⚡ Magnific made it to the top of the top of "Tiny teams hall of fame" 😍
We are now at $12M ARR + the ARR that Magnific is doing inside Freepik (don't know the exact data of that yet).
Thank you all!
@dieworkwear Derek do you recommend any specific brands for neckerchiefs? As a Spaniard the easy option for me was Zara. It has some supercheap options to play around a little bit with the basic bandanas that you mentioned but I want to level up my game. Help please!! 🫡🫡
We’re releasing Humanity’s Last Exam, a dataset with 3,000 questions developed with hundreds of subject matter experts to capture the human frontier of knowledge and reasoning.
State-of-the-art AIs get <10% accuracy and are highly overconfident.
@ai_risk@scaleai
[1/7] New paper alert! Heard about the BitNet hype or that Llama-3 is harder to quantize? Our new work studies both! We formulate scaling laws for precision, across both pre and post-training https://t.co/QLmNOV39Wk. TLDR;
- Models become harder to post-train quantize as they are overtrained on lots of data, so that eventually more pretraining data can be actively harmful if quantizing post-training!
- The effects of putting weights, activations, or attention in varying precisions during pretraining are consistent and predictable, and fitting a scaling law suggests that pretraining at high (BF16) and next-generation (FP4) precisions may both be suboptimal design choices!
Joint work with @ZackAnkner@bfspector@blake__bordelon@Muennighoff@mansiege@CPehlevan@HazyResearch@AdtRaghunathan.