Researchers introduced CUDA-Harness, a framework for generating and optimizing CUDA kernels directly from natural language (Text2CUDA), addressing the expertise barrier in high-performance kernel deve…
Model weights are the adjustable numerical parameters inside a machine learning model that are fine-tuned during training to improve performance, analogous to ingredient amounts in a recipe. Downloadi…
A new technical blog series by an unnamed author provides a roofline-to-reality performance analysis of DeepSeek-V3, a mixture-of-experts transformer model recently added to MLPerf 6.0 as a large-scal…
Waymo, an autonomous driving technology company, is hiring a Sr Staff Tech Lead, Machine Learning Engineer for its Perception team in Mountain View or San Francisco, California, with a salary range of…
A developer benchmarked three Gemma 4 deployments on a single AWS T4G GPU for under $3, comparing vLLM, JAX, and PyTorch runtimes. The project built a common harness to measure decode throughput, reve…
PyTorch's `.view()` method fails on non-contiguous tensors created by `.transpose()`, throwing a RuntimeError because the underlying memory layout has scrambled strides. The fix is calling `.contiguou…
A developer outlines a practical project roadmap for learning generative AI and large language models, progressing from basic LLM usage to retrieval-augmented generation (RAG) and fine-tuning with LoR…
RMSNorm, a normalization technique proposed by Zhang and Sennrich in 2019, rescales neural network activations by dividing by the root mean square of each row, skipping the mean-centering step of Laye…
OpenMPTCProuter v0.64.1 introduces MQVPN, a new multipath QUIC-based VPN set as the default, along with new MPTCP schedulers (Weight, Weighted Round-Robin, DSCP), VXLAN tunnel support, enhanced monito…
Reddit's r/MachineLearning leads the list of the seven best AI discussion groups, with over 3.5 million subscribers as of 2024, according to a new guide. The guide also highlights Hugging Face Communi…
AOTInductor, a PyTorch compiler backend, supports in-place input mutations in optimized inference engines, contrary to the assumption that it relies solely on functionalization. The key is to explicit…
Researchers introduced QGPINNs, a physics-informed neural network framework built in PyTorch for solving nonlocal differential equations on quantum graphs, validated on benchmarks including the IEEE 1…
A tutorial by an unnamed author demonstrates that a bigram model with a single embedding table can recover true transition probabilities from 100,000 generated samples, achieving learned probabilities…
A developer warns that AI model security training often overlooks the risk of malicious PyTorch checkpoints, which are programs executed via pickle deserialization, citing CVE-2025-24357 and CVE-2024-…
Sebastian Raschka published a video and accompanying note explaining how to set up the Python and PyTorch environment for building a reasoning model from scratch, using the `uv` package manager. The v…
A developer explores Triton, a Python-based language and compiler for writing GPU kernels, to understand low-level GPU programming and performance. The developer explains how Triton abstracts GPU thre…
Researchers from the Technical University of Munich introduced GaussianGPT, a transformer-based model that generates 3D scenes autoregressively via next-token prediction on Gaussian splatting tokens, …
Fireworks AI, a Series D company valued at $17.5 billion and founded by the team behind PyTorch, is hiring a Member of Technical Staff for its EMEA field team in London, with the role focused on build…
Developer soasme released micromlp, a single-file Python neural network with no dependencies that predicts California housing prices using a 2-layer MLP and from-scratch automatic differentiation, ins…
Meta Platforms Inc. is racing to regain frontier AI status with its forthcoming 'Watermelon' model, but its history reveals a complicated path marked by early insight and missed acquisitions. Mark Zuc…