Agüera y Arcas argues that symbolic AI never worked because it assumed intelligence could be reduced to airtight logical propositions and pattern regularities, when in fact no such self-sufficient propositions exist. ✦ AI generated
Blaise Agüera y Arcas · Machine Learning Street Talk · 2026-02-16 · original ↗
starts at this moment · 14:23
This is why good old fashioned AI never never panned out. And and the reason is that that you can't start out with like in math with propositions that are self-sufficient... When when your propositions are not airtight and when you're looking only at regularities and patterns, this good oldfashioned uh AI idea simply cannot work. And that's that's why we never got it to work.
verbatim transcript · starts at 14:23
14:23intelligence could be carried out by by just having a series of uh programs of of sort of strictly logical uh you know deductions or inductions. That doesn't work. This is why good old fashioned AI never never panned out. And and the reason is that that you can't start out with like in math with propositions that are self-sufficient. Even math is not self-sufficient, but let's pretend for a
14:45moment and just move from there and kind of do an algebra in order to work various things out. When when your propositions are not airtight and when you're looking only at regularities and patterns, this good oldfashioned uh AI idea simply cannot work. And that's that's why we never got it to work. Let's move now to to some of the artificial life experiments that uh that uh that I began playing with in at the
15:06end of 2023 and my team and I published in June of 2024. So just about a year ago. I think some of you uh many of you perhaps have heard of these. They're in the what is life books and I've talked about them a few times. The the basic setup here is to try and get self-replication to get you know abiogenesis the emergence of life from non-life to happen in a purely
15:27artificial life system. Uh okay so the setup is to begin with a minimal touring complete language uh I used brain [ __ ] uh because I I really liked the idea of being able to talk at a conference and say brain [ __ ] over and over and I'm fundamentally 12 years old on the inside. Um but but also because it's it's uh it it very closely models uh the
15:50touring machine. Uh you know it's it's a it's a a minimal programming language only only eight instructions that uh that looks very touring machineike and moves the head back and forth. I should say that in its original version brain [ __ ] is not embodied computation. It has basically a separate data tape and code tape and that means that it cannot make a copy of itself. So I I made a couple
16:09of modifications to brain [ __ ] that actually reduce it from eight instructions to seven in order to make it embodied. Meaning that as it works on the tape, it is able to read its own code and write and write its own code on that tape as well. There's no separate console. There's no separation between the data tape and the uh and the instruction tape. For those of you who