AMD Appoints Tim Ryan to Board of Directors
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汇集 AI 算力、GPU 加速器、芯片、数据中心与推理基础设施动态。
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This is a patch release on top of [v1.28.0](https://github.com/microsoft/onnxruntime/releases/tag/v1.28.0), containing support for device-free WebGPU compilation, improved compatibility with sandboxed Windows processes, and targeted graph-validation fixes. ##
This is the first release of ONNX Runtime CUDA Plugin EP, providing CUDA execution as a separately packaged plugin execution provider. These notes cover commits affecting CUDA Plugin EP core code, CMake integration, and its primary build and package pipeline.
Cloud-native platforms are becoming the foundation for AI transformation. Discover how Microsoft's Azure application platform helps organizations modernize, innovate, and operate AI-powered applications at scale. The post Microsoft named a Leader in the 2026 G
The demand for AI continues to accelerate. Workloads are getting larger, models are becoming more complex, and there is mounting pressure to deploy AI compute...
## Announcements & Breaking Changes - onnxruntime-web has announced the deprecation of WebGL and JSEP. The native WebGPU EP is the recommended path going forward. See the deprecation and migration plans for details ([#29716](https://github.com/microsoft/onnxru
This is a patch release on top of v0.27.0. - Support quantized DSpark Markov heads (#50424)
### Summary of major features and improvements * #### More GenAI coverage and framework integrations to minimize code changes * New models supported: * On CPU, GPU, and NPU: SmolLM3-3B, LFM2-1.2B, LFM2.5-1.2B * On CPU and GPU: Harrier OSS-v1-0.6B, Qwen3-8B wit
# Highlights *582 PRs from 194 contributors.* **Kimi K3 day-0 support**: A 2.8T-parameter multimodal LatentMoE (896 experts, top-16, routed in a 3584-dim latent space) with a 1M-token context, 69 KDA linear-attention layers interleaved with 24 MLA layers, and
# vLLM v0.27.0 Release Notes ## Highlights This release features 561 commits from 242 contributors (64 new)! * **Kimi K3 support** with a full stack landing in one release: core model files and kernels (#50089, #50000), Python (#50093) and Rust (#50104) fronte
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Capcom's RE ENGINE team set out to bring path tracing into two shipping titles at once, Resident Evil Requiem and PRAGMATA, each with a different visual...
Developers building 3D, design, simulation, robotics, and industrial digital twin applications need ways to bring physical AI capabilities into the tools and...
What began as discrete AI model training and human-facing chat interfaces has evolved into always-on AI factories dedicated to producing intelligence at scale....
A TensorRT engine build can take seconds to many minutes. Large strongly typed models, deep tactic search, and a cold timing cache on a brand-new GPU SKU can...
Frontier model pre-training has converged on mixture of experts (MoE), which is fundamentally changing what limits large-scale AI training. As compute per token...
NVIDIA OptiX ray tracing engine is an application framework for achieving optimal ray tracing performance on the GPU. Applications using OptiX can fail in ways...
Customization is what enables developers to take a general model and tailor it to use cases, domains, languages, and more. However, customization comes with a...
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## Highlights - **Major performance work for attention-heavy LLMs.** - FlashAttention decode kernels were fused and extended for any sequence length ([#28389](https://github.com/microsoft/onnxruntime/pull/28389)). - FlashAttention prefill shared-memory path wa
Adds the two compiler changes the Gluon Flash Attention kernels need, on top of gfx950-tutorial-v1.1. The LLVM pin is unchanged (850a2b1), so the out-of-tree LLIR-scheduler plugin does NOT need rebuilding. [Gluon] gl.warp_predicate — a per-wave masked-skip reg
# vLLM v0.26.0 Release Notes ## Highlights This release features 411 commits from 212 contributors (61 new)! * **New Inkling model family** with a full support stack: base modeling (#48799), piecewise CUDA graph support (#48822), Hopper FA4 relative attention
## Announcements & Breaking Changes - Upgraded to **ONNX 1.22.0** and protobuf 6.33.5 ([#28754](https://github.com/microsoft/onnxruntime/pull/28754), [#29606](https://github.com/microsoft/onnxruntime/pull/29606), [#28967](https://github.com/microsoft/onnxrunti
# Highlights *574 PRs from 169 contributors.* **DSpark: confidence-driven speculative decoding**: A new speculative algorithm. It drafts semi-autoregressively in blocks, then sizes each verify window from the draft's own confidence instead of a fixed draft len
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AT&T processed approximately one trillion tokens while developing OTel2.0 using Microsoft Foundry Managed Compute, open AI models, and AMD and NVIDIA GPU infrastructure. Discover how flexible model choice and scalable infrastructure are enabling production-sca
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