<!-- SC_OFF --><div class="md"><p>Hey everyone,</p> <p>I’ve been working on the idea of taking Scientific AI out of research notebooks and making it accessible as a useful
<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1t2zy4h/torchnvenccompress_gpu_nvenc_silicon_as_a_pcie/"> <img alt="torch-nvenc-compress: GPU NVENC
<h1> <img alt="Generative Simulation Benchmarking for Wildfire Evacuation Logistics Networks in Carbon-Negative Infrastructure" height="800"
<!-- SC_OFF --><div class="md"><p>doing infrastructure evaluation for inference workloads and running into the same problem everywhere: every platform publishes p50 cold start
<!-- SC_OFF --><div class="md"><p>everyone's focused on the benchmarks (14 state of the art evals, beats mythos on terminal-bench, etc) but i think the actual story of 5.5 is what
<!-- SC_OFF --><div class="md"><p>I am learning physics informed neural networks. Currently, I am solving a simple second ODE (damped harmonic oscillator). The equation is
<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s5g2zh/cohere_transcribe_webgpu_stateoftheart/"> <img alt="Cohere Transcribe WebGPU: state-of-the-art
<table> <tr><td> <a href="https://www.reddit.com/r/MachineLearning/comments/1tmebju/thermocompute_constant_time_inference_p/"> <img alt="Thermocompute constant time inference [P]"
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