chepetronix
@im_chepetronix
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Joined May 2023
RT @fchollet: Thanks to all contributors who worked on this release!. Full release notes:
github.com
New: OpenVINO backend OpenVINO is now available as an infererence-only Keras backend. You can start using it by setting the backend field to "openvino" in your keras.json config file. Ope...
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RT @fchollet: This is exactly what "memorization" means, to be clear. They memorize procedures (in the form of vector functions) that match….
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RT @fchollet: Some personal news -- I'm leaving Google to go start a new company with a friend. More to be announced soon!. I will stay dee….
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RT @ylecun: Stuff you grew up with is beautiful and the subject of nostalgia. Stuff that appeared while you were an adult is the work of th….
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RT @ylecun: Fei-Fei agrees with the overwhelming majority of AI scientists: SB1047 won't solve anything and will harm AI R&D in academia, l….
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RT @GregKamradt: Official comment from @mikeknoop on SB-1047. Important to keep open source open. "If unchanged, it will create an environm….
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RT @fchollet: Holding open model developers responsible for all fine-tuned models downstream of their own makes no sense -- it's as if open….
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RT @mcuban: I love you too Elon. But not as much as I love me. And probably not as much as you love you. Sorry.
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RT @ylecun: Excellent blog post from Turing Post on JEPA (Joint Embedding Predictive Architecture), my favorite meta-architecture for Self-….
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RT @fchollet: Lots of big announcements today! Make sure to check out this intro to what you can do with Gemma 2:. .
developers.googleblog.com
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RT @karpathy: Actually, really liked the Apple Intelligence announcement. It must be a very exciting time at Apple as they layer AI on top….
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RT @fchollet: I'm partnering with @mikeknoop to launch ARC Prize: a $1,000,000 competition to create an AI that can adapt to novelty and so….
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RT @fchollet: There's a big difference between solving a problem from first principles vs applying a solution template you previously memor….
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RT @ylecun: Four capabilities necessary for human-level intelligence (even dog-level intelligence) that Auto-Regressive LLM do not exhibit.
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