SITALWeek #442
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: fifteen years ago, right as the Great Recession was ending, US tech stocks began an epic run, compounding an astounding 20% per year through last week; a look at the opposing AI strategies of the big five tech platforms; Nature discusses the increase in custom vaccines for cancer treatment; greener steel; adults are buying more kids; toys for themselves than for young children; investors walking away from VC capital calls may signal a broader issue in illiquid assets; and, much more below.
Stuff about Innovation and Technology
Adjuvant Intelligence
Cancer vaccines could become a regular part of oncology treatment as progress is made in personalized mRNA shots and other methodologies, according to a recent news article in Nature. One of the factors conferring success has been the use of advanced technology to tailor treatments:
A bigger differentiator, researchers say, could be the computational engines that help to determine the vaccine’s composition. Each engine has its own proprietary suite of tools that it uses to select which neoantigens to target.
Most companies start with genetic sequencing of data from tumours and healthy tissues to reveal the mutations that cropped up during cancer development. T cells will not recognize all of these mutations, however, so algorithms are used to prioritize a subset — Moderna uses up to 34, BioNTech up to 20 — that are predicted to have the most potent immune-stimulating effects.
Such predictions are made on the basis of various factors, such as the levels at which neoantigens are expressed on tumour surfaces and their anticipated binding to cellular receptors that aid in provoking a T-cell response. Machine-learning models then incorporate experimental data to improve the accuracy of these tools.
Green Steel
Greenifying the $1T steel industry, which accounts for 10% of global carbon emissions, is the object of numerous startups. For example, Colorado-based Electra has developed an electrochemical process for producing iron plates from iron ore (including low-grade ores typically discarded by the industry) without fossil fuels. Their methodology involves dissolving the iron ore in an acidic solution, separating out the iron ions, and depositing them on a door-sized cathode surface. The whole process requires temperatures of only 140 °F (60 °C) vs. the conventional pyrometallurgical process of melting iron ore in a coke-fired blast furnace at nearly 3000 °F (1600 °C). The iron plates can be further converted to green steel using an electric arc furnace. The ramp to green steel is a long one as Electra plans to scale to only one million tons by 2030, a fraction of the current two-billion-metric-ton industry.
Fight or Freeze
With Apple finally declaring their AI intentions, I think it’s interesting to contrast the AI strategies of the five consumer/cloud/enterprise mega tech platforms, Apple, Google, Microsoft, Meta, and Amazon. What stands out to me is how differently the big five tech companies reacted to the “ChatGPT moment” in late 2022 when nearly everyone was caught flat footed by the sheer power and open-ended possibilities brought into being by the ability to converse with a computer intelligence. Microsoft had an inside line – thanks to Bill Gates’ work and their bankrolling of OpenAI – so their aggressive adaptation of their products to a conversational UI wasn’t too surprising. Likewise, Google and Meta both audaciously rose to the AI challenge. Google combined DeepMind with Google Brain and launched a series of impressive products, ranging from Search Generative to Gemini 1.5 and Gemma. Meta launched Llama and amassed a stockpile of GPUs in an attempt to garner developer attention. In stark contrast, Apple hasn’t moved much past the starting line. They released a series of small models that have a mediocre benchmark scoring, and they seem to be leaving more interesting AI use cases to developers, letting them choose from among competitors’ APIs (likely ChatGPT, Gemini, Llama, or a combination of small and large models) to build apps. Likewise, Amazon still seems frozen by the bright lights of AI. Rather than building their own AI models, Amazon has instead invested in startups like Anthropic. While I hate to generalize from just five examples, the differentiating factor in the urgency of reaction to LLMs seems to be largely connected to the role that company founders are playing. The founders of Google, Meta, and Microsoft are still actively involved, while Apple and Amazon are run by caretaker CEOs, who appear (from the outside) to be lethargic and/or pathologically risk averse. Apple and Amazon’s best bet from here is to enable developers. For Apple, that means giving developers full access to the native neural processes on their devices and working with all of the AI model creators to optimize on-device processing. For Amazon, that means investing in the right hardware to lure developers over with lower cost and/or better options than what Google and Microsoft’s clouds are offering.
Miscellaneous Stuff
I Don’t Wanna Grow Up
Adult consumers in the US purchased more children’s toys for themselves than for preschoolers for the first time ever, according to research firm Circana. These self-indulgent purchases, driven by nostalgia and other factors, totaled $1.5B in the first quarter of 2024.
Adding Time to the Clock for Carbon-Based Life
New data from the JWST suggest that carbon was far more abundant soon after the Big Bang than previously thought. Earlier data pegged carbon’s presence at around one billion years after the Big Bang; however, the JWST spotted a cloud of carbon from when the Universe was only around 350 million years old. Carbon is formed inside large stars and then dispersed in explosive supernovas. The presence of heavier, star-forged elements like carbon and oxygen starts the clock ticking for when life-sustaining planets could have conceivably coalesced from stellar debris. However, as mentioned last week, the mix of circumstances that would actually yield a planet capable of supporting intelligent life (as we know it) is far more rare than we previously thought.
