SITALWeek #452
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: LLMs contain answers, but only if you know what questions to ask: I reexamine the art of asking better questions; shoeing robots; the connection between stablecoins and US Treasuries demand; grid batteries and nuclear data center woes; reflecting on the political statements of horror movies and our biggest fears of new technology; GLP-1s reduce Alzheimer's risk; a couple of NZS news items; and, much more below.
Stuff about Innovation and Technology
Robooting
Whenever I see a new video of a humanoid robot performing an impressive task – like this latest demo of Boston Dynamics’ Atlas – all I can think about is: why isn’t it wearing shoes? Beyond the obvious benefit of dampening the clunky, menacing noise of robot footfalls, shoes seem like a potentially important buffer for mitigating the wear and tear on both floors and robot feet (and branding opportunity too). Not to mention the potential for slippery indoor and outdoor surfaces, which seem especially dangerous for a lumbering robot. Perhaps an industrial rubber strip could do the trick, but wouldn’t it be a better world if robots wore athletic shoes?
Stablecoin $tability
Following up on stablecoins from #451, I read with interest Tyler Cowen’s op-ed that underscored the role of the US dollar in crypto. Cowen writes: “Most stablecoins are denominated in dollars, and typically they are backed by dollar-denominated securities, if only to avoid exchange-rate risk. If ‘programmable monies’ have a future, which seems likely, that will further help the dominant currency — namely, the US dollar. You might think that other monies will become programmable too. But since stablecoins often are most convenient for international transactions, as well as for internet-connected transactions, the most likely scenario is that stablecoins concentrate interest in the dollar. The US has by far the most influence of any nation over how the internet works.”
It turns out that the US Treasury is thinking about the buoyed demand for the US dollar from stablecoins as well. The minutes from last week’s meeting of the Treasury Borrowing Advisory noted:
The presenting member began by discussing the reasons for, and impact of, the rapid growth in cryptocurrency market capitalization over the past several years. The presenting member observed that because most stablecoin collateral reportedly consists of either Treasury bills or Treasury-backed repurchase agreement transactions, the growth in stablecoins has likely resulted in a modest increase in demand for short-dated Treasury securities.
Subsequently, the presenting member reviewed both ongoing and proposed efforts related to the tokenization of Treasuries. Broadly speaking, tokenization attempts to represent ownership of a Treasury security using blockchain or distributed ledger technology. The Committee then engaged in a discussion of the costs and benefits of tokenization of Treasuries. On the one hand, tokenization could lead both to operational improvements and to innovation in the Treasury market. On the other hand, tokenization presents possible technological, operational, regulatory, and financial stability risks. In view of these risks, the presenting member argued that tokenization in the Treasury market would likely require the development of a privately controlled and permissioned blockchain managed by a trusted government authority. The presenting member concluded by observing that, in spite of potential risks, the growth in digital assets over the past several years currently has only marginal implications for both Treasury issuance and the health of the Treasury market.
If stablecoin growth continues, that modest predicted level of Treasuries demand uptick could become large, allowing Treasuries to effectively become the de facto short-term lender to the US government. Such a scenario, hypothetical as it might be, could lower the US government's cost to borrow, which could also further entrench the role of the US dollar globally.
Power Surge
The US power grid added batteries equivalent to 20 nuclear power plants in just the last four years. Meanwhile, Amazon worries about zombie data centers that lack enough reliable power to stay operational. Amazon also recently lost a bid to tap a nuclear power plant for data center power at the expense of the plant's existing customers.
