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: I look at the shift from grocery stores to eating out in the US and contemplate whether it's a digitally-driven sustainable trend or an anomaly; the uneven results from hybrid work and the risks of ordering employees back; despite claims, big corporations are thoughtlessly rolling out AI with far too few guardrails; what personality will you pick for your AI chat companion? metagenomic DNA sequencing; young galaxies; ditching strategic plans; and, much more below.

Stuff about Innovation and Technology
Shotgun Metagenomic Sequencing
Metagenomic DNA sequencing using the shotgun approach analyzes all genetic material present in a clinical sample (rather than looking for specific markers) typically with the goal of mapping its microbiome component. For example, this method can be used to profile gut microorganisms or diagnose rare diseases caused by brain-eating amoebas. The WSJ explains: “A typical sample might yield 100 million snippets of genetic material...Some 99% would be human. Those sequences are computationally stripped away and the remaining 1 million pieces are screened against all the sequences in GenBank in an effort to find a match.” Direct genetic analysis of samples using next-gen sequencing allows for more in-depth, comprehensive profiling than diagnostic methods that rely on culturing (to increase microbe concentrations), as many of these pathogens do not readily proliferate in vitro. Metagenomic analysis can also identify the causative microbial agents of pneumonia and sepsis, which are often missed by other diagnostic methods, allowing treatment before the diseases become terminal. Another example is the metagenomic research test for urinary tract infections, which can have a multitude of causative agents with varying degrees of antibiotic susceptibility. Determining the identity and prevalence of antibiotic-resistant bacteria could perhaps aid in the AI-driven creation of novel antibiotics. It appears to me that there is an opportunity to combine more widespread genomic testing with AI that can help design drugs and antibiotics along with identifying patients for clinical trials. 

WFH vs. Return to Office Battle
There have been numerous headlines featuring CEOs recalling employees to the office for at least three or four workdays per week. The skeptic in me sees these as temporary orders meant to cause people to quit, i.e., sneaky layoff maneuvers. But, I also think many companies have struggled to remain as efficient and productive while working remotely. For the companies that are willing to invest in the tools and effort to maintain/adapt corporate culture, there seems to still be plenty of fans of remote and hybrid working. Zillow detailed in its latest quarterly shareholder letter [PDF] that embracing work location flexibility “brought us more stability during the pandemic and continues to be the right call: Voluntary attrition declined steadily across the organization in 2022, down more than half in Q4 compared to Q1, and our workforce is more dispersed, more diverse and more engaged in our mission. We’ve also been able to dramatically broaden our candidate pool and attract talent at a much greater rate than before the pandemic, with four times as many applicants per job posting compared to 2019. Last and most important, we are seeing increases in productivity in critical areas of our business — for example, our Premier Agent sales team is more productive today than it was before the pandemic.” In related flexible-work news, a trial of 61 UK companies and 3,000 employees experimenting with a four-day work week resulted in 56 companies continuing the experiment after the trial period. With ongoing tight labor markets, the path forward seems likely to involve a combination of flexible policies to attract the most talented workers and a willingness to embrace technology to create a superior (or at least sustaining) corporate culture, until, of course, AI ultimately replaces everyone! Tech companies should be especially cautious about ordering employees back to the office given the increased demand for engineers from non-tech companies deploying digital technologies, including AI, across their businesses. As a side note, one area of media that should benefit from more commuters returning to the office is podcasts, which have suffered as of late. On the heels of data showing a significant decline in new podcasts, NPR reported its recent layoffs were largely due to declining podcast ad revenues.

