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Why does everyone use Grafana if TensorBoard exists

Claude 3.7 Sonnet can play Pokémon Red? Interesting. But *playing* isn't *winning*. Anthropic, let's quantify "play." I propose a rigorous benchmark: Anthropic's Claude vs. nunu.ai's agent. Head-to-head, *Pokémon Red/Blue* (original, no save states). One month. Then, a

Don't underestimate this change! Simply swapping LayerNorm with DyT (tanh-based) maintains AdamW convergence levels. Why is this big news? Second-order optimizers perform best on normalization-free architectures - which is precisely what DyT enables x.com/liuzhuang1234/…

Not all models excel at everything - specialized strengths matter. New AlgoLens benchmark data: • For creative writing: Mistral-7B delivers the best quality-to-cost ratio • For scientific texts: Phi-4 and Qwen-Turbo The data speaks for itself: x.com/TheXeophon/sta…

MCBench may be the first benchmark to test the emergent ability of internal vision-language alignment in the LM's world model. Under that lens, it makes sense that Claude and Gemini are currently #1, ahead of even Qwen-Max and QwQ: While Qwen has strong visual capacities, such

"H200 performance [measured on H100 node]" "1.67x speedup of B200 vs H200* [after going from fp8 to fp4]" *"H100" x.com/NVIDIAAIDev/st…

Don't blame SOAP when HeavyBall was broken. v1.6.3 fixes our convergence regression that's been killing your training runs. Second-order optimization should be your default - now it can be

HeavyBall 2 pre-release is out Accelerate your einsums, SOAP and PSGD with `heavyball.utils.set_torch(einsum_strategy='heavyball')`

Our "Physical Atari" demonstrates: simulation-trained agents fail in the real world Instead, our robot learns in real-time, using its own real-world experience, outperforming the state of the art Check out the annotated image and John's slides for more x.com/ID_AA_Carmack/…