flash attention
An optimized implementation of transformer attention, which Manifest AI's Vidril framework can match or outperform, especially on non-standard problem shapes.
What podcasters actually say about flash attention.
8 mentions, no marketing. Save them all to a pod and ask any question.
Common Themes
Videos Mentioning flash attention
Answer.ai & AI Magic with Jeremy Howard
Latent Space
An optimized attention mechanism for Transformers, its compatibility issues with newer versions of Transformers were discussed.
Building an open AI company - with Ce and Vipul of Together AI
Latent Space
An optimization technique for attention mechanisms in transformers, open-sourced and contributing to better AI models.
Ep 18: Petaflops to the People — with George Hotz of tinycorp
Latent Space
Flash Attention is highlighted as an algorithmic trick that improves efficiency without increasing compute, similar to Hotz's approach with Tiny Grad.
⚡️ Beyond Transformers with Power Retention
Latent Space
An optimized implementation of transformer attention, which Manifest AI's Vidril framework can match or outperform, especially on non-standard problem shapes.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 5: GPUs, TPUs
Stanford Online
An optimized algorithm for computing attention mechanisms in neural networks, designed for efficiency and reduced memory usage on GPUs.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Lecture 6: Kernels, Triton, XLA
Stanford Online
Mentioned as a potential application or goal that the lecture's concepts will enable students to implement.
Stanford CS25: Transformers United V6 I The Ultra-Scale Talk: Scaling Training to Thousands of GPUs
Stanford Online
An optimized attention mechanism that inspired the online softmax approach used in Ring Attention.
Stanford CS336 Language Modeling from Scratch | Spring 2026 | Guest Lecture: Dan Fu
Stanford Online
An optimized attention mechanism mentioned as something students in the class might implement for training.