Reactionary Chat Guardrails
Last week in You Auto-Complete Me, I reported on how LLMs like ChatGPT function as elaborate autocomplete engines, which is actually mimetic of human behavior. I concluded by suggesting that AI chatbots need to have a morality: “perhaps the more important question at hand for the survival and usefulness of LLMs is: can we teach them to be kinder than humans when they autocomplete? If Bing’s Sydney personality is simply a derivative of the most logical fill-in-the-blank response based on its compendium of text, then can we give it a morality or the emotional equivalent of Asimov’s Laws? Recall that the first of Asimov’s Three Laws of Robotics is: ‘A robot may not injure a human being or, through inaction, allow a human being to come to harm’. Sticks and stones may break our bones, but it turns out words from robots might also hurt us.” Subsequent to last week’s post, Microsoft erected some guardrails on Bing-Chat, and OpenAI (creator of ChatGPT) posted a blog on how they think about morality and behavior of chatbots:
We believe that AI should be a useful tool for individual people, and thus customizable by each user up to limits defined by society. Therefore, we are developing an upgrade to ChatGPT to allow users to easily customize its behavior.
This will mean allowing system outputs that other people (ourselves included) may strongly disagree with. Striking the right balance here will be challenging–taking customization to the extreme would risk enabling malicious uses of our technology and sycophantic AIs that mindlessly amplify people’s existing beliefs.
There will therefore always be some bounds on system behavior. The challenge is defining what those bounds are. If we try to make all of these determinations on our own, or if we try to develop a single, monolithic AI system, we will be failing in the commitment we make in our Charter to “avoid undue concentration of power.”
Thus, the company plans to allow users to adjust the morality and tone of the chatbot to meet their personal needs. While I sympathize with people who want a chatbot that reflects certain religious, political, or philosophical values, I am still hopeful there is a foundational set of beliefs humans can agree on. What OpenAI describes appears to be more of an “AgreeBot” or a “ConfirmationBiasBot” rather than an intelligent AI assistant. My mind wanders to books like The World’s Religions, which details the commonalities across the great wisdom traditions over the last few thousand years of recorded history, or the various books that attempt to derive a basic human morality from both evolution and religion. OpenAI doubled down on their plans to offer customized AI in the future in this blog post where they also claimed to be very cautious about deploying products as we approach artificial general intelligence (AGI). Their actions so far with ChatGPT and Bing seem to indicate a far more dangerous course. I find it troubling that such bounds weren’t contemplated before these AI products were released into the wild. Again, it’s just the kind of corporate “run amok” behavior Elon Musk was supposedly trying to avoid when he founded OpenAI. It feels like we are teetering on a future of “My AI can beat up your AI” divisiveness.

If we are going to be using these chatbots as I envision, it will be a close relationship with a lot of personal context. Therefore, we need to each decide what we are looking for in our customizable AI friends: do we want a mentor/teacher, parental figure, spiritual guide, romantic consort, the personality of a deceased relative or historical figure, a Socratic debate partner, Pauly Shore, a sycophant, or a business partner? Perhaps, a therapist is in order for most of us. Regardless of which path we choose, AI companions are increasingly going to complete us, acting as an extension of our brain and body.

