alt Hacker NewsI believe Gary Marcus is quite well known for terrible AI predictions. He's not in any way an expert in the field. Some of his predictions from 2022 [1]
> In 2029, AI will not be able to watch a movie and tell you accurately what is going on (what I called the comprehension challenge in The New Yorker, in 2014). Who are the characters? What are their conflicts and motivations? etc.
> In 2029, AI will not be able to read a novel and reliably answer questions about plot, character, conflicts, motivations, etc. Key will be going beyond the literal text, as Davis and I explain in Rebooting AI.
> In 2029, AI will not be able to work as a competent cook in an arbitrary kitchen (extending Steve Wozniak’s cup of coffee benchmark).
> In 2029, AI will not be able to reliably construct bug-free code of more than 10,000 lines from natural language specification or by interactions with a non-expert user. [Gluing together code from existing libraries doesn’t count.]
> In 2029, AI will not be able to take arbitrary proofs from the mathematical literature written in natural language and convert them into a symbolic form suitable for symbolic verification.
Many of these have already been achieved, and it's only early 2026.
[1]https://garymarcus.substack.com/p/dear-elon-musk-here-are-fi...
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> In 2029, AI will not be able to read a novel and reliably answer questions about plot, character, conflicts, motivations, etc. Key will be going beyond the literal text, as Davis and I explain in Rebooting AI.
Can AI actually do this? This looks like a nice benchmark for complex language processing, since a complete novel takes up a whole lot of context (consider War and Peace or The Count of Monte Cristo). Of course the movie variety is even more challenging since it involves especially complex multi-modal input. You could easily extend it to making sense of a whole TV series.
Besides being a cook which is more of a robotics problem all of the rest are accomplished to the point of being arguable about how reliably LLMs can perform these tasks, the arguments being between the enthusiast and naysayer camps.
The keyword being "reliably" and what your threshold is for that. And what "bug free" means. Groups of expert humans struggle to write 10k lines of "bug free" code in the absolutist sense of perfection, even code with formal proofs can have "bugs" if you consider the specification not matching the actual needs of reality.
All but the robotics one are demonstrable in 2026 at least.
I'm pretty sure it can do all of those except for the one which requires a physical body (in the kitchen) and the one that humans can't do reliably either (construct 10000 loc bug-free).
This comment or something very close always appears alongside a Gary Marcus post.
Which ones of those have been achieved in your opinion?
I think the arbitrary proofs from mathematical literature is probably the most solved one. Research into IMO problems, and Lean formalization work have been pretty successful.
Then, probably reading a novel and answering questions is the next most successful.
Reliably constructing 10k bug free lines is probably the least successful. AI tends to produce more bugs than human programmers and I have yet to meet a programmer who can reliably produce less than 1 bug per 10k lines.
Which ones are you claiming have already been achieved?
My understanding of the current scorecard is that he's still technically correct, though I agree with you there is velocity heading towards some of these things being proven wrong by 2029.
For example, in the recent thread about LLMs and solving an Erdos problem I remember reading in the comments that it was confirmed there were multiple LLMs involved as well as an expert mathematician who was deciding what context to shuttle between them and helping formulate things.
Similarly, I've not yet heard of any non-expert Software Engineers creating 10,000+ lines of non-glue code that is bug-free. Even expert Engineers at Cloud Flare failed to create a bug-free OAuth library with Claude at the helm because some things are just extremely difficult to create without bugs even with experts in the loop.