstone Real Estate Income Trust, which owns a portion of its assets in single-family home rentals, restricted investor redemptions because they hit the monthly limit of 2% of the fund’s value. What’s happening to the single-family home markets seems to represent a darker undercurrent in the analog-to-digital transition of the economy that merits a more thoughtful approach, including better regulation as industries are transformed by technology and power laws award outsized scale, and impact, to the winners.

Miscellaneous Stuff
Art – and Science – of Magic Tricks
Investors have a lot to learn from professional magicians and their skilled manipulation of our built-in cognitive biases (see also: Of Investors, Comedians, and Magicians). Even the most incomprehensible magic tricks are always explainable. Sometimes they rely on incredibly complex mechanisms that took years to master; but, more often, the magician uses obvious techniques right in front of our eyes. That’s the simple lesson from magic: if you train yourself to ignore misdirection and pay attention to the key inputs, you have a better shot at seeing the truth. But, if you are distracted by misdirection, you’ll be left puzzled, often not even realizing that you have been fooled. Dani DaOrtiz is a Spanish magician known primarily as a master teacher of other magicians. DaOrtiz recently appeared on the ninth season of Penn & Teller Fool Us (a fantastic show if you like magic and learning a little about how some of it is done). I was blown away by the routine, as were P&T, who were also officially fooled. You can see the ten-minute clip on YouTube. I purchased DaOrtiz’s class on the trick, and, as usual, I was amazed by how simple some of the seemingly impossible illusions were. Simple doesn’t mean easy – quite the opposite: tricks that are simple yet convincing often take decades of practice to perfect. One of the most ubiquitous ways to be fooled is by a “force”. Forces use the illusion of free choice/agency while directing the outcome toward the magician’s goal. In order to be fooled by a force, you need to have convinced yourself that you are in control; however, when you are told “pick a card, it’s a completely free choice”, and you end up selecting the three of clubs, it was most certainly not your free decision! There is a great paper (PDF) on the various types of forces exploited by magicians, which I recently came across thanks to Wharton professor Ethan Mollick. (A quick note of caution: if you love the feeling of being fooled by magic tricks, that paper will ruin many basic tricks for you; however, I think the real beauty of a trick lies in understanding just how much goes into making it work). Section two of the paper on reasoning biases has various elements germane to investing, e.g., Wegner’s exclusivity principle – whereby we think we know what caused something only because we cannot imagine what actually caused it. Forces are a rich area to explore to gain insight into what might be impacting your own decision-making processes as you go about your daily life or evaluate complex choices. The one thing I know for sure is that I am always being fooled, often by myself, but I never know which piece of information right in front of me, or hiding up a sleeve, is responsible. If you can get just a little better at identifying key elements and misdirection, the skill of unmasking hidden forces will compound generously.

Edit Everything
The other profession I find highly relevant to investing is stand-up comedy, as comedians are also very skilled at seeing the overlooked obvious (see also above-linked short essay). Jerry Seinfeld recently did a great spot on The Tonight Show Starring Jimmy Fallon, and he made a comment contrasting his highly edited and curated hit show Comedians in Cars Getting Coffee with long-form podcast interviews: “Why don’t we just cut to the jokes? I don’t understand the two-hour podcast explosion. Cut everything. Cut it.” What’s funny about that Seinfeld spot on Fallon is that the aired version on NBC was six minutes, but the actual segment, which you can see in full on YouTube, was eleven minutes. The five minutes that were edited out were by far the weakest segments (a couple of old bits on Chinese restaurants and card games along with an unfunny bit on Seinfeld appearing in a magazine). So, their editing cut right to the jokes, making the broadcast version far funnier than the actual interview. Seinfeld went on to say: “It’s a standup thing. Standup comedy is: ‘I have a lot of funny ideas.’ Just give us the funniest ones, we don’t want to hear anything else...edit your closet, edit your life, edit everything down.” This call to edit resonated with me. Maybe it’s because I’ve been writing ad nauseam about the proliferation of infinite content across streaming apps, music, social, and gaming, all created by professionals, users, and, now, generative AI, where content is essentially creating itself. The most important skill in a world drowning in content and information will increasingly be the ability to cut and edit everything down. This ties directly to magic and forces: you have to focus your observation where it needs to be, not where the magician is misdirecting it, and you have to edit out all the noise of your visual and auditory systems (not to mention your brain’s spurious storytelling and reactionary emotions) to see it clearly. There are narratives in the world around us (or the companies we are analyzing) that are continuations of prior stories that serve as misdirection for where the real story is headed next. I welcome the obvious jokes that SITALWeek runs a little long sometimes or could be more clear, but we actually edit it heavily. Good editing can take longer than the time it took to create the material itself. Whenever someone tells me they are thinking about writing a newsletter or paper, I give two bits of advice: write only for yourself – an audience of one – and, for the love of all things decent, please get an editor. What does Jerry Seinfeld think about magic? Well, he has a perfect 30-second bit on magic from 1979.

Stuff about Geopolitics, Economics, and the Finance Industry
Degree Not Required
College admissions have been declining steadily, especially for men. I covered this topic in Giving Up on the Old College Try, adding a layer of speculation that there may be broader trends at play as technological advances impact our sense of usefulness (I mostly agreed with the sentiment then, but I am not sure where I’d stand on that theory today). Giving up on college is a trend set to accelerate. Not only were admissions declining already, but demographics and a lack of immigration have set up another vector that’s contracting enrollment. The WSJ reports that myriad employers are dropping college degree requirements for a growing number of positions in the tight labor market. The labor pool is further evaporating as the aging workforce retires. Since the slow trickle of younger workers and new immigrants can’t fill all the vacancies, the trend of dropping degree requirements will likely accelerate. College tuition costs have paradoxically ballooned despite these countervailing forces of supply and demand. If tuition costs don’t sufficiently deflate for the ROI of obtaining a degree to make economic sense, the only solution will likely be a wave of college closures in the coming decade as revenues decline and endowments erode.

Solitude
The NYT reports that the fastest growing demographic segment in the US is people over 50 years old living alone. This group of Boomers and Gen Xers has gone from 15M in the year 2000 to nearly 26M today (this number should plateau for the next four to five years due to the lull in Gen X births from ~1971-1977 before rapidly accelerating again). As I am fond of exploring lateral implications of demographics, a few things came to mind as a result of this growing trend: 1) it might be a tailwind for pet ownership as a surrogate for human companionship; 2) eldercare could become an even larger labor force problem for the US as individuals age by themselves (likely placing more emphasis on automation and caretaker/companion robots for home use); and 3) while the current, aggregate stock of housing is ample for the stagnating US population growth, the size and location of those houses may increasingly be out of balance. On the latter point, specially designed communities with age-restricted covenants may be in increasing demand. Solitude is part of a broader trend, and not just for those individuals who live alone. An op-ed in the WaPo suggests that, over the last ten years, we’ve shifted around ten hours per week previously spent with friends or significant others to being alone. As Kurt Vonnegut wrote in Palm Sunday: “What should young people do with their lives today? Many things, obviously. But the most daring thing is to create stable communities in which the terrible disease of loneliness can be cured.”

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #373

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: I explore the story of how the multi-hundred-billion-dollar digital advertising industry spawned tens of billions of dollars in R&D experiments on AI, connected hardware, apps, and other less-obvious sectors. The ad industry is also at the heart of the ballooning $100B content industry, large language models, and much more. New signs of austerity, both in the economy and at the mega tech platforms, indicate the days of trying to stack S-curves with massive spending on new projects may slow down, or even end. The tech giants' science experiments were too early, and they crowded out viable, innovative startups, but is a window now re-opening for new disruptive companies? As I explore this topic, I talk about storytelling, both the one that got us here, and the ones we might tell about the future.

Stuff about Innovation and Technology
Edible Drone
Drones with wings made out of rice cakes can be flown to people stranded in disaster zones or remote locations. The wings are precision cut by lasers and held together by gelatin. The drones could potentially carry additional food/water cargo as well. These could become very popular in the US if the developers figure out how to make wings out of pepperoni pizza slices.

Gifting Bots
IEEE has a robot gift guide for the holidays. The list of various items, from a tail-wagging pillow to a garden-roaming weed zapper, is amusing but largely impractical. Clearly, robots aren’t quite ready to take over our lives just yet. “Powered entirely by the sun, [the Tertill bot] slowly prowls around your garden, whacking weeds as they sprout while avoiding your mature plants. All you have to do is make sure it can’t escape, then just let it loose and forget about it for months at a time.” Heh.

End of Advertising-Funded R&D?
Over the past fifteen years, the mega platforms of the Internet era have amassed profit pools totaling hundreds of billions and a combined market cap in the trillions. Keenly aware that all S-curves in technology eventually plateau, the platforms have heavily invested in new markets in an attempt to stack new S-curves that would maintain or expand their relevance into the 2020s and beyond. Creation of the $500B digital advertising market has led to the largest profit pool to fund new growth areas in the last fifteen years. From a reductionist viewpoint, we could say that advertising funded new experiments in AI, voice assistants, connected hardware, autonomous vehicles, etc. Such investments at Google produced sundry products like Pixel, Chromebooks, Nest cameras, smart assistant speakers/displays, and Waymo. Meta has funneled money into VR, smart displays, large language models (LLM), and more. Amazon, with its large advertising, Prime, and AWS profit pools, invested heavily in Alexa, smart speakers/displays, tablets, Ring, eero, household robots, Rivian, Zoox, etc.

