Thread

1. edot · 1791067681 · focus · HN ↗

   Absolutely based. Finally someone of stature in the industry calling this whole fear overblown. Bill Gates sounded like a nontechnical goofball in his Ezra Klein interview where he basically just screamed that the Terminator is real.

   There are lots of real worries (government use to suppress the people with minimal manpower or popular support, brainrot and fake news, unemployment due to the belief that LLMs can replace people, education collapse, etc.) we should instead be looking at. This whole rogue AI shtick is tiresome.

   1. reasonableklout · 1791077807 · focus · HN ↗

      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]: <a href="https:&#x2F;&#x2F;www.reddit.com&#x2F;r&#x2F;OpenAI&#x2F;comments&#x2F;1d5ns1z&#x2F;yann_lecun_confidently_predicted_that_llms_will&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.reddit.com&#x2F;r&#x2F;OpenAI&#x2F;comments&#x2F;1d5ns1z&#x2F;yann_lecun_...

      [2]: safe.ai&#x2F;statement-on-ai-risk

      1. oxag3n · 1791083471 · focus · HN ↗

         [1] is not a valid proof LeCun was wrong, LLMs still can&#x27;t do spacial reasoning when it can&#x27;t be derived from the training data. He didn&#x27;t argue that GPT 5000 won&#x27;t be able to describe something with words.

         1. brainwad · 1791115925 · focus · HN ↗

            This really doesn&#x27;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.

            1. mym1990 · 1791127183 · focus · HN ↗

               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”.

               1. jeremyjh · 1791132181 · focus · HN ↗

                  Why does CoT significantly improve their performance? Also, most of what they are applying they learned in post-training by solving similar problems themselves. This isn&#x27;t about regurgitating pre-trained knowledged.

                  1. mym1990 · 1791157966 · focus · HN ↗

                     I have not seen the research on CoT and how it impacts spatial reasoning and outcomes, so I can’t comment on that part. I do see continuously that in almost every example of non-trivial image generation and 3d modeling, there are quirks that point to the fact that the model does not understand relationships within the space based on physics.

                     CoT seems to work really well for text based generation but once you’re past that and into physics models and detailed relationship mapping, it may work better but it’s not enough to make me believe it’s “reasoning” in a way that humans do.

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