Miscellaneous Stuff
100 Years of Horror
The Hollywood Reporter has an excellent journey through the last century of horror films. Around a decade ago, I heard the explanation that the horror genre represents the most consistent source of political commentary to emerge from the movie industry. I was perhaps naive to this obvious element of the genre, but once I started thinking through examples, I was surprised by how true it is. The article picks up all the major fears and injustices these movies represented, decade by decade, starting with 1932’s Freaks (which, incidentally, was the movie that I went back and re-watched after first learning about horror’s relation to topical politics). The horror genre is full of paradoxes. What seems like mindless gore can be insightful socio/political analysis, and themes often end up being the inverse of what they first appear: just when you think a 1970s/80s horror movie is railing against feminism, the female protagonist kills the maniacal villain in spectacular fashion. It’s hard to criticize Hollywood Reporter’s masterful list of horror movies and how they represent the fears of the day, but it does seem to lack a big category: fear of modern technology. I would humbly add a few names to the list (some of which might crossover into just action movies rather than full horror flicks, but I’ll take some freedom in the definition). My list is by no means comprehensive, and I will no doubt regret leaving out many great movies the moment this newsletter sends (reply back with your favorite “fear of technology” horror movies!). I should note that the article covers early Hollywood horror based on scientific angst from the 1800s (Frankenstein, for example) through the 1960’s nuclear fears, so I’ll start my list in the 1970s with Westworld (the original Michael Crichton movie about AI turning on its creators from which the more recent HBO series was adapted). The 1980s marked the start of the indelible Terminator franchise, which is perhaps the most salient cautionary tale of autonomous AI run amok, even considering the last 40 years of cinematic blockbusters (The GOAT of AI artistic representation in The Terminator, James Cameron, gave a terrific speech last week at The Special Competitive Studies Project’s AI+Robotics Summit). John Carpenter’s 1988 film They Live is a mashup of fears ranging from aliens to Reaganomics that uses a clever virtual-reality plot mechanism. Virtual Reality became a bigger horror element in the 1990s with movies like The Lawnmower Man and Strange Days (the latter still haunts me whenever I think about new VR advances). It’s probably a stretch to include The Matrix as a horror movie, but the 25-year-old flick of course offers an iconically disturbing look at the mind-bending near future of many different technologies. An obscure 2000’s movie about the surveillance state and isolation of video technology is Adam Rifkin’s 2007 film Look. From the past decade, movies like Ex-Machina and M3gan reflect our resurgent fear of off-the-rails AI. There have also been some incredible series invoking bone-chilling goosebumps, like Black Mirror and Devs. The themes that standout to me across horror’s reflection of new technology are relatively consistent over the last five decades: a loss of control, isolation, loss of humanity itself, and fear of surveillance (loss of privacy).
GLP-1 Brain Boost
According to research published in The Journal of the Alzheimer’s Association, GLP-1s reduce Alzheimer's risk and cognitive decline:
Our study findings align with recent evidence suggesting GLP-1RAs like semaglutide may protect cognitive function. Preclinical research indicates semaglutide's potential in reducing Aβ-mediated neurotoxicity, enhancing autophagy, improving brain glucose uptake, and reducing Aβ plaques and tau tangles. Clinical data, including studies with dulaglutide, show GLP-1RAs can reduce cognitive impairment in patients with T2DM. Data pooled from three randomized, placebo-controlled trials and nationwide prescription registers from Denmark showed that GLP-1RAs were associated with a 53% reduction in all-cause dementia in patients with T2DM. Our large-scale study of 1,094,761 US patients with T2DM found semaglutide associated with a 40% to 70% decrease in first-time AD diagnoses, including a 40% reduction compared to other GLP-1RAs. Ongoing randomized trials are assessing semaglutide's therapeutic effects in early AD. Our findings support conducting future prevention trials to determine semaglutide's ability to delay or slow down the onset of AD.
Stuff About Demographics, the Economy, and Investing
Simplifying Complexity Investing
Jon and Brinton were recently interviewed for Columbia Threadneedle’s Multi-Manager Podcast where they discussed NZS’ investment approach. Here are the Apple and Spotify links.
NZS is Hiring
In other NZS news, we’re hiring for an analytics and IT associate role based in Denver, Colorado. You can find more information about the role and how to apply here.