Now, changes wrought in the digital ad markets, combined with a looming recession (ending the free-money era that has fueled many ad-driven digital startups), could have far-reaching implications for all of these science experiments. While some of the digital advertising market was built on personal intent (e.g., Google search) and first-party data, most of the industry relies on spying and deceptive manipulation of personal data. Some of the newer media platforms, like TikTok, were recursively built with huge amounts of ad spend on other platforms (e.g., Meta’s apps and Snap). There is a small chance that the overall digital advertising market could shrink, as the new privacy paradigm implemented by Apple (and to a lesser extent Google) blockades collection of identifying information and cookie placement by third parties, severely curtailing targeted ads. However, with the analog-to-digital shift of advertising still incomplete, the market might continue to grow as one of the final analog pools of ad dollars – video advertising – shifts to digital. Another big pool of advertising sustaining the growth of digital is the multi-hundred-billion-dollar retail trade promotion industry, which is quickly shifting to digital to the benefit of online retailers. The FT has some details on this segment, which is already $37B in the US.

Over the last decade, professional and user-generated content has also seen massive spending (well over $100B in 2022) funded by ad revenues, among other sources (e.g., other businesses at Amazon, Meta, and Google/YouTube, as well as direct-to-consumer streaming apps from Hollywood and Netflix replacing linear-TV distribution). Another beneficiary of the ballooning digital ad market has been LLMs and AI assistants. These products are likely to be the future of most human-technology interfaces, along with generative AI, and I expect large investments to continue; however, even they might fall victim to changing priorities at the mega platforms. As the tech giants have funneled tens of billions of dollars into these potential next platforms for hardware and software, they have crowded out, and in some cases destroyed, many startups that might have otherwise had better odds at disruptive innovation.

It’s dangerous to oversimplify what has clearly been a complex interaction of behavioral changes, new technologies, new distribution methods, monetary policy, and creative endeavors. Yet, it’s quite tempting to do just that: decades of nearly free capital, creation of the huge digital ad market, and rising usage of smartphones and connected screens for content consumption, seems to have resulted in an S-curve-chasing spending bubble for smart (or AI-enhanced) hardware and assistants and the content they utilize/promote. Is this bubble now poised to pop? Will a crackdown on data collection/sharing severely limit the growth of (or even shrink?) the digital ad market and its subsidized products? Will the loss of free capital and a new content spending discipline curtail the advertising market and Hollywood’s long run? Questions that were unthinkable a few years ago now appear more open ended.

We have shifted from a period of abundant time/money and scarce content to scarce time/money and abundant content in the period of just a few years. We would have eventually gotten there, but the timeframe was likely compressed by outsized pandemic-era investments in digital content creation, and avenues for its consumption, by the Internet giants and Hollywood studios (not to mention the pandemic tidal wave of free money). Now, we see signs of layoffs and spending discipline beginning to appear: Amazon is rumored to be gutting Alexa, and Meta discontinued spending on devices like Portal. Google appears to still be investing, for now. Saddled with debt, Warner Brothers Discovery has slashed projects for its streaming services like HBO Max. Apple is just beginning to dabble in areas outside of its core hardware business (funded with hardware sales rather than advertising), with little so far to show for it. Only time will tell if these examples of stalled research and austere developments are portents or happenstance.

Last week, I talked about how stories define the world around us, and how they evolve over time with human behavior at the center of complex narratives. What I’ve done just now is tell (yet another!) story that might explain the ramifications of digital advertising's growth – and potential decline – for investments in content, AI, and connected hardware. It seems like a compelling story, and it might even be true. And, this story might be evolving as a consequence of the shift to scarce time/money and abundant content, along with changing privacy priorities and a new economic regime defined by higher cost of capital and lower risk tolerance. I suspect the old story that I told above will carry on with many more chapters to come, overlapping with a new, evolving narrative that will form new truths. One way the story could shift is that the large platforms could further consolidate share of advertising (including video and trade promotion spending) and content due to the increased value of first-party data and benefits of scale. Interest rates and the economy could find some degree of stability, and investments might resume. Regardless of what happens, the changing narrative might mark an end of a long-term trend of digital advertising funding content and new, experimental markets and S-curves. It’s possible the big platforms were trying to tell their stories of AI and new computing platforms 5-10 years too early. We may yet be living those stories later this decade. And, with major cuts in R&D at the big platforms, maybe the time is ripe for entrepreneurs with great stories (i.e., in hardware and software) to step back into the void. Will anyone be bold enough, and will they find the money to carry out their visions?

Another way to frame these stories is to say the current, Internet Age yarn is running a bit long (an indulgent director’s cut) compared to prior technological cycles. We are more than two decades into the commercial Internet, and fifteen years have passed since the game-changing introduction of the iPhone. The AR/VR/AI stories of the newly dawning AI Age may be a little too ambitious to be written with today’s tools. In the meantime, many aspects of the traditional economy outside of the tech sector are still early in adopting/leveraging the digital tools of the slowly maturing Internet Age. As investors in these stories, our job is to watch for new evidence that either supports the status quo or indicates the world may be entering a new chapter. And, for the entrepreneurs out there, your job is to write these new stories and will them into creation against all odds.

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #372

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: A century of recorded music is now growing more than 30% a year; while we might not get autonomous cars for a while, the technology is being leveraged into other fields like agriculture; large AI models help make soup; AI systems are converging into platforms to drive efficiency and adoption; young galaxies; the power of comedy and transparency to change the narratives that dominate our world; and, much more below...

Stuff about Innovation and Technology
AI Botanist
Google X’s agriculture startup Mineral automates data collection in the field for phenotyping plants. The goal is to take some of the guesswork out of creating new breeds of plants, like strawberries. “The current version has all-terrain wheels and a half-dozen cameras that take pictures of plants from different angles, plus laser sensors and GPS to keep it from bumping into obstacles. It’s driven by a Mineral technician who uses a remote control; ultimately the company thinks its rovers will direct themselves. Mineral is also testing sensors that can be attached to conventional farm tractors, and ways to augment that data using images from drones, satellites and even smartphones.” Syngenta uses Mineral to identify weeds that can be individually target-sprayed with herbicide. Essentially, Mineral is a new use case of the technology from Google’s autonomous car unit Waymo combined with Google’s other AI capabilities.

AI Soup Chef
Campbell’s Soup has an AI model with 300 billion inputs, and they utilize an “agile design” strategy (typically deployed for software engineering) to help determine what their new flavors of soup should be and speed product development. Chief research, development, and innovation officer Craig Slavtcheff notes: “I would never go so far as to say we’re a tech company as we are all here driven by our passion for food, but [we’re using] all the goodness that came out of the world of tech, and applying it to food design.”

AI’s Carbon
Electricity usage by data centers has surprisingly remained steady since the advent of cloud computing as efficiencies in chips and system design have offset workload growth. As noted in #234: “Between 2010 and 2018, data centers grew compute capacity 6x and storage 25x while Internet traffic grew 10x. However, thanks to Moore’s law and the application of machine learning to improve data center efficiency, power consumption only grew 6% over that period.” That trend might continue, but it seems plausible that we will need breakthroughs in efficiencies for creating and deploying AI engines as they proliferate in usage. Training and utilizing a single large language model (LLM) creates anywhere from 50 to 500+ metric tons of carbon dioxide emissions, according to MIT Technology Review. With LLM efforts underway at many startups and most large tech platforms, it’s easy to see just how large a carbon footprint AI models could have. Add to that the generative AI engines and a host of new applications, and we quickly have the potential for an enormous emissions problem. One of the ways to improve efficiency will be to redesign hardware and software for high-throughput workloads.

Data Center Computing Unit
In related news, Microsoft and Nvidia have announced a full stack deployment of Nvidia’s chips, networking, and AI software on the Azure cloud (similar to a deal Nvidia announced with Oracle). Offering full stack is a break from prior cloud AI configurations, which were disparate collections of computing, communication, and software, and this move may indicate a new paradigm for many AI workloads. We could end up with a scenario where there are large, proprietary AI stacks, like Google search, running on their TPU ASICs, and then broad, general-purpose stacks powered by platforms like Nvidia. Regardless of how AI computing systems progress, it’s a validation of the integrated strategy Nvidia has been pursuing for years. In May of 2020, we quoted Nvidia’s co-founder and CEO as saying: “The exciting thing for the world is the server is not the computing unit anymore. The datacenter is the computing unit. You are going to program a datacenter, not a server.” The tighter the integration between software, hardware, and communication, the more likely AI can achieve power efficiencies over time.

Synthetic Creativity
I’ve been eagerly awaiting this new Wired article from Kevin Kelly on generative AI. Kelly covers many of the topics I’ve explored in SITALWeek over the last six months while bringing his special ability to see the bluesky potential of disruptive new technology shifts. “Instead of fearing AI, we are better served thinking about what it teaches us. And the most important thing AI image generators teach us is this: Creativity is not some supernatural force. It is something that can be synthesized, amplified, and manipulated. It turns out that we didn’t need to achieve intelligence in order to hatch creativity. Creativity is more elemental than we thought. It is independent of consciousness. We can generate creativity in something as dumb as a deep learning neural net. Massive data plus pattern recognition algorithms seems sufficient to engineer a process that will surprise and aid us without ceasing...For the first time in history, humans can conjure up everyday acts of creativity on demand, in real time, at scale, for cheap. Synthetic creativity is a commodity now. Ancient philosophers will turn in their graves, but it turns out that to make creativity—to generate something new—all you need is the right code.” I covered many of the ramifications of generative AI for a broader array of design and engineering disciplines in the Next Video Toaster.

Glut of Music
Music streaming services now have over 100M tracks available, and that number is growing by an astounding 100k each day. Further, AI-generated music is just getting started, and already one AI track – complete with synthesized vocals – has surpassed 100M listens on Tencent music. If the stats from Music Business Worldwide are reliable, that implies the number of tracks could grow by 30-40% per year on top of nearly a century of recorded music.

