A lot of receipts, going back to 1989 are here, for those interested in facts: https://
open.substack.com/pub/garymarcus
/p/the-false-glorification-of-yann-lecun?utm_campaign=post-expanded-share&utm_medium=web
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@garymarcus
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Gary Marcus Documents Yann LeCun AI Claims Since 1989
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Gary Marcus Challenges Yann LeCun Analysis With Receipts
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your analysis bullshit, and i have brought endless receipts, such as the ones here https://
open.substack.com/pub/garymarcus
/p/the-false-glorification-of-yann-lecun?utm_campaign=post-expanded-share&utm_medium=web
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LeCun Accused of Repeatedly Appropriating Others’ AI Research
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Over and over and over LeCun borrows other people’s ideas and makes them sound like his own. It’s astonishing that the media never investigates, when the pattern has been so consistent for decades.
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Future AGI Development and Platform Feature Limitations
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*here. in some decade we will be able to edit replies. Maybe AGI will come first.
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Humans Still Excel at 3D Understanding and Autonomous Driving
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depends on what information. humans are still better at comprehending the three-dimensional world, and much better at driving on unfamiliar roads, etc.
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The AGI Hype Cycle: Annual Predictions from Tech Giants
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2025 was all about how OpenAI was supposedly about to achieve AGI. 2026 is all about how Anthropic is supposedly about to achieve AGI. 2027 will be all about how Google is supposedly about to achieve AGI. Rinse, lather, repeat.
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AI Systems Still Struggling With Basic Visual Tasks
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amazing. i was giving examples like this for DALL-E three years ago. systems are still struggling with some basics.
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AGI Definition Debate: Current AI Systems Fall Short
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I don’t actually think there is that much truth here, @jason
. We certainly have not reached AGI by any of the traditional definitions. (See agidefinition.agi w @hendrycks @Yoshua_Bengio and myself and many others.) [Current AI systems still have huge problems with visual -
LLMs Spreading Misinformation: New Challenge Beyond Hallucinations
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At first, in the early 2020s, I worried that LLMs were often confidently wrong, calling them “fluent spouters of bullshit”. (And I was right; they have been and continue to be.). But now we have a new problem which is that *people* who *learn* from LLMs are also often
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Frontier Models Vision Capabilities: Benchmarks Gaming Problem
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Frontier models can’t see, and if you think they can, you’ve probably been fooled by benchmarks that can totally be gamed. In the very short essay linked below I discuss a stunning new finding from Stanford that shows just how serious the problem is. And why this means a lot