Ben Goertzel - Do LLMs Really Reason?

Can current AI really reason - or are large language models just clever parrots, skipping the "understanding" step humans rely on?

In this interview, Ben Goertzel (founder of SingularityNET and OpenCog) digs into one of the most fascinating debates in AI today: he argues that there is a big difference between appearing to reason and actually building abstract representations required for reasoning. We talk about Google Gemini’s gold medal at the International Math Olympiad, the paper The Illusion of Thinking, and whether LLMs can ever reach true reasoning ability.

Also we discuss whether reasoning is required for morality, whether AI will ever win a Moral Olympiad, and if it does, will this be a reliable signal that the AI is actually moral.

Finally we discuss whether AI may converge on new kinds of reasoning and logic, and also whether the ontology of the universe determines the kind of logic that arises within it.

Along the way we explore:

Why humans learn strategy differently from Deep Blue or AlphaZero

The link between reasoning, creativity, and Maggie Boden’s ideas on AI imagination

What’s missing in current AI when it comes to abstract representation

Searle’s Chinese Room and whether LLMs “understand” anything

Sam Altman’s redefinition of AGI

And whether AI could one day win a “Moral Olympiad” — or if ethical reasoning requires grounding in empathy

Quotes from the interview:
"The way Deep Blue or AlphaZero are playing chess, they are not learning general strategic principles, they are learning highly particular patterns about that particular game. We are not as good at chess or Go as they are, but we are extracting more generalisable knowledge when we learn to play chess or than these other algorithms are.

"Could you come up with a different go algorithm that combined the best of AlphaGo with the best of the human mind, and abstracted general strategic principles as well as a humongous library of very specific go playing patterns - quite possibly you could"

"A human cannot very easily turn knowledge into a bunch of text depicting an abstract representation of that knowledge without actually in it's mind constructing the abstract representation of that knowledge, right? An LLM can go straight from that abstract representation of knowledge to some text depicting an abstract representation of that knowledge without ever having an inside it's ram state the [actual] abstract representation of that knowledge - because it's learning from a set of ordered pairs.. so it's making a leap from the [abstract representation of the] knowledge to the textual depiction of the abstract representation, right?"

0:00 Intro
1:02 Grounding the idea of reasoning
6:44 Paper: 'The Illusion of Thinking' / Google Gemini wins International Math Olympiad - can LLMs do 'actual' reasoning?
19:52 Will LLMs ever get to 100% reasoning ability? What's missing is creativity
21:07 Humans, Deep Blue and AlphaZero all learn differently - humans learn from general strategic principles
24:55 Maggie Boden & AI Creativity
25:59 What else is required for AI to achieve true creativity?
32:56 Is Gemini (or LLMs) capable of abstract representation?
36:32 Searl's Chinese Room - and the pipeline from knowledge to the textual depiction of the abstract representation of the know
41:22 Sam Altman's redefinition of AGI
42:30 Olympiad level mathematics conquered - is common sense reasoning next?
43:17 Will AI win a Moral Olympiad?
44:38 Is it enough for AI predict human ethical judgements without understanding of what ethics is or grounding in empathy?
48:21 The danger of AI not understanding ethics
50:59 AI grounding moral reasoning (in empathy)
55:25 Are Google / Deepmind thinking about reasoning in the right way? Is the main thrust of their AI approach likely to reach AGI any time soon?
57:57 New types of reasoning?
59:56 Does physical ontology determine what reasoning is sound?

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Adam Ford
Science, Technology & the Future - #SciFuture - http://scifuture.org