Miscellaneous Stuff
Early Galactic Coalescence
The dark age of the Universe may have been shorter than previously thought – perhaps only 100 million years – thanks to new images from the Webb Space Telescope. Data on two early galaxies, from just 350Myr and 450Myr after the Big Bang (around 13.8B years ago), indicate earlier and more uniform galactic formation than anticipated. According to one researcher: “These observations just make your head explode. This is a whole new chapter in astronomy. It's like an archaeological dig, and suddenly you find a lost city or something you didn’t know about. It’s just staggering.” The galaxies are also brighter than expected, which should help astronomers locate even more. Further spectroscopic analysis of Webb's data will reveal details of the types of stars and elements present in the galaxies.

Stuff about Geopolitics, Economics, and the Finance Industry
Voter Tipping Point?
Reflecting on last week’s US midterm elections, I recalled a Big Think article (previously shared in #364) suggesting that the last decade has seen a much closer 50/50 split in right/left politics because of a generational and demographic tipping point that now will start leaning younger (which, for now, also implies more progressive on average) for the foreseeable future. This theory might be correct. I always tend to think values/ideologies vary most widely at the individual level, but surely there are some nuanced differences between generations. Time Magazine believes the current election data support an outsized impact by Gen Z, but it might simply have been a more general reflection of progressive ideas, notably concerning green energy and individual autonomy, beginning to steer the American zeitgeist. According to the Big Think article, this shift might at the very least lead to a little less polarization.

Comic Relief
Depending on your point of view, trolling large companies that do bad things can be very funny. It’s funny to me, which is why I enjoyed the “verified” blue check mark debacle on Elon’s Twitter that resulted in people mocking large, Industrial Age companies. The most prominent example was a parody tweet from someone pretending to be Eli Lilly proclaiming they were heretofore going to give insulin away for free. Eli Lilly was unamused. I, however, enjoyed a moment of levity watching all the big global consumer brands, advertising agencies, drug makers, etc. ride away on their high horses and declare their feelings had been hurt so badly that they would stop their Twitter advertising/participation because, apparently, this sort of parody is dangerous. The Information Age has created a paradox that few seem to understand: increased transparency exposes agents who are causing harm (or extracting too much value for themselves, i.e., negative-sum behavior), while the extreme velocity and volume of data transfer makes it exceedingly difficult to determine what is objectively knowable with any degree of certainty. In short, we are flooded with transparency and falsities at the same time.

Humans are storytelling machines – that’s how we came to rule the planet: language, imagination, and opposable thumbs. Everything is a story. We are always looking for stories, telling stories, and trying to convince people that certain stories are true or false. Largely starting in the 1970s, as the media and advertising industries came to increasingly dominate the social narrative (in the form of magazines, radio, movies, broadcast, and cable TV), for the first time since the Scientific Revolution our ability to distinguish truth from fiction started to deteriorate. With the advent of the Internet, social networking, and TikTok’s ultimate short-form storytelling, we are now so immersed in stories – eight billion people glued to little screens bombarding them with stories to be interpreted, adapted, and told to others – that an outside observer might assume that any sort of objective truth is irrelevant to societal function. However, while nearly all of the stories are indeed untrue in their entirety, they also have little relevance to anything existentially important. The sooner people are trained to understand this inconvenient truth about the media we consume, the sooner we can progress to the next societal phase. Whatever that phase may be, it's sure to be better.

If you follow enough stories, tell enough stories, and try to make connections between enough stories, eventually you might get a little better at identifying which stories have some chance of being true, or at least teasing out the bits that might be more firmly embedded in reality. Among other activities, that’s how I see the profession of investing. We tell stories when we buy stocks and assemble a portfolio, trying very hard to find objective threads of evidence we can feed into our narratives. Then we look really closely to see if the story is true or not for each investment, as well as whether or not the story that defines the portfolio in totality has a chance at being true. We try to examine where our stories are vulnerable, or overly precise, in their embedded predictions. Stories are the heart of our pre-mortem process. I’ve been known to inform prospective clients that I am telling them a story and that it’s their job to decide if it has a chance of being true. CEOs tell stories about their companies and cultures. Salespeople tell stories about their products and services. Customers tell stories about why they consume those products and services. Politicians tell stories about society today and in the future. Your view of your “self” and your place in the world is merely a long running narrative your brain tells you about your time on Earth so far, which itself is largely influenced by the stories other people tell about you.

Few people intentionally concoct elaborate lies (at least for very long – it takes a lot of mental effort). Rather, the vast majority of people simply don’t realize that they are telling stories that may or may not be grounded in truth. This society-wide storytelling is the essence of our culture, and it can change slowly or quickly depending on the stories people decide to agree on. I prefer stories with comedy, heart, and commentary on the world around us. While they don’t always turn out to be true, they tend to be more true over time than the stories filled with cynicism, pessimism, and despair. Of course, there are still some things held to be objectively true, especially following the Enlightenment and the Scientific Revolution. We should cherish those things, but also remain open to saying “I don’t know”, because sometimes even seemingly objective truths migrate over time with new evidence. Some special people have the power to will their stories into existence, but most of us aren’t even actors in the stories we tell, let alone writers or directors. The more quickly that humans can come to understand how the Information Age has informed storytelling – and its tenuous relationship with objective truths – the more we can appreciate the humor of it all and turn our attention to making progress on the real, challenging issues facing the world. So, that’s my, ahem...story, of why I enjoyed the recent parody trolling on Twitter: comedy is the best way to shine a light on anything uncomfortable or complex in the hopes of changing the future narrative for the better. In a little glimpse that perhaps, after all, comedy does have the power to change the narrative, the CEO of Eli Lilly, speaking at an event last week, declared that the Twitter fury over the parody tweet "probably highlights that we have more work to do to bring down the cost of insulin for more people."

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #371

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: AI is facing its first lawsuit in what could set precedence for many industries; Microsoft aims to replace office workers with AI, and they may succeed sooner than anyone thinks; a great article from Tom Junod on evolving human behavior as seen through the lens of one infamous NFL catch; can psychedelics also heal physical ailments?; prioritizing instinct before objective analysis; the many long-term influences on rates; looking back at a conversation on semiconductors two years later; and, why investing is like going to the movies.

Stuff about Innovation and Technology
Litigating AI
The first class-action lawsuit challenging the legality of a generative AI system has been filed against OpenAI, Microsoft, and GitHub over the Copilot software coding assistant. Copilot helps autofill snippets of code for programmers and was trained on large repositories of open-source code, which, despite being open for usage, is generally governed by licensing agreements that require users to provide proper citation. Given the eyebrow-raising copyright questions introduced by other types of generative AI services (like text-to-image engines such as Dall-E, also controlled by OpenAI), this case could set precedent for an explosively growing industry. The software engineer who is spearheading the lawsuit hopes that by bringing clarity to how these engines work and which prior art they rely on he can help accelerate their development rather than hinder them. Hopefully, we will have some useful rails sooner rather than later given the ecosystem’s already rapid consumerization and proliferation. As I’ve noted in the past (also, here), you may soon be able to just declare what you want a bit of software to do and generative AI will spit out an entire app. Toward that goal, Microsoft announced last week that Copilot is also adding a voice interface called Hey, GitHub!

Clippy Took My Job
Microsoft’s ultimate goal for OpenAI’s Copilot isn’t just to help coders, it’s to replace you. Well, perhaps they would argue they want to help you do your job more efficiently, but the writing is on the wall. This is a big Catch-22 for Microsoft because, as they make office workers more productive, they lose lucrative Office 365 customers. Effectively, if you let Copilot or other AI assistants into your workplace, they are going to learn what you do and largely replicate it. And, as jobs have gone remote, the task of tracking and replicating work has become even easier. This white-collar automation could have a dramatic impact on many middle-class jobs. Of course, this scenario isn’t anything new in the world of software. Kicking off the trend, ERP tools automated away many back-office jobs in the 1990s. However, the precedent and speed with which AI tools could begin automating the work of full-time office employees may catch the world by surprise (in addition to horizontal Office 365-based tools, AI assistants are also likely to develop for specific verticals). Amazon is perhaps one of the best examples of replacing human tasks with software. Their “Hands off the Wheel” program is described in this HBR article: “The transition to Hands off the Wheel wasn’t easy. The retail division employees were despondent at first, recognizing that their jobs were transforming. ‘It was a total change,’ [a] former employee…said. ‘Something that you were incentivized to do, now you’re being disincentivized to do.’ Yet in time, many saw the logic. ‘When we heard that ordering was going to be automated by algorithms, on the one hand, it’s like, “OK, what’s happening to my job?”’ another former employee, Elaine Kwon, told me. ‘On the other hand, you’re also not surprised. You’re like, “OK, as a business this makes sense.”’” The range of economic volatility will increase significantly as algorithms replace humans. For now, machines are only as smart as the data they are fed, and, effectively, they will all be fighting each other to maximize speed and profits. One example of the old “garbage in, garbage in” adage was Amazon’s SCOT system, which led the company to massively overbuild capacity during the pandemic. And, as I covered recently, automated yield-optimization algorithms drove a giant bubble in apartment rents. While the automation of white-collar jobs and decision making is inevitable, we should approach it with great caution and as much transparency as possible.

Miscellaneous Stuff
“We Stay for the Replay”
Tom Junod waxes philosophical for ESPN on the infamous Dez Bryant catch in the 2015 Cowboys-Packers playoff game, expounding on how humans have turned the concept of determining what’s real into the game of life itself:
“We invest endless faith in the power of technology to deliver clarity. But what it delivers is uncertainty, along with the prayer that better technology might yet yield better results...We watch football because the questions it requires us to answer are much easier than the questions required by politics and religion and law and science, not to mention real life. But the questions are increasingly becoming the same. How do we know what we know? How can we believe what we see? In football as in politics and in politics as in football, we come for the game; we stay for the replay. We watch the replay over and over, in the hope of resolution, but resolution is as hard to come by now as it was in the first instant replay, the one filmed by Abraham Zapruder in 1963. And that's why we have no choice but to keep on watching.”
Junod’s narrative is beautifully insightful and applicable to nearly everything, but it seems particularly germane to what has happened in the sphere of social media in the post-truth world. It’s an acutely accurate description, perhaps without intending to be, of the new Elon Musk era of Twitter.