The Art of Data Query
Before AI became the new dotcom (and that’s OK), we suffered through the relatively fruitless landscape of "big data". This period, centered in the 2010s, probably peaked 8-10 years ago. I remember one conversation with a leading, next-generation “unstructured” database provider (unstructured was the buzzword bingo winner of the big data era) where the founder explained the problem to me: building bigger, smarter databases was easy, but figuring out what questions to ask the data they contained was hard. This conundrum feels especially pressing now that AI has also been thrown into the mix: although there was meaningful machine learning happening around unstructured data, layering on large language models obviously creates an unprecedented ability to glean new answers. But, we still have the same problem: how do we ask better questions? How do we even know what questions we should ask? One strategy I’ve taken is to simply ask whichever AI model (e.g., NotebookLM) I am using: what should I be asking about this topic? Shifting from seeking answers to asking questions is perhaps the most important mental shift many of us need to take in order to stay relevant in the age of AI. Last week, Anthropic demonstrated AI taking control of a computer and doing tasks (in one instance, it got distracted and started searching pictures of Yellowstone!). The Information also reported that Google is working on Project Jarvis to take over computers as well. While we might be somewhat complacent with AI mysteriously crunching data in the cloud and spitting out an answer, it feels significantly more disconcerting to watch an AI agent completely usurp a human task generally accomplished with a mouse, keyboard, and screen. Such developments in AI force us to confront the uncomfortable question: where can I add value in the future? I’ve long felt that developing better skills at questioning is key to our long-term relevance, and, back in #382’s More Q, Less A, I took a deep dive into this topic. As we barrel headlong into our AI future, it seems relevant to take a moment to, once again, question how we question, so I am reposting my thoughts in full here:
More Q, Less A (from January 29, 2023)
Outside the basics of reading, writing, and arithmetic, the educational systems of our formative years largely taught us how to memorize and repeat back facts – we learned a lot of answers to a narrow range of potential questions we might be asked. Owing to the rapid innovation in AI, however, simply knowing a bunch of answers is of decreasing value, as answers proliferate for anyone to access anytime. In SITALWeek #375, I suggested that we’re reaching another technological milestone with AI chatbots and LLMs, and that humans once again need to reassess how best to employ our time and resources. Just as the computer and Internet obsoleted the arduous search for answers using a card catalog and physical volumes of Encyclopedia Britannica, now that we have AI answer engines, we need to move to the next level of problem solving and dot connecting. As I wrote last year:
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…; 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 Edit Everything); and 3) improving decision making processes by incorporating the surplus of new AI generated content and tools (#1 and #3 are subjects I address here).
I’d like to spend some time exploring point number one above: asking better questions. Unfortunately, this topic hasn’t been addressed by mainstream education (at least in my experience in the US). As noted above, the core of my education was rote learning, i.e., here are some facts determined to be historically important – memorize them and repeat them back. Learning to connect concepts in new and interesting ways was rather marginalized, and, outside of advanced science classes, learning to formulate questions was entirely ignored. Granted, the ability to build a mental map and remember lots of things has provided a foundation for the many endeavors of generations of graduates. Now, however, we have an incomprehensible extension of the brain with the Internet and rapidly advancing LLMs like ChatGPT.
For the last few months, I’ve been struggling to find resources to help me learn how to ask better questions (if you know of any, please send them my way). I am not sure if I’m just looking under the wrong rocks, or if asking questions is a relatively unexplored area of human cognition in modern times. Have we been that discouraged from asking questions? As I searched, I kept coming back to my dog-eared copy of Robert Pirsig’s Zen and the Art of Motorcycle Maintenance (ZAMM). I don’t think it’s a coincidence that this book is a favorite of many famous inventors (e.g., Steve Jobs). While many of the concepts covered are highly abstract, there are concrete lessons for problem solving. I’ve struggled in the past to encapsulate this book for those who haven’t read it, so I am going to resist the temptation to distill a book that defies distillation. But, ZAMM is the best resource I have yet found for thinking about the topic of asking questions.
Reviewing ZAMM has helped me derive three key pathways of inquiry: 1) beginner’s mind; 2) Socratic questioning; and 3) Sophist rhetoric. I’ll cover each of these briefly.
Beginner's Mind
Let’s start with beginner’s mind, a concept from Buddhism that informs a childlike openness. Whenever I think about beginner’s mind, I think of Tom Hanks as ten-year-old Josh Baskin in the 1988 movie Big. Thrust into the body of an adult, Josh tries to navigate the seemingly alien behaviors of adults. Josh is fond of saying: “I don’t get it.” Followed by, “I still don’t get it.” Robert Pirsig explores the beginner's mind in the face of “stuckness” in ZAMM. You can get mentally stuck (e.g., due to an inability to adapt or an overdose of rational objectivity) or physically stuck (e.g., by a piece of malfunctioning hardware). Pirsig writes about a stuck screw that has rendered a motorcycle unusable:
Normally screws are so cheap and small and simple you think of them as unimportant. But now, as your Quality awareness becomes stronger, you realize that this one, particular screw is neither cheap nor small nor unimportant. Right now this screw is worth exactly the selling price of the whole motorcycle, because the motorcycle is actually valueless until you get the screw out. With this reevaluation of the screw comes a willingness to expand your knowledge of it.
