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I made a comment recently speculating that Terence Tao may be a paid promoter of AI. After some off-site discussion elsewhere, our resident shaman on whom the mods cast a long-duration silence posted my comment as a circus exhibit on Twitter to demonstrate a dangerous form of psychosis. Fortunately, OpenAI deemed this a worthy time to intervene and publish an ad featuring Terence Tao, who has taken time out of his busy schedule to assist this struggling non-profit with their promotional.
I want to dissect what I think is really going on.
For starters, every time I sit down to watch WoW on YouTube, I'm greeted with my favourite streamer telling me about the super fun game Raid Shadow Legends, which I should definitely download and play because it's super fun. Is the OpenAI-Terence Tao relationship like this? Not really. Terence Tao does appear to actually spend some time playing around with LLMs. Further, he's not exactly saying a bunch of empty marketing blather, either. In fact, probably to the annoyance of some readers here, I want to take a couple paragraphs for a technical aside, because there is actually subtlety here. I'll bound this in horizontal bars so non-technical readers can skip it:
The main talking point is that automated theorem proving is a perfect fit for LLMs precisely because it's not vulnerable to their main catastrophic failure mode: hallucination. The model can hallucinate whatever it wants, but the text still goes into the theorem prover, and if it's bullshit, well, the prover just rejects it and you query the LLM again. Do this in a loop, burn whatever unholy amount of compute you want, and if the loop stops, you've got yourself a proof! (Well, or a bug in the theorem prover. Or a "You've run out of tokens on your budget" error message. But I digress). This story is largely true. There's a giant asterisk of "Uh, so how much compute we talkin' about?", and the answer is "As much as you need or can afford, whichever comes first!" Which is, of course, the business model.
I will point out one additional technical nit-pick that annoys me because Terence Tao is working in Lean 4, which is a dependently-typed theorem prover. In classical mathematics, one is concerned solely with whether a theorem is true or false, and the structure of the proof is basically irrelevant as long as it's valid. Lean 4 is not based on this model. Rather, it's based on a more computationally-motivated model of mathematics pioneered by Brouwer in the early 1900s called "constructivism." In this world, the question isn't the boolean notion of "Is this theorem true or false?" but rather the related but distinct notion of "Which proof do you have?" To ground this in practical terms, consider the following example: I can prove that True|False and Yes|No are isomorphic, but I can do so in multiple ways: I can map True to Yes and False to No, or I can map True to No and False to Yes (and then show that there are respective inverses which preserve identity, obviously). It is in this sense that one can meaningfully say "Which proof of isomorphism?" when I say I have a proof of isomorphism. Perhaps this all sounds like technobabble, but to connect it to the preceding paragraph: you can immediately see how this does reveal some cracks into the narrative being sold there. It does actually matter which proof is produced, not merely in a social sense of "can any human understand this wall of text the LLM spit out", but in a technical, computationally-relevant sense. For pure mathematics, this distinction is often not considered important -- in fact, many classical mathematicians aren't even aware of the difference, and will be confused if you try to explain it to them and think this is all a bit silly. However, it's not a silly or minor distinction for the following reason: one of the motivations of this computational model for "theorem provers" (it's really a programming language + compiler, rebranded for mathematicians) like Lean is so that formal methods can be applied not just to classical mathematics, but to software in general. And as soon as you enter software formalisation, this distinction is no mere intellectual curiosity, but of paramount relevance. The classical-style logic in the preceding paragraph does not apply to constructivist logic used for software formalisation! I'm sure this distinction is not lost on Terence Tao. But that doesn't concern OpenAI. OpenAI is more concerned with whether the distinction will be lost on the MBAs listening to Terence Tao, and the answer is "absolutely."
Ok, no more technical details like that, I promise. Back to the social level:
So, I mentioned Raid Shadow Legends is a poor metaphor for the OpenAI-Tao relationship. Let me propose some better ones: Michael Phelps and Wheaties (with the added benefit that Terence Tao never smokes weed. See, this is why mathematicians are better than athletes), or better yet, attending Harvard University. This may seem like a strange juxtaposition, but I've done so intentionally, because the marketing is obvious in one but subtle in the other, but it's actually the same trick: the goal is to misattribute performance. With Wheaties, the goal is to sell the notion that Michael Phelps is a great swimmer because he has a healthy diet of stuff like Wheaties, and if you eat Wheaties, maybe you'll perform well, too! Of course, in reality, he was eating sugar-coated french toast and chocolate chip pancakes because he needed 10k Calories/day just to break even on energy, and the reason he's such an awesome swimmer is in large part genetics. Wheaties, or anything similar to it, has virtually no relevance to Michael Phelps at all. But what about Harvard?