Psychedelic Physical Healing
Nature photographer Jim Harris apparently cured his lingering, therapy-resistant paralysis, resulting from a horrific snowkiting accident that initially left him paralyzed from the chest down, with a single dose of psilocybin. Psychedelics are known to induce neuroplasticity and increase the effects of neurotransmitters – thus allowing neural regeneration – but our understanding of their effects and capabilities to promote physical healing is only rudimentary. It’s possible psilocybin reawakened dormant neural pathways in Harris’ paralyzed hamstring muscles, thus removing the last major impediment to his independent mobility. Outdoor Magazine quotes a researcher at a psychedelic company saying: “The changes in brain chemistry reverse atrophy and increase the neurons’ ability to rapidly repair damaged neurons, allowing them to begin their normal signaling process. Longer-term beneficial effects of psilocybin are believed to be related to regeneration of neurons and neuronal pathways that may have died.” Colorado recently became the second state to legalize medicinal psychedelics.

Stuff about Geopolitics, Economics, and the Finance Industry
Gut Before Brain?
A key step in our process of evaluating investments is the pre-mortem. As detailed in Time Travel to Make Better Decisions:
Pre-mortems help you determine what could go wrong before it happens. A pre-mortem is a way to try and picture yourself in the future and work backward to decisions made today. It’s similar in concept to Jeff Bezos’ regret minimization framework: “I wanted to project myself forward to age 80 and say, ‘Okay, now I'm looking back on my life. I want to have minimized the number of regrets I have.’” We do pre-mortems for every stock we consider investing in by transporting ourselves into the future and trying to guess at the answers in these scenarios: 1) We didn’t buy enough. Why? What questions/data would have clarified our understanding of the potential? And, 2) We should not have bought it. Why did we? What did we miss about the range of outcomes, the degree of predictions forced by the valuation, etc.? Similarly, if we are contemplating selling a stock, we try to answer these questions as our future selves: 1) We regretted selling it and ended up buying it back at a higher price. Why? And, 2) We never regretted selling. What negatives were there that we were right about? Often, the question isn’t about buying or selling outright, but getting to the truth of what position size an investment should be...This exercise may sound simplistic and obvious, but the key is to make time travel feel as real as possible to fully experience the thoughts and emotions of your future self. Making mistakes in investing (and life in general) is personal and painful – it’s a gut punch of regret. So, we try to literally vault ourselves into the future and see what it feels like to be selling a stock at a major loss – it’s a horrible feeling, how could we have avoided it? The answer can only be in the present. What information are we missing today, or, more likely, what questions are we failing to ask? What is it about the range of outcomes that we need to better grasp? Imagine you have an actual time machine to travel five years into the future. Imagine which path you took through time to get there and which ones you avoided.
Part of this process is trying to strike the right balance between rational analysis and intuition-informed decision making. The key is knowing how to properly weight objective data vs. subjective instincts, making sure to acknowledge that a large amount of our intelligence is collected and relayed by nerve cells distributed throughout our body, not just in our brain (see: Outsmarting Your Brain). Author and researcher Gary Klein suggests that there may be value in applying intuitive reasoning before rational deduction, lest your first-impression reaction be lost once you start digging into the details. That order is generally counter to the way most people inject a dose of intuition into decision making, with the gut feeling informing the final decision after all data have been analyzed. I’m eager to try this inversion with our pre-mortem analysis by considering the whole picture before precisely examining all of the hard data inputs. I think the ultimate process would probably be an iterative method that alternates intuition and objective analysis.

Patience and Interest Rates
Real interest rates have been declining for around 800 years. As we’ve previously noted, following the work of Ole Peters, this trend is most notably due to our enlarging debt burden existentially requiring lower rates for continued economic function. The current rapid rise in nominal rates is a Fed-policy based attempt to combat elevated inflation (itself a result of the last round of mistaken monetary and fiscal over stimulus), such that real rates (nominal interest rate minus the inflation rate) are actually still not that far off the 800-year downward slide. Of course, that is of little consequence if higher rates collapse asset values and wipe out debt. Since one person’s debt is another person’s asset, when we wipe out those assets, the consequences are far reaching and long term. There is an elevated chance that the current monetary policy intervention will inadvertently stop the centuries-long trend in rates for a long period of time by destroying asset values too quickly for the economy to recover. The economy is a complex adaptive system, defined by resilience and adaptability, but any complex ecosystem ravaged by overwhelming external factors risks breakdown and extinction. My base case remains that the economy is largely self-healing, and I’ve argued that the speed of information in modern times increases the ability of the economy to solve many of its own problems. But, that assumes governmental meddling doesn’t create new difficulties not easily corrected via normal market mechanisms. One interpretation of the rather extreme volatility in the markets lately is investors grappling with the unknown outcome of whether or not the Fed’s interference will prevent the economy from self-healing, and in doing so cause an amplified recession, or worse. Time will tell.

As Peters has pointed out, a consequence of ever-rising debt levels is rising wealth concentration. It’s possible that a little bit higher inflation and rates than we have seen for the last decade are actually a positive indication that redistribution and growth are happening in the context of somewhat slower debt expansion (see Blueprint for Rebooting Distributive Era). As a side note, in addition to the mathematical reasons that ever increasing debt is symbiotic with lower rates, economists at the University of St. Andrews recently updated a working paper hypothesizing that another reason for 800 years of declining rates is selective breeding for patience. As I am fond of saying, the first species that humans domesticated was not dogs but, rather, ourselves, thanks to our constant attempts to improve the quality of our tribes and interpersonal interactions. There is a bit of mental gymnastics to understand the theory that enhanced patience is driving lower rates, but the main point I would make is that there may be multiple paths to explaining the gravity pulling interest rates down over the long term as a civilization grows in size, abundance, and perhaps even in patience. Regardless of whether the patience theory has explanatory power, our hope for the future is heavily tied to our desire to borrow and invest in things like families and businesses. There may be good reasons to analyze how the prevailing economic backdrop impacts long-term rates and how the Information Age might be different than the Industrial Age. It will be interesting to see whether or not the TikTokification of life and declining birth rates (which could imply diminishing patience and declining hope) are enduring trends that will impact interest rates. Maybe someday we will come to learn that interest rates rise as our attention spans shrink.

Shifting Winds Plot New Economic Course
It's been two years since Jon and Brinton talked about the semiconductor ecosystem with Shane Parrish. Toward the second half of the interview, the conversation turned away from the handful of companies that have come to rule the fate of the world and toward geopolitics, including the potential for the US to impact China's semiconductor ambitions by banning capital equipment sales. It has been clear to us for several years that the geopolitical range of outcomes for the world continues to widen – and access to leading-edge semiconductors sits at the center of the conflict. For example, we thought the range of outcomes for Apple was widening due to a strong dependency on China for manufacturing. While Apple has sought to diversify their supply chain in the past several years, they remain fragile to China. And, sweeping restrictions from the Biden administration put in place in early October appear much harsher than policies implemented by the Trump administration. More broadly, since that interview, we've seen baby steps to diversify the semiconductor supply chain away from China and Taiwan. TSMC is building fabs in both Japan and Arizona. Intel has announced they're getting into the foundry game with a big investment in new Ohio-based fabs. It seems to us that we are in for a decade-plus of moving from geographically centralized to decentralized production, which could spark higher levels of capital investment than we've seen in the past. This is not just true for chips, but for every industry, as thirty years of globalization, which peaked a decade ago, gradually unwinds (to varying degrees). Focusing on whether or not the range of outcomes is narrowing or widening around a given scenario allows us to adjust our thinking and ultimately adapt to the changing environment.

Today, the range of outcomes for nearly every aspect of the global economy is widening as decades of globalization, accommodative monetary policy, and population growth transition to deglobalization, a scarcity of capital, and a rapidly aging population. This will result in capital allocated to new areas with the highest potential returns, resulting in a whole new set of long-term economic drivers with profound global impact. We will be writing more about these seismic changes in the coming year, and we touched on the potential range of outcomes in our recent quarterly letter, excerpted here:

The third quarter was marked by the ongoing tug of war between investors, policy makers, dictators, and the painful landing of the pandemic-inflated economy. In the short term we expect uncertainty to persist; however, over the long term we know that the future, like always, will be determined by the optimists. Investing, like nearly everything in life, is a form of storytelling. When anyone buys or sells a stock, they are crafting a story about the future. But, of course, no one can predict the future with any precision, and relying on the past can be just as problematic. Therefore, the stories we tell must be based on what we can clearly discern in the present, no matter how foggy the environs might seem. We then live through these stories as they play out in real life, fact-checking our narrative with reality to identify plot holes, inconsistencies, and elements of truth that help us refine our story. There are some types of plots that tend to play out more often than others, there are always unexpected twists and, if you are lucky, a deus ex machina. At NZS Capital, we think stories of optimism – where the protagonist is adaptable and creating more value than they take (non-zero sumness) – occur much more often than stories of cynicism and pessimism, where the characters are rigid in their beliefs and extract too much value from society. The market, however, tends to be more cynical than optimistic, which creates cycles of fear.

