---
title: "Driving the Future of Open Source AI: An Update from PyTorch Foundation Projects – PyTorch"
url: https://daily.dev/posts/driving-the-future-of-open-source-ai-an-update-from-pytorch-foundation-projects-pytorch-nzlqvwtdu
source_url: https://pytorch.org/blog/driving-the-future-of-open-source-ai-an-update-from-pytorch-foundation-projects
type: article
source: "PyTorch"
published: 2026-07-22T14:48:34.092Z
updated: 2026-07-22T14:48:57.025Z
tags: ["deep-learning", "pytorch", "ai-inference", "vllm"]
reading_time: 7
upvotes: 0
comments: 0
language: en
---

> ## Documentation Index
> Fetch the complete documentation index at: https://daily.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# Driving the Future of Open Source AI: An Update from PyTorch Foundation Projects – PyTorch

**[PyTorch](https://daily.dev/sources/pytorch)** · 7 min read · 0 upvotes · 0 comments

## Summary

The PyTorch Foundation, now a multi-project organization hosting PyTorch, vLLM, DeepSpeed, Ray, Helion, and Safetensors, shares Q2 2025 progress across all six projects. PyTorch 2.13 ships FlexAttention on Apple Silicon (~12x faster than SDPA), a memory-saving LinearCrossEntropyLoss, and FSDP2 communication overlap. vLLM completes Model Runner V2, publishes its Q3 2026 roadmap focused on agentic workloads, and announces its first conference. DeepSpeed integrates Ulysses parallelism into Hugging Face libraries and earns a best-paper honorable mention at ASPLOS 2026. Ray adds GB200/GB300 hardware support and a new high-performance Ray Data 2.57 engine. Helion delivers cross-hardware attention kernels outperforming FlashAttention-4 and introduces LLM-guided autotuning with 10x efficiency gains. Safetensors adds GIL-free serialization, Python 3.14 support, and MPS fast-load paths.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://pytorch.org/blog/driving-the-future-of-open-source-ai-an-update-from-pytorch-foundation-projects>

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---

Tags: [#deep-learning](https://daily.dev/tags/deep-learning), [#pytorch](https://daily.dev/tags/pytorch), [#ai-inference](https://daily.dev/tags/ai-inference), [#vllm](https://daily.dev/tags/vllm)

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