Heritable Emissions
An attempt to curtail cow methane emissions reveals that some bovines are bigger offenders than others:
For free-roaming livestock, another promising option is to breed animals that emit less methane. For sheep or cattle, animals of the same size and identical diet can have methane outputs that vary by as much as 30 percent or 40 percent. “That’s a lot of diversity to play with,” says Montgomery. The trait appears to be as heritable as many other traits that breeders routinely select for, and breeders have already begun incorporating methane production into their selection criteria for Canadian dairy cattle, Irish beef cattle and New Zealand sheep.
Stuff About Demographics, the Economy, and Investing
Private Asset Malaise
Some investors are defaulting on their venture capital funding commitments, likely due to a variety of factors, including high interest rates, the dearth of IPOs, and a run of underperformance for early-round, high-valuation VC investments during the pandemic, according to Business Insider (the article cites a firm that is raising capital to buy distressed venture stakes). The multi-year low-rate environment that preceded and predominated the pandemic compelled many institutional investors to allocate a higher percentage of their assets to illiquid private equity, venture investments, real estate, etc. (in some cases, remarkably, investors actually borrowed money to do so). However, post-pandemic rate hikes have revealed potential strains on this strategy and have rendered other liquid asset classes more attractive. In some instances, institutional investors in need of liquidity are selling their PE stakes at steep discounts. It’s been difficult for many private assets to match the phenomenal returns of the public markets (see next section). BI reckons there could be as many as 8500 venture funds that have stopped investing for a variety of reasons, including a lack of funding from their investor base. At the beginning of the Fed rate hike cycle in June of 2022, I wrote about some of the issues that can arise when a highly levered system endures higher rates for too long in The Point at Which Higher Rates Collapse the Economy. The pain of higher rates has not yet become existential for asset classes rife with excessive amounts of leverage, but that point could arrive if rates stay high for another year or two.
Tech Stock Outperformance
The mighty run of US tech stocks has been something to behold. Fifteen years ago, markets were on their back as they worked through the Great Recession. Remarkably, since June of 2009, the Morningstar US Technology Index shows a total return of just under 1500%, representing a compound annual growth rate of just over 20%. (Note: The S&P 500 IT Sector shows an even greater 21.6% compound annual total return over the same period.) That’s an astonishing performance, and even more remarkable when you look at the power law dynamics, network effects, and cash flow that have driven a small number of companies to become a large percentage of the index. These mega cloud, software, and hardware platforms don’t just have big market values, they have become the drivers of the global economy, providing both growth and deflationary productivity gains across the ecosystems of companies/services they have enabled.
Let’s return, however, to the miracle of compounding. A $100,000 US tech index investment made fifteen years ago would be worth over $1.8M today. If the same return rate were to continue for the next fifteen years, that number would balloon to $35M in 2039 – 350 times the original investment! Of course, not everyone experiences this level of return in the market – even if they bet on the right sector. The past fifteen years have been far from a steady trajectory, marked by bull runs, bearish punctuations, a pandemic, etc., and it’s this chaos that trips up otherwise savvy investors. Often, painful downturns induce investors to sell when they should hold/buy, while periods of market hysteria cause FOMO-susceptible investors to imprudently pile onto their positions.
To see that everyone is susceptible to FOMO investing, let’s take a look at one tech investment made by perhaps the most famous investor, Warren Buffett. Nearly four years ago, in September of 2020 (in the middle of a bull market for tech stocks), I wrote about the IPO of Snowflake in the context of how to approach highly valued, very-high-growth businesses at the portfolio level for investors. (Note: I also followed up that post in early 2021 with some detailed thoughts on expected returns for high-growth software businesses.) I pointed out that, to my surprise, Berkshire Hathaway invested $730M in the Snowflake IPO offering. Post IPO, the stock was trading at around 100x the estimated revenue for 2021, which seemed a bit rich for Berkshire, particularly given Buffett's prior disdain for IPOs. According to filings, Berkshire still owns the same position in Snowflake, and they are roughly flat on the stock – with only a 4-5% gain – compared to a nearly 70% return in the S&P 500 over the same time period (and, the ~15% growth in shares outstanding since the IPO has diluted their ownership claim on the business). Of course, I am talking about only one stock that soured relative to the rest of the market, and Berkshire has done much better with their most famous tech investment, Apple.
It’s always difficult at any given time to know the right level of offense and defense to play when constructing a portfolio because, frankly, no one can know the future (we describe our strategy for portfolio construction under uncertain conditions in Complexity Investing; see also PDS). Our best guesses may turn out to be overly optimistic or not nearly optimistic enough. Who would have thought that, back in the summer of 2009, we were staring down a 20%+ annual return for the next fifteen years? At that time, the market was still in the depths of a historic correction following the collapse of “too big to fail” banks. By the end of 2009, hindsight showed that June 2009 marked the official end of the recession, perhaps proving that it is always darkest before the dawn – and highlighting the importance of staying grounded in optimism long term. Of course, if you live under the influence of social media and TV news algorithms like most folks these days, you might be amongst the 49% of Americans who believe the S&P 500 index is down, rather than up, this year. That’s a staggering level of delusion induced by algorithmic mind control. Hopefully, those folks didn’t sit on the sidelines for the last decade under a false sense of pessimism. While it's important to always have some element of defense, it's a good lesson to not let pessimism or cynicism keep you from missing the blue sky upside that can persist far longer than we might think.
✌️-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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