Investing in the stock market is like buying a ticket to a movie about which we have little a priori knowledge. We can make educated guesses based on the title and trailer, but sometimes a seemingly feel-good rom-com has an unexpected horror subplot. The current market volatility implies a tension between two completely different plots for how our economic future will unfold. One story is a doomsday movie wherein government policy makers, in an attempt to rewrite their “certified-rotten” pandemic-policy script, send the economy careening off a cliff while geopolitical tensions send humanity into nuclear armageddon. Herein, there is no hero, and the only way out is time and patience. Like Major King riding the bomb in Dr. Strangelove, this movie ends with more uncertainty and questions than with which it began. The other script, however, has a happier ending. The underpinning of this second narrative is the self-healing ability of the economy, with innovation and hope driving a long cycle of post-WWII-like prosperity, investment in green energy, and a steady increase in global economic resilience. The first story implies that the last forty years of globalization, low interest rates, deflationary forces, and rising inequality will be met with a long and harsh punishment. In contrast, the second story plays to the evolutionarily ingrained resilience and ingenuity of humans. Of course, there are thousands of ways the future could play out, and we won’t know the ending until the lights come up and the curtains close.

Like the complex world around us, the global economy is dominated by power laws and extremes. Humans, however, tend to be linear thinkers, so we can miss emergent, game-changing events unless we train ourselves to look outside our typical mental confines to routinely scan left field and beyond. Some of the best stories of the future may be written in surprising locations and combine different topics and technologies in novel ways. Importantly, in times of volatility, policy changes, and technological disruption, economic resources often shift and refocus on newly emerging areas. A series of events, such as the world has recently experienced, can create pivot points for society. We continue to see significant opportunities in the engines of the analog-to-digital transition of the global economy, such as software, semiconductors, and the Internet. But, we expect resources and attention to shift to new origins of asymmetry in areas like AI, automation, healthcare, and other parts of the economy. While we cannot know the precise storyline for what lies ahead, we can appropriately prepare for all potential plot twists.

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #370

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: the effort to design new computing platforms from artificial and real neurons has the potential to upend the current processor and software/AI architectures; bundling Hollywood videos into an unending ocean of content; a look at Bob Dylan's new book and his philosophical ins generational shifts and changing technologies; productivity drops the most since 1947 as people change jobs and return to the office.

Stuff about Innovation and Technology
Superconducting Synapse vs. DishBrain
Neuromorphic microchips operate more like neurons than traditional semiconductors. Rather than running and communicating at all times, neuromorphic circuits fire (i.e. transmit) only above certain thresholds of input, as do neurons. One of the largest impediments to AI is that the human brain is so incredibly power efficient that we can’t come close to replicating the performance per watt in silicon. The computational capacity and connectivity of neuromorphic chips have likewise been limited by traditional, power-hungry hardware. Researchers at NIST are working to overcome the baggage of traditional electronics for these neural-mimetic chips by using optical waveguides, which allow each neuron to connect with thousands of others at the speed of light. To bypass the conundrum of having to trap light on a microchip, researchers came up with a novel way to convert photonic signals to 2-picosecond-long electrical pulses: “These pulses each consisted of a single magnetic fluctuation, or fluxon, within a network of superconducting quantum-interference devices, or SQUIDs.” Scientists were surprised at how easy it was to construct this system, which resulted in artificial neurons firing 30,000 times faster with only 0.3% energy usage vs. biological neurons.

A different approach to creating more efficient neuron-like processing is to use actual neurons. Cortical Labs in Australia has trained a dish of mouse neurons, along with neurons grown from human precursor cells, to play the game Pong. The DishBrain consists of a petri dish with a single-layer mesh of 800,000 cells connected to hardware and software, which trains the neurons using feedback. For comparison, the human brain has 86B neurons and a fly brain has 100,000. Rather than the dopamine humans are used to, the cells are rewarded with a predictable signal (and poor performance is anti-rewarded with unpredictable signals). This system of reward sounds eerily similar to Karl Friston’s free energy theory of the brain. I covered Friston in #271 and #272: “This can be viewed as minimizing free energy, which is simply the difference between what you expect to happen and what your bodily senses are telling you is actually happening. For example, if I expect that I will warm up by stepping from shade into sunlight, and then proceed to do so, odds are the temperature receptors in my skin will confirm that prediction – no surprise and minimized free energy. Underlying the free energy principle is the idea that the brain is a Bayesian probability machine...If the brain acts as a Bayesian machine, it will constantly adjust predictions based on new sensory inputs. According to his free energy principle, if the brain makes a prediction that appears incorrect, it can respond in one of two ways: accepting the surprise and modifying its version of the world (Bayesian inference) or by acting to make the prediction true (what Friston calls active inference).” The gist of the theory is that the brain works to minimize energy consumption by making more accurate predictions. The free energy principle might be key to advancing new forms of neural networks, whether mechanical or lab grown. If any of these efforts, using standard inputs, can create usable outputs at scale, they would effectively replace the current ecosystem of AI chips and processors. Also, possibly, the world would be changed so fundamentally that we don’t have the language or imagination to describe what might happen.

YouTube’s Primetime
Bundling is King. That’s what I wrote back in #359, noting that YouTube was in one of the best positions to re-bundle the deconstructed Hollywood content. Last week, YouTube announced it would begin offering content from the studios’ streaming platforms as Primetime Channels, embedded in YouTube’s flagship 2B-user app. I noted back in August that the value in media now lies in the distribution platform that can offer the highest non-zero-sum value bundle and also drive the highest advertising rates for content creators. The biggest issue for Hollywood’s premium content studios is the extreme fragmentation of attention, something I wrote about in more detail in The TikTokification of Consumption Habits. Today’s professional content appears to have diminishing value, a reality that becomes apparent when you compare it to the endless stream of videos on YouTube. While bundling is likely the only path forward for Hollywood, it’s a double edged blade. The algorithm is king now, and Hollywood’s content is as indistinguishable as a drop of water in an endless sea.

Miscellaneous Stuff
Dylan on TikTok?
I was reading this New Yorker article on Bob Dylan and came across his comments on the cumulative nature of creativity, i.e., artists are constantly building on what came before them. The article quotes Dylan from an 2015 acceptance speech saying: “These songs didn’t come out of thin air, I didn’t just make them up out of whole cloth. . . . It all came out of traditional music: traditional folk music, traditional rock and roll, and traditional big-band swing orchestra music. . . . If you sang ‘John Henry’ as many times as me—‘John Henry was a steel-driving man / Died with a hammer in his hand / John Henry said a man ain’t nothin’ but a man / Before I let that steam drill drive me down / I’ll die with that hammer in my hand.’ If you had sung that song as many times as I did, you’d have written ‘How many roads must a man walk down?’ too. All these songs are connected. I just opened up a different door in a different kind of way...I thought I was just extending the line.” This sentiment got me thinking about generative AI and the controversy over algorithms using other artists’ work to create new outputs in music, images, and video.

Dylan has also commented in the past on the progress of technology from generation to generation. Back in SITALWeek #249 (June 2020), I posted Dylan’s response (NYT article) to the reporter asking: “Are you worried that in 2020 we’re past the point of no return? That technology and hyper-industrialization are going to work against human life on Earth?” Dylan replied: “Sure, there’s a lot of reasons to be apprehensive about that. There’s definitely a lot more anxiety and nervousness around now than there used to be. But that only applies to people of a certain age like me and you, Doug. We have a tendency to live in the past, but that’s only us. Youngsters don’t have that tendency. They have no past, so all they know is what they see and hear, and they’ll believe anything. In 20 or 30 years from now, they’ll be at the forefront. When you see somebody that is 10 years old, he’s going to be in control in 20 or 30 years, and he won’t have a clue about the world we knew. Young people who are in their teens now have no memory lane to remember. So it’s probably best to get into that mind-set as soon as we can, because that’s going to be the reality. As far as technology goes, it makes everybody vulnerable. But young people don’t think like that. They could care less. Telecommunications and advanced technology is the world they were born into. Our world is already obsolete.”

I started listening to the audiobook of Bob Dylan's newly released The Philosophy of Modern Song. This fascinating book covers 20th-century American musical history through an examination of 66 songs (66 may or may not be a coincidence – 1966 was the culminating year of a long run of successful releases and performances, followed by a controversial dabbling in new-fangled rock and roll, after which Dylan retreated from the public eye for eight years). The audiobook features Dylan and an entertaining cast of characters, including Jeff Bridges, John Goodman, and Steve Buscemi (as well as a few actors who were not in The Big Lebowski). Discussing the song “My Generation” by The Who, Dylan writes “Today it is commonplace to stream a movie directly to your phone. So, when you are watching Gloria Swanson as faded movie star Norma Desmond proclaim from the palm of your hand ‘I am big, it’s the pictures that got small’, it contains layers of irony that writer/director Billy Wilder could never have imagined. Of course someone streaming something to their phone is most likely watching something shorter and faster-paced on TikTok. Certainly not anything in black and white with a running time of 110 minutes. Every generation gets to pick and choose what they want from the generation that came before with the same arrogance and ego-driven self importance that the previous generations had when they picked the bones of the ones before them.” Is there a connection between Dylan's comments in the NYT on the obsoletion of the older generations and his comments on picking the bones clean in "My Generation"? It seems so. In contemplating these connected concepts of iterative art, generational technology shifts, and Dylan’s seeming awareness of TikTok, I can’t help but chuckle at the idea of Dylan someday becoming wildly popular on the short-form video platform, which itself is a mish mash of people iterating on songs and dances of others. We know that Dylan, in his long career, revels in playing with truth and reality to the point where it’s impossible to know what’s real (see #198). So, perhaps stranger things have happened than Bob Dylan one day shooting to TikTok superstardom. We can only hope.

Stuff about Geopolitics, Economics, and the Finance Industry
Productivity Plunge Risks Stagflation
This year in the US, returning to offices and job hopping has created a precipitous decline in productivity not seen since 1947. It appears that, despite viral reports of mouse jiggling, white collar workers were getting more done at home during the pandemic. And, now, accelerated quits – as people “swipe up” for higher salaries – has slowed output, with experienced employees having to stop what they are doing to train each new crop of temporary-minded hires. This unproductive mire is one of the biggest factors sustaining inflation, as productivity can be one of the best ways to combat rising prices. All of these circumstances should continue to feed an accelerated automation of white and blue collar jobs.