Divert to Digital Dining
Recent data on strong restaurant sales in the US have been rolling around in my head quite a bit. While the government data is always subject to revision, the numbers suggest an acceleration in out-of-home meal buying that goes beyond the easy comparison to last year, when fewer people were eating out due to the peak of the Omicron COVID wave. I am most intrigued by the divergence in spend between restaurants and grocery stores, with the latter lagging substantially. Commerce Department data suggest a seasonally adjusted, sequential growth of 7% y/y for restaurant spend (corresponding to 25% total growth y/y) vs. only a slight uptick in grocery store spend (which, given inflation, would imply an actual decline). When I look at the inflation-adjusted data (using the proxy of urban food inflation as my adjustment factor), the trend of restaurants gaining share from grocery is fairly dramatic, e.g., see the divergence between restaurants (gray line) and grocery stores (yellow line) in this chart I put together. I heard the CEO of the restaurant food supplier Sysco corroborate strong January data at the CAGNY conference last week. Another trend of note is that while people are eating more restaurant food, the growth is largely in takeout/delivery rather than dine-in. The National Restaurant Association noted that seated diners were down 16% vs. pre-pandemic levels but delivery and drive-through were higher. Off-premises business tends to be good for restaurants as it requires less labor and allows higher throughput in the kitchen. With these new data, I revisited a whitepaper I wrote in 2019, before the pandemic was ever a consideration, called The Evolution of the Meal. In that paper, I suggested that food delivery was likely only to be economically viable if it happened with some combination of memberships, delivery routing/density, and vertical integration. Further, I suggested grocery stores, with their thin margins, were vulnerable to even modest behavioral changes (and that, likely, the labor transfer of digital ordering to grocery stores would relegate its use to affluent customers only). My main conclusion four years ago in that paper was that the range of outcomes for how we consume food appeared to be widening. What has changed since then? Overall, I think it’s still too early to know if the combination of pandemic behavioral changes, demographics, and macroeconomic factors point to a specific future path for food, but it’s worth highlighting a few interesting hypotheses. 1) Digital ordering through apps and delivery platforms, like Uber Eats and DoorDash in the US, has clearly increased the convenience factor and created a new habit for many households. This appears to be generating a network effect around more restaurants offering takeout through apps (and embracing digital technology), thus driving more consumer adoption (while simultaneously making delivery more economically viable with improved delivery density). There are winners and losers from this trend as historical category leaders like pizza delivery are losing out with the increased selection of participating restaurants. 2) Grocery store inflation has been such that on a relative basis, eating out is not as expensive as it was, so there is a degree of arbitrage that might be in play. 3) In the more speculative realm, I might suggest that demographics are ushering in a younger generation of prime consumers (i.e., Millennials entering their 30s and having kids) who are, perhaps, not as interested in devoting significant time/energy to shopping and at-home meal prep as were prior generations (now aging out of their high-consumption years, and may themselves be taking more advantage of the conveniences of digital food ordering). 4) On the supply side of the equation, restaurants, which early on were reluctant to give up a profit bounty to platforms like DoorDash, might now have the technologies and processes in place to take advantage of those benefits I noted above (memberships, delivery routing/density, and vertical integration), especially given the tight labor market that makes it harder to serve in-person. 5) If (and it’s still a big if) meals are going “digital”, then we might expect to see a power law (concentrated head with a long tail) form around digital ordering/technology/delivery platforms as well as restaurant brands. However, given the diversity of tastes and preferences, we may see a power law with platforms but not restaurants; rather, we could see restaurant diversification as friction is reduced for ordering a variety of options, including fare from non-chains. 6) Lastly, I’ll point out that advertising is likely to play a much bigger role, as restaurants will effectively have to bid on your stomach with ads/incentives every time you open a food app. I’m holding any conclusions on the recent data loosely as we remain in an odd economic transition period out of the pandemic era, but I am intrigued by the shifting behaviors that appear to be digitally driven.

Miscellaneous Stuff
Model-Breaking Baby Galaxies
The James Webb Space Telescope continues to find evidence that huge galaxies were present much sooner after the Big Bang than predicted by our current models for the Universe’s formation. The large, young galaxies visible through JWST are only 350M years old. University of Nottingham astrophysicist Dr. Emma Chapman noted: “The discovery of such massive galaxies so soon after the big bang suggests that the dark ages may not have been so dark after all, and that the universe may have been awash with star formation far earlier than we thought.”

Fentanyl’s Rampage
Drug overdoses have risen from 60% of accidental deaths in NYC to 80-85% due to the rise in fentanyl-laced cocaine, heroin, and other synthetic drugs. Similar overdose trends are present across the US as fentanyl-related overdoses reach a record high, according to the NYT.

Stuff About Demographics, the Economy, and Investing
Forgoing Forecasting?
The need to forecast is strong in corporate boardrooms. Most execs cling to their business plans, five year strategic initiatives, and EPS targets like warm security blankets. So, I don’t believe it for a minute when the FT reports that some execs are foregoing detailed forecasts for more loosely held plans. Ikea’s CEO, for example, claims: “Instead of setting out specific goals for the year, it has a set of ‘scenarios’ to give the business wiggle room as the outlook changes. It means acknowledging that widely different outcomes are possible. ‘It’s teaching us agility in how we operate.’” Well, if it’s true that CEOs are willing to embrace adaptability and ditch the false belief in a predictable future, then we humbly submit our 2014 paper Complexity Investing and 2019’s Redefining Margin of Safety as blueprints for charting a path into the unknown future. Given the speed with which digital disruption and AI are progressing today, it’s a good time to hold all your views of the future as loosely as possible.

✌️-Brad

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