or, putting it differently, that set of weights, if you don’t have the system, and just the trained LLM, is the OUTPUT of a system as a whole that used symbolic rules as a critical component in its training process.
@garymarcus
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Science System Degradation: Policy Impact by Year-End
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we have the best science system in the world. it’s not an old car not worth repairing. well, we did, anyway. we won’t by the end of the year.
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DeepSeek R1 Innovation: Beyond LLM Architecture Apparatus
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also, the community note depends on ignoring the RL apparatus of DeepSeek, and treating R1 as the LLM only, ignoring that apparatus, but that apparatus was part of the innovation, which is why it was reported in the paper. so yes you can play definitional games if you like but
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Academic Questions OpenAI o3 Results on FrontierMath
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Noted academic @rao2z reaches basically same conclusions about OpenAI and FrontierMath that I did. The o3 result smells fishy.
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Training data transparency and synthetic data analysis
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show me the training data, including synthetic data, and do an analysis of how many of the correct answers derive fairly directly (or not) from those data, and then we will talk.
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Graduate Student Research Quality Standards in Academia
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wonder how long a grad student who produced 90-95% garbage would last?
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Altman’s Unfulfilled Promises: Media Accountability Gap
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Very Safe Prediction: Altman will continue to spin fairy tales (generally with plausibly deniability, implication without full commitment) as long as the press keeps reporting them, and as long the press keeps failing to hold him account for broken promises. We will not have x.com/AISafetyMemes/…
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OpenAI o3 presentation criticized as misleading GPT-5 hype
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In time, people will see December’s OpenAI o3 presentation for what it seems to have been: a desperate, rigged, misleading, scientifically shoddy demonstration that overhyped future products and distracted from their struggles in getting a viable system worthy of the name GPT-5.
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OpenAI’s hand in crafting industry-wide agreements
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well, it should be uniform at the very least. ideally, “none”, i agree. but OpenAI presumably had a strong hand in crafting the arrangement that was reached.
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OpenAI Scandal: Unfair Competitive Advantage in AI Training
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Scandal at OpenAI, explained with an analogy: If you studied hard for an exam, but didn’t have access to the problems and their solutions, but someone else did, would you think it is fair to compare their results and yours? That’s what OpenAI did, in their “mindblowing”