A developer known as No Saved DATA introduced Neve, a new programming language designed to unify high-level Python-like syntax with low-level efficiency for deep learning. The language features LLVM J…
Sasha Rush's notebook introduces differentiable rasterization, a method to make the conversion of vector graphics to pixels differentiable for gradient-based optimization in deep learning frameworks l…
A developer released Jixp, a Lisp DSL for describing Jax neural nets, as a side project for learning Jax. The compiler reads Racket-style DSL and outputs Python, enabling simple model specification wi…
A blog post derives the backward pass of attention mechanisms step by step, using a concrete example to illustrate gradient computation for Q, K, and V matrices. The derivation builds on FlashAttentio…