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How so? His predictions were accurate so far
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No they were not. These were his 5 predictions in 2022:

""" 1. By 2029, AI will still be unable to watch a movie and accurately explain the characters, events, conflicts, and motivations.

2. By 2029, AI will still be unable to read a novel and reliably answer questions about its plot, characters, conflicts, and motivations beyond what is stated literally.

3. By 2029, AI will still be unable to work as a competent cook in an unfamiliar kitchen.

4. By 2029, AI will still be unable to reliably create more than 10,000 lines of bug-free code from natural-language instructions or interaction with a nontechnical user, excluding simple assembly of existing libraries.

5. By 2029, AI will still be unable to convert arbitrary mathematical proofs written in natural language into symbolic form suitable for formal verification. """

There's still 3 years to go and he's already wrong on 4 out of 5.

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Well I don't typically side with GM, but playing devil's advocate:

1. still not wrong? Unless it's just feeding the audio or screenplay I don't think you can feed AI a full movie in a single context window yet?

2. Not sure, but can you prove this wrong? Can you feed a full, unseen new book and get that kind of answer?

3. Not wrong.

4. I think he'd probably pull you up on 'bug free' - I don't think that frontier models can reliably write 10k LOC without _any_ bugs typically (not that humans can do this either).

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4. I think they can, especially if the problem statement is well-specified and, importantly, autonomously testable. Of course, specifying a problem that meets these requirements is non-trivial, but the claim requests _a_ counterexample :P
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The wording was 'reliably' though? I could just be splitting hairs on that one though to be honest.
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1 is wrong. If I tell Codex + GPT-5.6 to do it now, it will figure out how to do it. If it would need to extract audio and run a speech model on it, it will find one, set it up, and run without my help.
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I'm not buying this. GM clearly was trying to set a benchmark for video comprehension, not tool usage. Video comprehension is required for many 'AGI tasks', especially robotics to work in real time.

An LLM could theoretically try to earn some money and pay a human to do all 5 tasks but it's clearly not the spirit of the challenge.

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> There's still 3 years to go and he's already wrong on 4 out of 5.

Have these been tested or are you just guessing?

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Do LLMs generate deterministic or trustworthy answers?
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It can be annoying when someone you disagree with is frequently right!
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