With the expansion of the knowledge, I would guess, would come a reevaluation of what the screw really is. If you concentrate on it, think about it, stay stuck on it for a long enough time, I would guess that in time you will come to see that the screw is less and less an object typical of a class and more an object unique in itself. Then with more concentration you will begin to see the screw as not even an object at all but as a collection of functions. Your stuckness is gradually eliminating patterns of traditional reason.
In the past when you separated subject and object from one another in a permanent way, your thinking about them got very rigid. You formed a class called "screw" that seemed to be inviolable and more real than the reality you are looking at. And you couldn't think of how to get unstuck because you couldn't think of anything new, because you couldn't see anything new.
Now, in getting that screw out, you aren't interested in what it is. What it is has ceased to be a category of thought and is a continuing direct experience. It's not in the boxcars anymore, it's out in front and capable of change. You are interested in what it does and why it's doing it. You will ask functional questions. Associated with your questions will be a subliminal Quality discrimination identical to the Quality discrimination that led Poincaré to the Fuchsian equations.
What your actual solution is is unimportant as long as it has Quality. Thoughts about the screw as combined rigidness and adhesiveness and about its special helical interlock might lead naturally to solutions of impaction and use of solvents. That is one kind of Quality track. Another track may be to go to the library and look through a catalog of mechanic's tools, in which you might come across a screw extractor that would do the job. Or to call a friend who knows something about mechanical work. Or just to drill the screw out, or just burn it out with a torch. Or you might just, as a result of your meditative attention to the screw, come up with some new way of extracting it that has never been thought of before and that beats all the rest and is patentable and makes you a millionaire five years from now. There's no predicting what's on that Quality track. The solutions all are simple-after you have arrived at them. But they're simple only when you know already what they are.
Are we still talking about screws here? Not exactly:
Right now this screw is worth exactly the selling price of the whole motorcycle, because the attitude of "beginner's mind." You're right at the front end of the train of knowledge, at the track of reality itself. Consider, for a change, that this is a moment to be not feared but cultivated. If your mind is truly, profoundly stuck, then you may be much better off than when it was loaded with ideas.
The solution to the problem often at first seems unimportant or undesirable, but the state of stuckness allows it, in time, to assume its true importance. It seemed small because your previous rigid evaluation which led to the stuckness made it small.
But now consider the fact that no matter how hard you try to hang on to it, this stuckness is bound to disappear. Your mind will naturally and freely move toward a solution.
This is the first type of questioning, and it’s a primal, childlike way to form enquiries on a subject. By removing the barriers of preconceived notions, conclusions, and biases, you can let your mind quest its way to the solution, becoming open to any possible truth about the situation, no matter how inconceivable it might have first seemed. You have to throw out all preformed models of what something (e.g., a stuck screw) is and see it as something completely different to be probed.
Socratic Questioning
Now let’s look at the second type of questioning: the Socratic method. While the term might sound familiar, it’s not necessarily a concept most of us deploy daily unless we have a philosophy or law degree (of which I have neither, so what you read here is simply the spirit of the idea that I’ve twisted to my purposes). The Socratic method is a type of inquisition that helps someone get to the root, or basic assumptions, of their beliefs about a topic. I think of it as a way to drive toward first principles, i.e., an idea boiled down to its core. The Socratic method is what Pirsig refers to as the “Church of Reason”, and it’s defined by placing rationality on a pedestal. Logic, rational thinking, and the scientific method are used to uncover the real facts or motivations behind a belief or idea. The Socratic method is intended as a confrontation between two people where one is interrogating the other. An analogy I like to use for this is a therapist and a patient, where the patient is blinded by something that keeps them from seeing the real reason for a problem in their life. If you just keep asking questions (starting more broadly and then with increasing precision), eventually you can reach an “a-ha” lightbulb moment. This video contains an explainer on the Socratic method by dissecting a scene in the movie Pulp Fiction.
