Gary Marcus

terence tao, shitposting🤣

Complementary remarks from Gary Marcus and Terence Tao on OpenAI’s giant math drop Making sense of a new regime in math https://garymarcus.substack.com/p/complementary-remarks-from-gary-marcus?r=8tdk6&utm_campaign=post-expanded-share&utm_medium=web

holy shit

We need a name for the kind of people that conflate 2022 pure LLMs that were in fact a tiny bit like stochastic parrots (not my phrase, and not one I ever endorsed) with 2026 systems that couple those LLMs together with symbolic harnesses, code interpreters, and symbolic verification, typically to make a slippery rhetorical point. Aside from being unfair to people who made a metaphor that applied (to some degree) to the technology of that time, it disrespects the innovations that were subsequently made and disrespects the critical contributions that neurosymbolic AI made to progress. What I hate most about this site is that so many people talk about AI yet few take any time to understand how the different underlying technologies work. Most prefer to make cheap rhetorical points instead. Which is exactly why we are in the mess we are in.

The real news here isn’t the result; it’s what we were not told. 1. AI once tried to be a science. Now we get stuff like the completely vague report from OpenAI below, and a lot of ignorant questions from people who don’t know how to think critically. “Same procedure”? “using an unreleased model”? This would never pass peer review. We don’t know what the procedure was. We know nothing about the architecture (e.g., were proofs generated in one shot, and then verified by Lean? was there an iterative process?). We know nothing about the failure rate. We know nothing about the training/post training/data agumentation. 2. As a result we have zero idea of how generalizable the result is outside math. 3. A lot of X has been reduced to an ignorant cheering section that applauds without knowing what it is applauding or what it might mean — without ever asking basic scientific questions. The new system could be a legitimate step towards AGI or just a clever leveraging of Lean and synthetic data in a verifiable domain with no generality whatsoever; from this report we can tell almost nothing.

“Use of AI tools, when done responsibly, can support not just the initial generation of a solution, but all of the valuable followup activities that traditionally flow out of that solution. But at the current time, the opposite is often occurring.” - Terence Tao

i honestly don’t understand how technophilia turned into this condescending and scientifically ignorant cult. is the dynamics of social media? it is about money? it’s truly sad, whatever it is. tech should be a good thing, not what it’s become. and above all else it should cherish science and not run roughshod over it.

what’s the best argument against this?

an actually intelligent question! i give my answer below it.

Photos can’t fully do justice to majesty of the translucent marble of The Taj Mahal.

the only tweet i read today that is humane.

i don’t know whether this is a joke or serious but the whole challenge with generative AI is that it literally cannot be trusted to follow “simple, generalizable instructions”. the inability of most people to grasp this is going to bite society in the ass.