link? and dude where’s my exponential?
@garymarcus
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Free LLM Models: Marketing Hype vs. Quality Reality
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It’s nice gig making LLMs. You can distribute free models that suck. Hype them to the skies. Take credit for the hundreds of millions of user you’ve got. And when they make a mistake, you can blame the users for not using the paid models.
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AGI Systems Should Verify Facts to Avoid Hallucinations
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you could make that argument. or could argue that a system that bills itself as near AGI ought to do a search to check its facts. (does depend a bit on how you define hallucination, i would agree)
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Silicon Valley AGI timeline predictions revised again scrutinized
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LMAO. Last year most of Silicon Valley was predicting AGI in 2027 (which, spoiler alert, ain’t gonna happen). Now the most prominent former advocate of AGI in 2027, @DKokotajlo
, says 2029, and Groks writes it up as “AI forecasters shorten timelines for AGI”, when on net Daniel -
Honest Technical Assessment Critical for AI Timing
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Agreed; timing will make a huge difference. Which is *why* honest examination of technical strengths is so essential.
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AI Hype: Universal QA Systems Cannot Deliver on Promises
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well we can agree on the last. on the former, this stuff has been hyped to the skies as doing something it can’t (act as as universal QA system), and that’s part of the point.
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AI Marketing Hype: Missing Warnings on Universal Tools
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if you advertise your thing as easy to use and universal and don’t give users significant warnings, it’s (also) a hype issue.
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METR Study Shows Mixed Results on AI Model Capabilities
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most recent, somewhat mixed METR study below (and Claude Code may change things):
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Frozen Data Limitations in LLM Reasoning Systems
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it’s an issue of using frozen data in lieu of reasoning etc
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AI Tools May Reduce Coder Productivity Despite User Perception
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Interesting take, consistent with the surprising @METR_Evals study that showed coders using AI tools took a hit on productivity even they imagined otherwise.