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #369

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: Halloween is a big holiday at our house, resulting in an abridged topic list this week. I explore a couple of ideas around "generative AI" – the trending term for the many transformer AI models that are rapidly becoming a hot area of focus for many industries, most notably design and art; a look at the folks trying to blend cultured meat with plant material to recreate a tastier and more economical animal-protein substitute; and, lastly, an interesting look at how information consumption varies at companies, which follows a pattern we expect to see in living organisms. If you missed last week's much-discussed exploration of the perils of algorithm use by corporations, and how it likely caused the crazy spiral in apartment rents, check it out here. Have a great Hall🎃ween!🤘

Stuff about Innovation and Technology
AI Copycats
The field of generative AI, the term that encompasses text-to-image, audio, and video creation/manipulation algorithms driven by short user prompts, is advancing rapidly. As new platforms proliferate, the concern over copyrights for AI art is rising, and the Recording Industry Association of America is worried that generative engines will be trained on their recording artists’ music without their consent/compensation. There is a common process in the music industry for paying royalties to sample copyrighted music, which would be very hard to follow if AI engines can’t trace their sources. CNN also spoke to several painters who were upset to see AI models easily recreate their painting style after being trained on their images. Stability AI, the startup behind Stable Diffusion that recently raised money at a $1B valuation, told CNN it’s working on ways to potentially compensate artists. One of the big issues today is artists aren’t even being asked permission before their works are included in training. I’ve covered the topic of AI art recently, and it seems clear these engines will need to be able to list the works that inspired the final product. It’s a rather tricky situation, but it could be solved (at least partially) by artists being able to copyright a “style” rather than a specific artwork itself. There may be some precedent in other industries; for example, car makers have a history of suing each other over things like similarly styled front grill designs. But, where do you draw the line for commercial art? If you see a painting or hear a song that appears characteristic of a specific artist, maybe that “style” will/should be copyrightable by the original artist (or whoever owns the rights).

Artificial Homework
Back in #355, I covered the rise of text-generative AI, such as Sudowrite, for assisting authors with book writing. Last week, The Information reported on the increase in students using such tools to write and edit papers. From high school to college level, many kids are getting good grades while the AI does the work. One student “felt confident in GPT-3’s ability to complete college-level work, because it had helped him graduate from high school. For one biology homework assignment in 12th grade, he was asked to write a paper describing all the functions of a cell. ‘I just really didn’t want to do it,’ he said. So he gave it to an artificial intelligence writing tool to produce. He looked at the text the AI generated and felt it was good enough to submit—so he did. His teacher gave him 100%.” Jasper is an example of text-generating AI, while others, such as QuillBot, edit what you have already written. These tools are yet more examples of the swiftly evolving nature of creative output. And, the next logical step might be to embed some of these AI assistants into word processing programs, rapidly amplifying accessibility and training of the AI models. Will we soon have a plethora of Stephen King wannabes churning out 1000-page horror crime thrillers with little more than a handful of specified plot points? As noted above, authors may want to investigate copywriting their “style” as well.

Miscellaneous Stuff
“Hybrid” Burger
In a section of #316 titled Cultured Meat Pie in the Sky, I noted the massive amount of bioreactor capacity and other hurdles that would need to be overcome to make even the tiniest of dents in the meat industry with lab-grown animal protein. And, since the current cadre of plant-based burgers doesn’t appear likely to win over a world of meat eaters, some companies are taking a different approach to meat replacements. A startup called SCiFi Foods is attempting to blend cultured meat cells with plant-based meat alternatives to create a cost effective, yet tasty, alternative to farm-raised meat, according to Vox. There remains wide skepticism, but optimistic estimates suggest that this hybrid approach could be competitive with traditional meat by the end of the decade. Another startup, New Age Eats, includes cultured animal fat cells (in addition to muscle cells) in their hybrid products, which is reportedly key to taste and mouthfeel in replicating real meat. If all goes well, maybe these new meatier plant burgers will be served up by the RoboBurger robot. The company, which recently raised $10M in new funding, has an autonomous machine that can cook and assemble a burger in four minutes.

Stuff about Geopolitics, Economics, and the Finance Industry
Information Footprint
According to a new paper (pre-print PDF), information consumption at companies follows a 3/4 power law, similar to scaling trends found in complex systems and biological organisms throughout the world, from circulatory systems to cities. Here is an excerpt from #315 describing the basic concept:
We’re big fans of Geoffrey West’s work and have often recommended his book Scale to people who ask us about complex systems and the Santa Fe Institute. In Scale, West describes how physiological characteristics of mammals follow quarter power scaling laws. For example, an elephant weighs 10,000x more than a squirrel and grows 10x slower, has a 10x longer gestation period, and lives 10x longer (10 being 10,000^¼). Because growth is dependent upon distributing nutrients to cells throughout the body, one might think that volumetric (a.k.a. weight in this case) differences would determine growth rates, giving third power scaling (since volume is three dimensional), which would correspond to 22x slower growth/gestation. Why is the elephant able to eke out a faster growth rate, and thus better reproductive fitness? The fascinating reason for this quarter power scaling is likely due to blood vessel and respiratory networks that have evolved through natural selection to maximize metabolic rates in the three-dimensional world we find ourselves in. The best way to maximize space in a 3D world is to use fractal, or self-similar, patterns. Fractals are so efficient that they essentially give a network, like blood vessels, an extra dimension, which is why the number four repeatedly shows up as a scaling factor – it’s three dimensions...plus one. In other words, a linear fractal is two dimensional, a surface area fractal is three dimensional, and a volumetric fractal is four dimensional.
This fractal upscaling might also explain the researchers' findings – that larger firms superlinearly consume more information (i.e., news articles) per employee than smaller firms – implying that “The tools of the knowledge economy enhance firm productivity” (p. 7). If we extend the fractal analogy, I might surmise that firms are maximizing the number/depth of topics they explore relative to their constrained size. Of course, it’s possible the scaling effect is a coincidence, but, given large organizations can be viewed as living organisms, this interpretation seems plausible. Curiously, reading amount was more closely tied to a firm’s revenues rather than number of employees, again implying some benefit to economic size. And, the common path of many firms “suggests that large public firms are increasing[ly] confined to a deterministic trajectory in terms of information diversity” (p.4). Firms that start out with very specialized information interests are slower to diversify topics. An interesting hypothesis that comes to mind is whether the type of information diet (diverse, connected, etc.) a firm consumes directly impacts the adaptability/success of their fitness function (which defines their operation within their sector). Specifically, would a more information-diverse organization see disruption coming before a competitor? The data in the article were limited to a small window, but it would be interesting to trace the metrics of information consumption over a longer span (5+ years) to find correlations with expansions, revenue growth, vertical integration, self-disruption, or entry into new sectors. If anyone has that type of company-wide (anonymized) article access data they would be willing to share, please contact me.

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #368

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: a fascinating look at an algorithm used by the apartment industry that might be one of the biggest false flags in the Fed's policy-setting data; why EV chargers may proliferate at a much faster rate than expected; waterways are becoming very stressed with more drought on the way; an economic blueprint for the next few decades; public investors sitting on record cash levels while private companies burn record amounts of cash; and, much more below...

Stuff about Innovation and Technology
Algorithmic Distortion of Apartment Rents Fuels Interest Rate Hikes
In Magic AI-Ball, I wrote about the accelerating implementation of algorithms in corporate decision making, declaring that “the increased use of AI tools/software add-ons will have one tangible impact: a significant increase in the amplitude of feedback loops in the economy.” Referencing the Amazon SCOT inventory/capacity planning system, which caused Amazon to far overshoot on pandemic ecommerce capacity, it seemed entirely probable that broad implementation of algorithmic tools, all crunching the same data in similar fashion, could increase the frequency and amplitude of business cycles. This might be exactly what happened with apartment rentals in the US during the pandemic. According to ProPublica, a large portion of apartment operators were using the same pricing and yield software tool from RealPage, causing a spiral in rent prices beyond what might have otherwise happened. In some cities, nearly all major apartment owners were using the tool, which utilizes private pricing data from competitors to determine rental and occupancy rates that maximize revenues. The result was an apparent form of collusion using an algorithmic go-between to push double-digit percentage rent increases. RealPage-driven price increases coincided with an unexpected uptick in demand during the pandemic (see the final Demographics section from two weeks ago for an explainer on that topic). Now, the rental market is experiencing an aberrant drop in demand while abundant new supply hits the market. Likely, much of that new supply had been started before the algorithmic acceleration of rents, but it’s possible high rents also encouraged supply. The outcome could be a glut of supply and a downward spiral in rents as the pricing software tries to beat the competition to drive occupancies. The victims appear to be the renters, who are potentially being charged more than a normal free market clearing price (RealPage claims to advocate higher rents at the expense of occupancy). And, the bigger victim here might be the economy as a whole, given how heavily the Fed relies on rent prices – which account for 40% of core CPI measures – to feed its interest rate decisions (if the Fed could digest more real time data we might avoid a major recession or liquidity crisis in the economy). I wouldn’t go so far as to say that one misguided algorithm is going to drive the world into a global recession as central bankers aggressively raise rates (there are many other factors at play, including excessive fiscal stimulus and overly accommodative rates during the pandemic), but algorithms are clearly having a negative, multiplicative impact.

