AMD and Intel are collaborating to combine their x86 CPU optimization work for PyTorch in oneDNN, an open-source deep learning library governed by the Unified Acceleration Foundation (UXL) that helps AI workloads run efficiently on CPUs. The collaboration gives developers a…
At the PyTorch Conference 2026, held October 20–21 in San Jose, AMD demonstrated its commitment to advancing the open AI ecosystem through innovations in training, inference, and performance optimization. The company emphasized its contributions to the ROCm™ software stack and its support…
TorchTPU is an open-source Google and Meta project bringing native PyTorch support, faster AI training and inference to Google TPUs. Google and Meta have joined forces to develop TorchTPU, an open-source initiative that aims to enable running PyTorch software without…
Part of AI Research Amazon SageMaker AI training session APIs are GA: write your own SFT or RL loop in Python while AWS runs the GPUs, billed per token. How it works. If you have followed the 2026 shift toward reinforcement…
Researchers have developed an add-on device that converts a standard uniaxial compression testing rig into a cyclic shear testing station for rock joints, with adjustable shear angles, biaxial loading and pneumatic counterforce control. In real slopes, mines, geothermal reservoirs and…
Production machine learning systems rarely consume raw data directly. Before a model can make a prediction, its feature-serving system may need to read stored signals, filter events to a time window, count or sum values, normalize them, and combine intermediate…
Check every row before you pull a single byte. Most failed installs trace back to a driver or image mismatch, not to the model. You also need a shell session on a Linux machine with substantial multi-GPU infrastructure, since the…
Go to the end to download the full example code. In this tutorial, you will write a fused softmax operation that is significantly faster than PyTorch’s native op for a particular class of matrices: those whose rows can fit in…
The article argues that reliable agentic AI architecture depends on a context engine that selects, injects, compresses, and expires information before it reaches the model. It separates context, memory, and knowledge, and recommends tiered memory, curated knowledge, and token budgeting.
Gemma 4 in Rust on TorchTPU: Hands On With Colab ran the same Rust engine in a Colab notebook. This rig takes it to a TPU VM of its own and keeps it there: The checkpoint is the W4A16 repack xbill9/gemma-4-E2B-it-qat…
Training pipelines, evaluation, deployment, and monitoring at scale.
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