SITALWeek #394
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: chatbot vs. chatbot; understanding LLMs as a new way to interact with technology that gives users more agency; quantum sensors; ecommerce and digital ad giants enabled decades of innovation in new products and services, but as growth slows and focus shifts to cost cutting, who will create the next platforms for disruption?; Buster Poindexter; and, much more below.
Stuff about Innovation and Technology
AI Negotiators
Walmart’s AI chatbot can simultaneously converse with 2,000 suppliers to extract...er, negotiate, as Walmart puts it...improved terms. The bot learns on the fly how to maximize tradeoffs, like taking lower prices in order to get paid faster or vice versa, and it can apply what it learns to future interactions. Other companies, like shipping giant Maersk, also deploy AI negotiation tools, according to Supply Management. Amazon has been leveraging AI with mixed outcomes for years with their “hands off the wheel” strategy. The best counterdefense to AI-negotiating chatbots would probably be deployment of your own chatbot advocate. I currently have chatbots negotiating some of my recurring monthly subscription bills. Before long, most customer relations will be chatbots talking to chatbots – the hands-off-the-wheel future that will greatly increase volatility for us humans who will be experiencing the outcomes of these silent battles. One area that might see significant impact from chatbot-to-chatbot negotiations is complex legal contracts, as Fortune reports that many startups and law firms are already leveraging AI tech.
LLMs as Social Collaboration Interface
This explanation of large language model AI from Jaron Lanier is compelling from a number of angles. Here is an excerpt from the essay in the New Yorker, which I recommend reading in full:
If the new tech isn’t true artificial intelligence, then what is it? In my view, the most accurate way to understand what we are building today is as an innovative form of social collaboration.
A program like OpenAI’s GPT-4, which can write sentences to order, is something like a version of Wikipedia that includes much more data, mashed together using statistics. Programs that create images to order are something like a version of online image search, but with a system for combining the pictures. In both cases, it’s people who have written the text and furnished the images. The new programs mash up work done by human minds. What’s innovative is that the mashup process has become guided and constrained, so that the results are usable and often striking. This is a significant achievement and worth celebrating—but it can be thought of as illuminating previously hidden concordances between human creations, rather than as the invention of a new mind.
As far as I can tell, my view flatters the technology. After all, what is civilization but social collaboration? Seeing A.I. as a way of working together, rather than as a technology for creating independent, intelligent beings, may make it less mysterious—less like HAL 9000 or Commander Data. But that’s good, because mystery only makes mismanagement more likely.
Further, here’s Lanier’s characterization of how digital platforms force us to conform to them, and how AI may flip that:
Many of the uses of A.I. that I like rest on advantages we gain when computers get less rigid. Digital stuff as we have known it has a brittle quality that forces people to conform to it, rather than assess it. We’ve all endured the agony of watching some poor soul at a doctor’s office struggle to do the expected thing on a front-desk screen. The face contorts; humanity is undermined. The need to conform to digital designs has created an ambient expectation of human subservience. A positive spin on A.I. is that it might spell the end of this torture, if we use it well.
Squeezed, Entangled Photons for Navigation
Researchers at the Universities of Arizona and Michigan have used distributed quantum sensing and squeezed light to improve the speed and precision of light-based accelerometers by 60% and 40%, respectively. These optomechanical sensors may prove invaluable in navigational systems where GPS performance is limited (e.g., underground, underwater, indoors, outer space). The advance uses quantum entanglement to split a laser beam into two, which can then be analyzed by two sensors as if it were the same beam (owing to its photons being entangled with each other) to improve precision (the more times you can measure the same thing, the more precise the measurement). Squeezed light reduces the quantum uncertainty in one parameter, like the photonic phase, at the expense of sensitivity for measuring other, extraneous variables to further enhance precision. While quantum computing remains an experimental pipe dream, quantum sensors and quantum communication networks will likely be commercialized sooner.
They’re Cute…Until They’re Not
This IEEE article highlights three new robotic prototypes. I cannot get enough of these adorable little robots doing cute things like playing sports, even though, one day, they will probably hunt down every last member of humankind. It feels like an incredibly short distance between today’s experimental robots and Black Mirror’s graphic robotic dog attack in “Metalhead”. I am both looking forward to and dreading the day that these little bots are loaded up with AI. (For more on this topic see last week’s Soccerbots). In the meantime, the clairvoyant show Black Mirror is set to return to Netflix for season six this summer. Regarding the show’s four-year break, creator Charlie Brooker described the pandemic-weary world as not having the stomach for new episodes.