Another area I mentioned where algorithms are increasing volatility is stock trading, which, as we saw last week, can induce rather seismic political upheavals. As easy as “swiping up” on TikTok, the UK is getting another new prime minister after the bond and stock markets reacted negatively to policies from PM Liz Truss. Investor concern regarding new fiscal policy is nothing new, but the stock and bond markets’ severe reaction and political impact were largely without precedent. Given how much short-term market moves are now dictated by algorithms and high-frequency trading, it seems logical that algorithms feeding each other headlines and sentiment indicators exaggerated a feedback loop that effectively caused the resignation of the UK’s shortest reigning prime minister. The complexity of the system makes it hard to trace the exact causal sequence, but I think we can disconcertingly say that algorithms have an outsized impact on major parts of the world. This is likely to continue to become a larger issue as more companies rely on so-called AI to make business decisions.

Mexican ‘Za with Side of Electrons
A Taco Bell franchisee with 120 locations plans to install EV chargers in parking lots for customers. The ChargeNet chargers will add about 100 miles of range in 20 minutes for $20 while you eat your Mexican Pizza. That cost is roughly the same as gas for an ICE car that gets around 20 mpg. However, I wonder if, over time, having chargers available will go from a profit center to a cost of doing business, with management offering subsidized electrons to entice consumers to their business over a competitor. There are currently an estimated eight parking spaces for each car in the United States. If every household and a significant percentage of parking spaces eventually have a charger, the size of the charger market could be quite large. You could imagine a future where each grocery store, movie theater, mall, office building, etc. has hundreds of subsidized chargers in their parking lots to win your business and/or maintain your employment. Meanwhile, rest stop chain Pilot (owned by Berkshire Hathaway) plans to install 2,000 EVgo rapid chargers across 500 stations in partnership with GM, with the first units going live in early 2023. Ubiquitous charging would eliminate range anxiety for potential EV owners, thus accelerating adoption. IEEE has a bunch of stats on EVs and charging in this article, noting that if 90% of vehicles were EVs by 2050, grid demand would increase by 41% from 2021 levels. That load would need to be balanced throughout the day and rely on vehicle-to-grid stabilization, all of which could be accomplished with a wider availability of charging infrastructure.

Miscellaneous Stuff
Aqueous Stress
The World Meteorological Association indicates that one-third of thermal power plants, 15% of nuclear plants, and 11% of hydroelectric plants are in regions experiencing stress to waterways due to drought and/or flooding. These facilities in large part depend on freshwater to operate, e.g., cooling nuclear power towers. Meanwhile, the mighty Mississippi, critical for moving agricultural and energy products, is running dry, with the sinking water level tying an all-time low of -10.7 feet. The US is expecting its third La Niña weather pattern in a row, a drought-causing sequence of events that has only happened twice since 1950.

Stuff about Geopolitics, Economics, and the Finance Industry
Blueprint for Rebooting Distributive Era
A couple of weeks ago, I wrote about the forty-year cycle of growth and positive reallocation in the economy, with a distributive cycle beginning post-WWII and ending around 1980, when wealth started to become more concentrated. My suggestion was that the potential to return to a distributive period of economic growth could be driven by a number of factors, including steady deglobalization and/or rebuilding of manufacturing in the West along with significant green energy projects. You can think about the post-WWII era in the US as being a social engineering and government policy project designed to build a robust middle class and a strong domestic manufacturing industry. This period was marked by mid-single-digit inflation and domestic economic expansion, which existed up until the Vietnam War and energy crisis of the 1970s. Since then, the economy has become increasingly leveraged – to the point where we risk financial collapses. As such, we need to reduce the debt burden by cycling back to a distributive economy so that borrowers can rebuild their balance sheets. Market strategist Russell Napier provides one potential blueprint for doing so by “increasing the growth rate of nominal GDP”. Specifically, governments should (1) back commercial banks with credit guarantees, allowing them to guide how much – and where – money is invested, and (2) follow a policy of financial repression to redistribute wealth held in government bonds. In this framework, mid-single-digit inflation (4-6%) is something to be embraced rather than feared. Such inflation levels would make debt more affordable (allowing debt holders to pay off debt in the future with inflated money) and act as a steady form of wealth transfer from savers (the aging population) to debtors (those entering the workforce and establishing households). It’s almost too much of a Goldilocks scenario to actually happen. But, if we could engineer a multi-decade period of targeted policies that reversed the inequality created by the last 40 years of globalization and accommodative interest rates (which drove debt levels sky high in the public and private sectors), it seems like it’s worth a try. One missing ingredient is the boom of babies seen post WWII. As long-time readers know, we have an aging population crisis as birth rates decline globally and certain countries (like the US) discourage immigration, putting a big damper on economic growth (and causing labor-cost inflation absent significant automation/innovation offset). While I expect a small bump in births due to the bolus of Millennials hitting their 30s in the next few years, perhaps an even bigger trend will emerge. NBER data suggest births in late 2021 and early 2022 were running around 5% above trendline in the US (after dropping a similar amount below trendline in 2020 and early 2021; page 18 of PDF). More recent data from California shows a modestly above-trendline birth rate continuing throughout 2022. Birth rate growth was highest among mothers in their 30s with 4+ years of college education, which could be explained by work-from-home flexibility (pages 20, 24).

Cash Hoarding
A recent survey of global fund managers by BofA Securities revealed high cash levels not seen since 2001. Cash sits at an average position size of 6.3%, and equity allocations are three standard deviations below the average. This hoarding of cash – specifically the US dollar – is driving the dollar’s high valuation that’s wreaking havoc on emerging markets. Bloomberg reports food exports are piling up in the US as foreign countries cannot afford to pay for orders, risking a hunger crisis in many locations. Emerging markets also frequently borrow and make debt payments in dollars, increasing the risk of defaults. Regarding the far-reaching impact of algorithms discussed at the start of this week’s newsletter, perhaps it’s not too much of a stretch to say that this food crisis is, in part, a consequence of algorithm-driven rent hikes. The economy is increasingly interconnected and complex.

Pop!
Cash might be piling up for investors, but it’s disappearing fast at startups. Silicon Valley Bank (SVB Financial Group subsidiary), the preferred banking institution for startups and VCs, saw cash withdrawals in the latest quarter second only to the first quarter of 2001, during the dotcom crash, according to a report by Steven Alexopoulos at J.P. Morgan. Plummeting balances are a result of startups burning more cash than they are raising, ending a long run in the VC funding bubble. The trajectory of the cash-burning, high-growth publicly traded stocks and private companies appears quite similar to the early post-dotcom bubble-bursting era, which could suggest a prolonged, multiyear lull before fresh capital circulates to begin the next cycle. Twenty years ago, the Federal Funds Target Rate decreased from around 6% to 1.5% over the course of 2001, laying the groundwork for a recovery. Today, however, the Fed is planning the exact opposite, an unprecedentedly steep increase in rates in short order, just as things are beginning to unravel. Hopefully, it will only take a few modest quakes to reacquaint the Fed with reality, and we can thus avoid the big one.

✌️-Brad

Disclaimers:

The content of this newsletter is my personal opinion as of the date published and is subject to change without notice and may not reflect the opinion of NZS Capital, LLC.  This newsletter is an informal gathering of topics I’ve recently read and thought about. I will sometimes state things in the newsletter that contradict my own views in order to provoke debate. Often I try to make jokes, and they aren’t very funny – sorry. 

I may include links to third-party websites as a convenience, and the inclusion of such links does not imply any endorsement, approval, investigation, verification or monitoring by NZS Capital, LLC. If you choose to visit the linked sites, you do so at your own risk, and you will be subject to such sites' terms of use and privacy policies, over which NZS Capital, LLC has no control. In no event will NZS Capital, LLC be responsible for any information or content within the linked sites or your use of the linked sites.

Nothing in this newsletter should be construed as investment advice. The information contained herein is only as current as of the date indicated and may be superseded by subsequent market events or for other reasons. There is no guarantee that the information supplied is accurate, complete, or timely. Past performance is not a guarantee of future results. 

Investing involves risk, including the possible loss of principal and fluctuation of value. Nothing contained in this newsletter is an offer to sell or solicit any investment services or securities. Initial Public Offerings (IPOs) are highly speculative investments and may be subject to lower liquidity and greater volatility. Special risks associated with IPOs include limited operating history, unseasoned trading, high turnover and non-repeatable performance.

SITALWeek #367

Welcome to Stuff I Thought About Last Week, a personal collection of topics on tech, innovation, science, the digital economic transition, the finance industry, and whatever else made me think last week.

Click HERE to SIGN UP for SITALWeek’s Sunday Email.

In today’s post: electric air taxis to the airport; connected license plates; fractal dimensions can improve AI-generated art; the AOL stage of the metaverse; using school buses to stabilize the grid; robot bee dances; Shatner; the big lesson we never learned from choose-your-own-adventure books; the escalating chip war with China is likely to meet retaliation and require cloud regulation; and, much more below...

Stuff about Innovation and Technology
Car Tags Go Digital
California has legalized digital license plates across the state. Although the plates can display a custom message along the bottom and, in the future, may enable tolls and other services, the real value is of course the freedom from the tyranny of having to affix a new expiration sticker every year. (Although, at a cost of $215/year if you prepay, it’s a bit steep even for us sticker haters.) We say it far too often, but anything that can be connected will eventually be connected to the digital world.

Aerial Airport Taxi
Delta Airlines is investing up to $200M in eVTOL startup Joby with a goal of providing air taxi service to airports in cities with heavy traffic. As mentioned in #348, the electric vertical takeoff/landing maker previously received FAA approval to begin testing its service. Delta plans to launch at LAX and LaGuardia when the service is ready. If there were some way to clear security remotely and then have Joby drop you right at the gate that would be very cool.