Rhetoric
The third and form of questioning I’ll mention here is Sophist rhetoric. Sophists reason by arguing multiple, opposing views of a particular question, regardless of their own beliefs on the topic. We often think of a rhetorical question as one asked without expectation of an actual answer. However, Aristotle defined rhetoric as: "the power of perceiving in every thing that which is capable of producing persuasion." History calls it specious reasoning, but I define rhetoric as the art of bullshitting. Venturing out of Ancient Greece and into the 21st century of fake news and broken reality, bullshitting transforms into grounds for inquiry. As longtime readers know, I often discuss the human brain’s penchant for storytelling. We tell stories about everything, to ourselves and others, nonstop. Most of the time, these stories are nonsense, or only very tenuously related to objective reality. However, in these stories lies a type of questioning that entails making stuff up and seeing where it goes. There is an element of childlike beginner’s mind to it, as well as an element of a Socratic back and forth, like swinging a pendulum to try and hit upon the truth. But, in the end, it’s a way to explore alternate realities, i.e., different potential truths, to see if we stumble upon a narrative that illuminates the key questions we should be asking.
Pirsig’s alter ego, Phaedrus, struggles throughout ZAMM as he tries to tear down modern socioeconomic constructs built entirely on logic and rational thinking. In reality, we have become so enmeshed in – and fooled by – faulty logic and rhetoric that we can no longer distinguish truth from fiction – we actually believe the stories we tell ourselves and hear from others. Overapplied logical reasoning can also fail us by excluding ambiguity, subtleties, and the vast interconnectedness of everything. These are all key aspects of nondualistic thinking that a Western upbringing tends to exclude, or, in most cases, denies the existence of entirely. For example, science can’t possibly pin down any one single definition of normal, rational human behavior, yet humans have all sorts of arguments about myriad behaviors we see as unequivocally right or wrong. Reintroduction of nondualism to our reasoning can help us to spot ideas interconnected in strange and unexpected ways – ways that might defy our sense of logic but end up being closer to the truth. This, I believe, is the heart of Pirsig’s elusive concept of Quality: by combining nondualism and pre-logic concepts with logic and scientific reasoning, we can make more progress towards understanding than we would by relying on either dualistic or nondualistic thought alone.
Thus, to learn to ask better questions, I believe we must travel back in time to that foreign period before Plato, when humans used a different framework for interrogating the world around them. Specifically, we need to thoughtfully combine the Buddhists’ beginner’s mind and the Sophists bullshitter’s mind, both of which rely on nondualistic thinking, before we add a dash of the more modern Socratic logic and scientific inquiry. (Note: the modern conception of the Socratic method is a concept that comes from Plato’s representation of Socrates rather than Socrates directly, and I am glossing over and simplifying a very complex disagreement between Sophists and Socrates because [1] I am not an expert, and [2] I am merely using Greek philosophers as shorthand for the points I am making).
I’d like to overlay this framework with a supplemental fourth type of inquiry: editing. Editing is becoming one of the most important human skills in a world filled with infinite answers accessible through AI. Editing itself is a form of questioning: is this important? Is this of value? Or, as Pirsig might ask: can we find Quality in something? The Buddhists have a way of editing with two simple questions: Is it true? And, is it useful? The former is increasingly difficult to determine, but the latter is a little bit easier to suss out: if a question leads you to a useful answer, then pare down everything else that appears untrue or not useful.
The ultimate goal of questioning, of course, is to make sense of the complex world around us and glimpse probable future paths by identifying cognitive biases and excluding unhelpful stories of fantasy and misdirection. However, the four paths of inquiry I’ve discussed here – beginner’s mind, Socratic questioning, Sophist rhetoric, and editing – do not work nearly as well when practiced in the isolation of one person’s brain. You need someone else, or ideally a small team, with which to engage and hone the complex artform of asking questions. Be prepared for a learning curve given the lack of prior emphasis on such skills. However, learning to ask better questions is becoming existential as we find ourselves increasingly awash in a sea of answers. Given these circumstances, we’re better off determining which questions shine a light on key truths rather than endlessly sifting through noise and misinformation. AI may have all the answers, but the journey of interrogation is a creative endeavor that, at least for now, is still within the domain of humans.
✌️-Brad
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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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