[synctext]

Eurisko is an expert system in LISP from 1983. right? In 2025 this formal logic is replace with stochastic LLM magic. interesting evolution.

[TeMPOraL]

Symbolic processing was obviously a bad approach to building a thinking machine. Well, obvious now, 40 years ago probably not as much, but there were strong hints back then, too.

"AI agent" roughly just means invoking the system repeatedly in a while loop, and giving the system a degree of control when to stop the loop. That's not a particularly novel or breakthrough idea, so similarities are not surprising.

[ryukafalz]

I'm not convinced that symbolic processing doesn't still have a place in AI though. My feeling about language models is that, while they can be eerily good at solving problems, they're still not as capable of maintaining logical consistency as a symbolic program would be.

Sure, we obviously weren't going to get to this point with only symbolic processing, but it doesn't have to be either/or. I think combining neural nets with symbolic approaches could lead to some interesting results (and indeed I see some people are trying this, e.g. https://arxiv.org/abs/2409.11589)

[thom]

When “invoking” becomes “evolving” I think that remains very fertile ground.

[thom]

What’s interesting to me is the rise of agentic approaches which are effectively “build a plethora of tools and heuristics” with an outer loop that combines, mutates and assigns values to these components. Where before that process was more rigid, we now have access to much more fluid intelligence but the structure feels similar - let the AI prod at the world and make experiments, then look at what worked and think of some plausible enhancements. At a certain point you’re enhancing the code that enhances the enhancer and all bets are off.