Comment by reasonableklout
21 hours ago
LeCun has been consistently wrong about LLMs though, claiming that they were a dead end and that they'd never be able to do spatial reasoning, which was disproved a year later with GPT-4 [1]. He is also opposed by his fellow Turing laureates Geoffrey Hinton and Yoshua Bengio, who both signed the CAIS statement on AI extinction risk [2].
[1]: https://www.reddit.com/r/OpenAI/comments/1d5ns1z/yann_lecun_...
[2]: safe.ai/statement-on-ai-risk
[1] is not a valid proof LeCun was wrong, LLMs still can't do spacial reasoning when it can't be derived from the training data. He didn't argue that GPT 5000 won't be able to describe something with words.
This really doesn't match my experience. I can ask an LLM to modify engineering plans using vague natural language prompts and it will find the right place in the plan from the description and then make appropriate modifications, which necessarily requires doing spacial reasoning.
Or it’s just taking common examples from training and applying those copied heuristics to your problem? Doesn’t mean it’s actually reasoning about the space and how to solve the problem. It’s the equivalent of a student writing an answer they saw somewhere else without understanding “why”.
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I think the point here is that LeCun was arguing that training on pure text would not grant spatial understanding. I believe most models are trained on spatial data as well, so you are both right.
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I've seen recent AIs make detailed and technically impressive 3D models. You might argue "they're not doing spatial reasoning, they're making measurements with code and doing math to configure relative positions". Fine, but at a certain point that becomes functionally indistinguishable from spatial reasoning.
I don't know - real-world tests leave me unconvinced: https://youtu.be/ENWVpqtOdRI?t=867
> when it can't be derived from the training data
This sounds like a goalpost on wheels. Can you define clearly where your stake in the ground is?
we have benchmarks proving it can do spatial reasoning.
...poorly? https://youtu.be/ENWVpqtOdRI?t=867
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Aaah, the old benchmarks maxxing argument, having precise and clear definition of what "spatial reasoning" is, what, and most importantly WHY, the benchmarks of choice are would settle this debate, otherweise let's not delve into it.
Why chatgpt is still struggling very hard with photo editing and proportions though? It can't modify anything in a picture without messing the 3d space.
Isn't that a lack of spacial reasoning?
Almost everyone who knows what they are talking about is saying that LLMs are a dead end.