Passing the Innovation Baton
In aggregate, the three big pillars of the Internet – digital ads (search, social, etc.), ecommerce, and streaming video – have experienced a slowdown in revenue growth in recent quarters. While initially attributed to lapping the post-pandemic demand pull in, some elements of the slowdown also appear to be related to the maturity of the decades-old industries and user behavior. This malaise has been met with widespread cost cutting efforts at companies like Meta, Alphabet, and Amazon. Back in November, in a long post entitled End of Advertising-Funded R&D?, I reflected on how maturing s-curves in digital ad businesses might curtail future experimental funding in new technologies. Over the last few months, my thinking on this topic has expanded to encompass a more general, weaker backdrop for innovation fueled by the mega platforms. For two decades, the creation of the digital advertising, ecommerce, and mobile phone markets (especially by Google, Meta, Amazon, and Apple) was a primary engine of asymmetry and new business model formation across a host of products and services. AWS, created and funded by Amazon’s ecommerce business, became the platform for nearly every new tech startup in industries from media to fintech. Businesses like Netflix and Uber were built on cloud platforms like AWS (and smartphone apps running on Android and iOS). We might have eventually arrived at these new digitally-enabled businesses, but it’s possible the tens of billions of dollars needed to build out the infrastructure, subsidized by advertising and ecommerce, was an existential enabler. Likewise, without Azure (which was a response to the competitive threat of AWS and GCP/Google Suite) and Microsoft’s $billions, we likely wouldn’t already have OpenAI’s world-altering ChatGPT. It’s hard to separate out the causes of today’s slowdown for the mega platforms, but it could be a reflection that we have maxed out our potential screen time and have tapped much of the potential of online shopping. Perhaps growth will be a little harder to come by, or perhaps AI represents an entirely new mega platform to subsidize a vast new array of businesses we cannot even imagine today. I’m by no means ready to posthumously eulogize today’s digital giants. If anything, they remain the key enabling layer of the future of the economy, including AI. However, as these platforms experience a slowdown, or perhaps even a de-powerlawing, innovation is shifting from the unbounded, positive feedback loops of the purely digital world to the messier negative feedback loops of the physical world. As this happens, innovation will make inroads into the analog infrastructure layers of the economy. Digital innovation and analog transformation are like two gears spinning at different speeds, and friction inevitably arises at the interface. AI has the potential to greatly speed up the digital gear to a point where the analog gear might not be able to keep up.
Europe’s Top Tech: ASML
Bloomberg published a profile on chip giant ASML featuring a quote from our very own Jon Bathgate. To see more of the team’s thoughts on the importance of semiconductors, see our 2020 whitepaper and podcasts.
Miscellaneous Stuff
Cinéma Vérité
In Personality Crisis: One Night Only, the New York Dolls frontman David Johansen plays his alter ego Buster Poindexter singing the songs of David Johansen and the New York Dolls. Is that confusing? Perhaps it would help if I clarified that it’s a rockumentary from Martin Scorsese. No? Well, there may not be much point in trying to define this film, which is another of Scorsese’s projects, similar to 2019’s Rolling Thunder Review: A Bob Dylan Story, where Scorsese took viewers for a ride through the always-changing narrative that is Bob Dylan. I talked about the Dylan doc briefly here and here, and what particularly attracts me to these reconstructed realities is their commentary on living in the post-truth world. As David Bowie once explained, since the 1970s, we’ve been moving from objective to subjective reality. The Internet rapidly accelerated this transition, and, now, AI is pushing us even deeper into the mist of unreality. I was fortunate enough to see Johansen front the New York Dolls live on a 2008 tour in Denver. It was one of the more memorable shows I’ve attended because, even though I stood up close, I couldn’t figure out what exactly I was seeing on stage. Johansen was caked in makeup and drenched in wardrobe. It appeared as if there was a face hovering over his actual face. It’s an image that still haunts me to this day. I didn’t have the context at the time to understand what I was experiencing, but I can now reflect on the show as an example of a great performer playing with reality like it’s their job to do so. As I watched Personality Crisis last week (currently streaming on Paramount+), I found myself questioning whether some bits of the embedded old footage were real or AI generated. Had Johansen been de-aged or aged? Are all the stories true? Or, perhaps nothing was recast, and it all happened exactly as it appears on the screen. Regardless, you can watch the doc without any of this context because Johansen is mesmerizing and his songs are so damn good. Or, you can watch it as an experiment with reality (even if it’s not!) and an instructional guide for the strange illusions and rewritten histories that AI-generated reality is already bringing us. I was nine in 1987 when David Johansen released his one album under the name of Buster Poindexter, which featured the massive hit “Hot Hot Hot”. When I saw Johansen helm the New York Dolls in 2008, I had no idea he was the same person who belted out that one-hit-wonder summer anthem. As I sit here today, 36 and 15 years removed, respectively, from these two moments in time, I question my own memory. Did Buster Poindexter even exist? Was I really at that concert? I have the ticket stub, but is that sufficient proof? Wikipedia says Buster is real, but what evidence is that? Does it even matter? In the end, is what actually happened important, or is it just the residual memories and feelings that are of consequence? Is this film (and our AI-Age reality) just the new cinéma vérité, as Scorsese calls it? The NYT wrote an entirely serious review of Personality Crisis, whereas the LA Times review concluded that what the documentary “lacks in factual detail it more than makes up for in raw charm” and noted Johansen’s line: “It’s best to leave an incomplete picture of yourself.”
Stuff About Demographics, the Economy, and Investing
NZS Capital Update
We recently welcomed Brett Larson to NZS Capital as the fifth member of our investment team. In the first quarter, we also passed $2B in assets. Driven by a mix of luck, circumstance, and skill, the complex path through time can take many twists and turns, so we are very grateful to have reached this milestone, in no small part thanks to the support of our clients. Now in our fourth year of investing at NZS, we are eagerly looking forward to navigating, on behalf of our investors, what are sure to be interesting times ahead.
✌️-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.
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