Well, Harvard sells the image so well that most people outside this forum outright believe the illusion. The illusion is, of course, that attending Harvard makes you smart and likely to succeed, rather than Harvard accepting only people who were smart and likely to succeed in the first place and thus redirecting credit for these future achievements to Harvard. Mark Zuckerberg may see Harvard as a pointless waste of time, but the world sees Harvard as "The university that made Mark Zuckerberg happen!"
I like the Harvard analogy because this is surely the intent with Terence Tao. There's a high chance sooner or later Terence Tao will prove something cool "using" ChatGPT, and if he does, it would be really awesome if we could make it sound like the secret ingredient in the ChatGPT-Terence Tao alliance was ChatGPT, when obviously the actual secret ingredient is Terence Tao. The analogy I always use for this is stone soup, a European folktale where starving travelers dupe gullible townsfolk into helping them make soup from stones by requesting "extra" ingredients bit by bit until they've just made actual soup, thus astonishing the gullible townsfolk.
There are a lot of other things I could say on this, especially on the technical side, as there are a lot of clever tricks you can pull to make it look like a model is doing more than it really is, but I'll stop for now and conclude with this:
Just be cognizant that OpenAI, and all the other LLM vendors, do marketing. They have an enormous budget that dwarfs anything you have ever seen before. Remember the reality distortion field of Black Lives Matter? Or trans people? Imagine that, but like... two orders of magnitude larger. That is the level of persuasive pressure we're dealing with here.
Just take it all with a grain of salt.
I’m confident Terrace Tao is pro-AI both because it funds him and he finds it interesting and potentially useful. That’s academia (usually).
OpenAI’s model did solve a long-standing Erdos problem (not in Lean, hand-checked by mathematicians, but still)
I think crypto is a good analogy. There is actual tech there, and many do indeed believe in it (me being among them). But the hype and noise was wildly disproportionate to what was realistic and done.
At this point, if you put your bet on anything other than "Slightly improved Bitcoin with privacy that was obviously intended originally but not known how to do at the time," you’re probably down 70+%, if not entirely liquidated. Entire narratives about "business on the blockchain!" were complete nonsense.
Fun fact: Sam Altman himself launched a crypto coin back in the heyday. It's down 96%.
I think crypto isn't such a good analogy. I never saw anyone get value out of crypto qua crypto. As an asset and an investment, yes, and occasionally as a way of paying for mildly shady or super-techy things, but in general the value proposition just never seems to have manifested to me.
Whereas I get massive value out of AI. For writing, for my hobby projects. My startup would be facing much larger headwinds without AI for coding and research. I think the hype is still kind of overdone, but only because the hype is so strong that only the immanent eschaton could live up to it and because it's not clear how much of a directly-related ecosystem there will be for third parties.
Minor point, this seems to be the wrong way round. The asset aspect is the boring (if hyped) part, and the proposal to do financial transactions without a trusted party (which can easily coerced to block some transactions by the feds) was the innovation. Of course, this freedom to do transactions has mostly been used in darknet marketplaces and for ransomware, but that's humans for you.
I will grant you that the anarcho-libertarian utopia promised by the blockchain has not happened, though. 'crypto' is 99% get-rich-quick scams, and the 1% are probably mostly ransomware and the like, with 0.01% being nerds buying acid or donating to wikileaks. Legal crypto exchanges are very much centralized, and banking laws in the US are probably broad enough that the feds can jail you for decades if you put substantial amounts of your money through a mix or otherwise annoy them.
And gen-AI is definitely the bigger deal, sure. It might take six or eight orders of magnitudes more money to train a LLM than it takes to train an individual human, but my feeling is that if we assume that the tech will keep the current intelligence level and and simply improve on the execution, that is already enough to make the mean white collar worker obsolete. Heck, I have a PhD-level education and consider a future where I am reduced to wearing AR goggles and connecting cables to where some AI decides they should go while it takes care of the software tasks far more efficiently than I ever could distinctly possible.
This is not to say that the AI bubble bursting is not also possible. I mean, investors in the late 90s were not wrong about everything -- the internet did have an enormous effect on commerce. It was more the specifics which they were wrong about, like if pets.com would ever become profitable.
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