The breakthrough came on a holiday weekend. Memorial Day 2022. While most of Silicon Valley was at barbecues, Dan Fu, Tri Dao, and their colleagues were about to prove the AI establishment wrong. The conventional wisdom was settled: transformer attention was already optimized. GPU experts had squeezed every drop of performance from the hardware. There wasn't much left to gain. Then Dan, Tri, and their colleagues published FlashAttention . Andrej Karpathy, then Senior Director of AI at Tesla, tweeted about it that afternoon. Within hours it was ricocheting through AI research channels. "Honestly, we weren't expecting anybody to see it when we released it," Dan recalls. "We were prepping some blogs and code release for Tuesday morning. But then we saw Karpathy tweet about it Monday at 7 p.m. — so then we knew it was something people were paying attention to." Previous work on sparsity and low-rank methods showed theoretical speedup but only 10% real performance gains. The FlashAttention team took a different approach: understanding actual GPU memory movement and compute patterns. …