I write a quarterly report tracking what AI researchers actually disagree on. This quarter's list got dark, what you all think?

Reddit r/ArtificialInteligence News

Summary

A quarterly report catalogs documented disagreements among leading AI researchers, including Karpathy's shift from independent to lab work, Sutskever's scaling claims vs. SSI's silence, and LeCun's bet against LLMs, highlighting unresolved debates about scaling, AGI timelines, and enterprise AI ROI.

https://preview.redd.it/u4mtz20wqfch1.png?width=1528&format=png&auto=webp&s=58bc48af1c0d6a24e30f0698f26bf9bb4453ecd5 Been tracking this for a quarter now, basically collecting every place where two people who actually build frontier AI are on record contradicting each other. Not takes, actual documented disagreements. A few that stood out this time: Karpathy spent 2025 saying the future was staying independent and directing swarms of agents solo. In May he joined Anthropic's pretraining team. He'd already said out loud that staying outside a lab means your judgment drifts because the models are opaque. So even the guy most convinced independence was the future decided he needed to be inside a lab to keep his judgment sharp. Sutskever said the scaling era is over, ideas are the bottleneck now, not compute. His own company, SSI, has raised $6B at a $32B valuation, has about 20 people, and has shipped nothing and published nothing in two years. Which is either exactly what betting on ideas over scale looks like before it pays off, or it's just two years of silence. Genuinely can't tell which from outside. LeCun left Meta, called LLMs a dead end, raised over a billion dollars to prove it. Turing Award winner staking his whole legacy on the opposite bet from everyone still scaling LLMs. Nobody knows who's right, including him. MIT found 95% of enterprise AI pilots produce zero measurable ROI. Still true a year later. The ones that work aren't the ones with the best model, they're the ones wired into an actual back-office workflow through a real vendor partnership. Boring wins, every time. There's a bunch more (AGI timeline disagreements between Hinton/Hassabis/Amodei/LeCun, the Jevons paradox thing where cheaper AI makes bills go up not down, the jaggedness idea about why models are great at code and bad at everything else). Wrote the whole thing up here if anyone wants the receipts and sources. [comments] But genuinely curious what people here think is the biggest one of these. Which of these disagreements do you think actually resolves in the next year, and which one is still unsettled in 2030?
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