AI Art and Fractal Dimensions
Phenaki is a new text-to-video transformer model from Google that creates much longer videos from narrative inputs. The video at the bottom of Phenaki’s website starting with “Lots of traffic in futuristic city...” is a good example. The Verge reports on Phenaki and other recent text-to-video innovations. While the renderings and realism are distinctly beta, you can imagine a future where any one person could write a story and end up with a Pixar-like output. Obviously, there’s great value in a well-crafted and honed storyline, so Pixar, which excels in this area, will likely still be around for a long time. Yet, giving animation capability to anyone who wants it will no doubt create a deluge of new content to compete for our limited attention (see also: The TikTokification of Consumption Habits). Kevin Kelly goes one step further in this interview, suggesting the next step is the creation of an entire interactive virtual world from a text prompt. One topic concerning text-to-image and text-to-video engines that I have yet to see explored is the fractal dimension of the output. Fractal dimension is a number between 1 and 2, where 1 is a straight line and 2 is an extremely complex fractal pattern. Human eye movement evolved to trace a fractal dimension of 1.4 because it’s very common in nature (e.g., tree branches and such). We therefore are drawn to art that reflects this level of complexity. I suspect fractal dimension could be used to greatly improve the believability and beauty of AI-generated art. This 2017 Nautilus article exploring the concept of fractal dimensions and how they relate to human consciousness is a fascinating read.

Metaverse of AOL Chat Rooms
There was no shortage of articles last week ridiculing the launch of Meta’s new high-end VR passthrough headset and its other metaverse announcements. Most of the criticisms are hard to argue with, but what I am far more interested in are the glimpses we are starting to see of where the technology and experience will be in 5-10 years’ time. Many of our real-world activities could be made more useful and interesting with an unobtrusive augmented overlay. I think AR has the potential to be even more transformative than the Internet and will follow a similar adoption curve, going from non-existent to ubiquitous within a decade or two. If we want to see where things are headed, the area to focus on is what artists are doing with VR/AR (a topic I explored in more detail in AI Art, Video Toaster, and Back to the Future). A NYT reporter, Kashmir Hill, spent months exploring Meta’s Horizon World VR app and reports on several interesting aspects in this article. She encountered users like Aaron Sorrels who runs a standup comedy club in Horizon with 13,000 weekly visitors. That number may not sound impressive, but it’s likely far more patrons than your local comedy club garners. Sorrels offers access to the virtual club’s private lounge to paid supporters and is making enough that running the club is a full-time job. Attending live, real-world events (where real people appear real in the headset) as a virtual participant is another compelling use case. To be clear, I don’t think the future of AR will be anything like Meta’s Horizon platform, and the devices won’t be like the Quest, but I do think this early tech offers some insight into the applications that may migrate to future platforms. Hill sums up her experience well: “explaining the metaverse through the lens of Horizon feels akin to unpacking the potential of ‘the web’ by surfing AOL chat rooms in the 1990s, during the days of dial-up modems. Meta’s V.R. social network is an early and singular part of what could become a large technological shift.”

Fleet-to-Grid Power
School buses sit idle most of the day, as do many other types of fleet vehicles. A startup called Synop has software and tools to turn fleets like school buses into large vehicle-to-grid (V2G) power banks, providing reserve energy to the grid during peak usage. Buses can be fully charged overnight while demand for power is low, drive morning and afternoon routes, and still have plenty of battery capacity to drain out during the middle of the day and in the evening. Given variable pricing for energy, the goal is for schools to make money off their buses as they provide peak electrons to grids. Many fleets, such as rental cars/trucks, have times throughout the day (or year) when they could be used as V2G ballast. Synop software tracks vehicle routes and usage to assure they have enough reserve capacity when they are in use.

Miscellaneous Stuff
Hive Hacking
Bees communicate where to forage using a waggle dance. Researchers in Germany have learned how to create maps from the bee dances to figure out where bees have visited and also program their own robotic bee proxies to communicate specific directions. Using high-tech hives equipped with cameras and dancing drones, it should be possible to identify areas where bees are picking up toxins and reroute them to safer areas free of pesticides and other dangers. Other researchers are working on spy bees to infiltrate and influence queens: “The idea is for robots to infiltrate the queen’s group of closest attendants. In theory, the impostor bees might be able to induce the queen to lay more eggs by feeding her more protein-rich food. Or they could make her egg laying more efficient by guiding her to areas of the nest where cells for babies have already been prepared.”

Reconnecting with Our Pale Blue Dot
William Shatner experienced a roller coaster of emotions during his trip to space on Blue Origin. He reflects on those feelings in this essay he wrote for Variety:
It was among the strongest feelings of grief I have ever encountered. The contrast between the vicious coldness of space and the warm nurturing of Earth below filled me with overwhelming sadness. Every day, we are confronted with the knowledge of further destruction of Earth at our hands: the extinction of animal species, of flora and fauna...things that took five billion years to evolve, and suddenly we will never see them again because of the interference of mankind. It filled me with dread. My trip to space was supposed to be a celebration; instead, it felt like a funeral.
The experience of viewing Earth from space tends to cause a shift in perception known as the Overview Effect:
It can change the way we look at the planet but also other things like countries, ethnicities, religions; it can prompt an instant reevaluation of our shared harmony and a shift in focus to all the wonderful things we have in common instead of what makes us different. It reinforced tenfold my own view on the power of our beautiful, mysterious collective human entanglement, and eventually, it returned a feeling of hope to my heart. In this insignificance we share, we have one gift that other species perhaps do not: we are aware—not only of our insignificance, but the grandeur around us that makes us insignificant. That allows us perhaps a chance to rededicate ourselves to our planet, to each other, to life and love all around us. If we seize that chance.
Perhaps, whenever we sing national anthems at organized events, we should also take 3.5 minutes to pay homage to our Pale Blue Dot.

Choose-Your-Own State of Mind
I recently stumbled across a bit of writing from Edward Packard titled The View from Ninety. Packard was the creator and author of the popular choose-your-own-adventure youth books for three decades beginning in the 1970s. The essay is a reflection on his own path through life and what he learned. Notably, the notion that you can actually choose your path through life is challenged by the seeming randomness of it all. Life in some ways represents a choose-your-own adventure where someone is also rolling the dice every time you flip the page. Luck plays a far bigger role than choice, and you have to be ready to open that door when luck comes knocking. Here is an excerpt:
My view from ninety is a lot different from the one I had at twenty, fifty, and even eighty. To explain this, I have to go back a ways. When I thought up the idea of a book in which “you” are the main character and make decisions from time to time leading to multiple plot lines and endings, I realized that, as the story moved along, I ought to give readers plausible choices as to what to do. The idea was that they would have to think about the pros and cons of each possible choice and analyze which would be best. It wasn’t until many decades later that I realized that the way life plays out doesn’t just turn on conscious decisions made at key junctures. Rather, the paths you take are determined largely by chance and by what kind of person you are. Countless things about you, such as your genetic makeup and life experiences, even your body language, even a propensity to smile or scowl, can affect other people, change dynamics, and produce situations in which you fail to perceive options or unthinkingly dismiss them and seize upon one that looms large in your consciousness, and events seem to be happening in rapid sequence before you can assimilate them, so that you have little or no sense of making decisions, and in fact you are not –– you are traveling through time as if floating downstream on a river raft, poling now and then and sometimes hanging up on a shoal, not paying proper attention, maybe falling asleep, and finding yourself almost on the opposite bank, where the wind took you, which is not where you meant to be, all the while missing something, and you may not even know what it is.
At least that’s the way it was for me while I was growing up and after growing up. I was sleepwalking through life, and as a consequence making a lot of bad decisions. Reflecting decades later on my long succession of them, as to each of the most important ones I asked myself, How could I have acted that way? What was I thinking? Why wasn’t I thinking?
This line of inquiry led me to an insight: When you face a choice in life, particularly an important one, whether you choose wisely or unwisely isn’t likely to depend on how good your powers of analysis are, but on your state of mind: Having the wrong state of mind is conducive to making wrong choices. Having the right state of mind is conducive to making right choices.

Stuff about Geopolitics, Economics, and the Finance Industry
Divisive Banking
As culture continues to fracture into smaller and smaller factions, an effort has emerged to create more parallel economies. There is, of course, the East-West divide where in the case of China a separate political economic system and Internet exist. There are upstart businesses catering to one political viewpoint, social networking alternatives to Meta, Twitter, etc., and states pushing anti-ESG agendas. The WSJ writes about the failure of GloriFi, a bank that focused on “pro-America values such as capitalism, family, law enforcement and the freedom to ‘celebrate your love of God and country.’” I don’t believe any of this behavior is new in terms of aligning beliefs with businesses – consumers have boycotted or favored businesses of various types (e.g., based on union affiliations or social/environmental ideology) for decades (if not millennia). However, the potential to create parallel economies at scale inside a Western country with businesses and Internet tools aligned to only one viewpoint seems like a step in the wrong direction.

Know Your Cloud Customer
The Biden administration escalated our trade war with China by placing a slew of new restrictions on chips and chip equipment sales into the country. The fear in D.C. seems to have been recently elevated by China’s achievement of hypersonic missiles and increased attempts to crack key US encryption, according to the NYT. As I’ve noted before, the chip industry has failed to keep its basic programmable chips, as well as higher-end devices, out of places like the Russian military, thus becoming a key enabler of tyrannic wars. While the US fear seems well placed, the idea of restricting access to high-powered computer chips is increasingly challenging given the availability of cloud platforms. In the banking industry, the complex problem of tackling money laundering and criminal activity is handled with KYC, or know your customer. It seems likely that all cloud platforms will have to go through similar processes in order to grant access to GPUs or large amounts of compute power to train machine learning models, etc. It's plausible that cloud platforms will be required to know what workloads are actually doing on their platforms, a slippery slope of regulation. I suspect the US is overplaying its hand in this latest salvo given how reliant the West remains on China for a myriad of goods and raw materials. One thing is for sure: the stakes are high given the relative importance of a small number of semiconductor companies, and this maneuver is unlikely to go without retaliation.

✌️-Brad

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