Really fascinating update! I’m especially intrigued by Gemma 2’s use of knowledge distillation—training smaller models with larger “teacher” models seems like a smart way to scale AI efficiently. The benchmarks like CharXiv and LMSYS Chatbot Arena are crucial to see where models truly excel beyond memorization.
On a lighter note, reading about LLMs mastering reasoning reminds me of teaching my https://snake-game.io to anticipate moves—it’s a smaller scale, but the principles of prediction and strategy feel similar!
This essay makes the case that, regardless of how AI systems advance, they will probably be employed more harm than benefit if policymakers ignore the dynamics of hazardous extraction, detrimental normalization, and antagonistic self-dealing. https://speedstars-game.io
Really fascinating update! I’m especially intrigued by Gemma 2’s use of knowledge distillation—training smaller models with larger “teacher” models seems like a smart way to scale AI efficiently. The benchmarks like CharXiv and LMSYS Chatbot Arena are crucial to see where models truly excel beyond memorization.
On a lighter note, reading about LLMs mastering reasoning reminds me of teaching my https://snake-game.io to anticipate moves—it’s a smaller scale, but the principles of prediction and strategy feel similar!
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This essay makes the case that, regardless of how AI systems advance, they will probably be employed more harm than benefit if policymakers ignore the dynamics of hazardous extraction, detrimental normalization, and antagonistic self-dealing. https://speedstars-game.io