flerovium114

3 ms·

1. 1.▲
   by flerovium114 1mo ago

   Are LLMs doing drug discovery? To my knowledge, that’s all classic “machine learning”
2. 2.▲
   by flerovium114 3mo ago

   The idea of "pythonizing" resource-constrained environments like embedded seems feasible to me, and even a good idea if executed well (e.g., numpy, torch, jax, etc.), but it does have me cackling imagining the first encounters of
3. 3.▲
   by flerovium114 4mo ago

   In what setting are you mixing LaTeX and C code?
4. 4.▲
   by flerovium114 7mo ago

   pizza
5. 5.▲
   by flerovium114 1y ago

   Have you tried using Enzyme ( https://enzyme.mit.edu/ )? It operates on the LLVM IR, so it's available in any language that breaks down into LLVM (e.g., Julia, where I've used it for surface gradients) and it produc
6. 6.▲
   by flerovium114 1y ago

   Randomized numerical linear algebra has proven very useful as well. It allows you to use a black-box function implementing matrix-vector multiplication (MVM) to compute standard decompositions like SVD, QR, etc. Very useful when MVM is O(N