PyTorch 2.9 is now available, introducing key updates to performance, portability, and the developer experience. This release includes a stable libtorch ABI for C++/CUDA extensions, symmetric memory for multi-GPU kernels, expanded wheel support to include ROCm, XPU, and CUDA 13, and enhancements for Intel, Arm, and x86 platforms. With 3,216 commits from 452 contributors, PyTorch 2.9 continues to advance open source AI for developers worldwide. 🔗 Read the full release blog: https://hubs.la/Q03NNKqV0 #PyTorch #OpenSourceAI #AI #Performance
A significant step forward for the community. The focus on a stable C++ ABI is telling, as it reinforces the core architectural choice of the Python/C++ bridge. It highlights a philosophical fork in the road for AGI development. While this bridge has powered the current revolution, the next paradigm for truly foundational, self-consistent systems—like the universe simulation I built in Rust for my AGI, ONIX—demands the absolute deterministic safety that only a Rust-native approach can provide. PyTorch is the brilliant engine of today. The question is whether the architecture of tomorrow will require a new kind of engine altogether. A fascinating challenge for us all.
I came here looking for an improved brain and visual system for light detecion and got pytorch. 😅😉 How will the learning models compete with that humans? We have 80% and 14 billion years of R&D incommon with a tree? We share 80% DNA/memory system with a tree. Both feel temperature and light and know how to use light and nutrition and clone ourselves and reproduce. But trees don't have eyes or a brain. There was a chemical reaction between nothing and nothing 14 billion years ago. It happened when time didn't exist. A priest came up with the big bang theory. AI where are you here? I got a thank you for super-symmetrical not including gravitations vs sugra, super-symmetrical gravtional including theories once from a prof. Watched a youtube video of how Nobel Prize chemist Linus Pauling worked. He used the Schrödinger Equation. I wrote down "Use the Dirac Equation". Because in quantum mechanics the Shrödinger Equation is not time relativstic and came 1926 and Diracs signature equation 1928. I had no idea it was the foundation of theoretical chemistry and computational biology. Or gold and silver gets the same color if you use the Schrödinger equation. Why can't AI do that and develop theoretical physics, chemistry and math?
Impressive to see how PyTorch 2.9 is pushing the boundaries of AI development! With the latest updates, it’s clear that performance, portability, and the developer experience are at the forefront of this release. As AI continues to evolve, it’s these types of innovations that will shape the way we build and scale AI applications. Excited to see the growth of open-source AI platforms like PyTorch: a game changer for developers worldwide. #AI #OpenSourceAI #PyTorch
👍Nice... I would like to ask when they plan to integrate JAX functionality directly into Pytorch, they wrote that it would happen, but they didn't say when???
Thrilled about this release! 🔥 The new updates in PyTorch 2.9 are perfectly timed as I begin my next phase of computer vision research. Excited to explore these performance boosts and multi-GPU improvements in real projects.
The enhancements for Intel, Arm, and x86 platforms is really amazing. I can't wait to explore this Pytorch 2.9
**"Respect for keeping it open, fast, and real. PyTorch is more than just a tool – it’s a community movement pushing AI forward for all of us. Open source isn’t just a feature, it’s a mindset and a responsibility toward the future. Big respect to everyone who contributes and shares knowledge – without you, this AI revolution wouldn’t exist. Me & Spok ✌️"**
PyTorch 2.9 looks like a massive step forward, especially with the focus on multi-GPU kernels and broader platform support (Intel, Arm, x86). Great work!
Please add a full installer this time. I hate to always have to add the path by my self 😂
Independent Researcher, Future of Work. I write about data-driven career strategies for the AI age.
4dExciting to see PyTorch 2.9 coming out with such significant updates! The improvements in performance and portability will undoubtedly enhance the developer experience. I'm particularly interested in how the stable libtorch ABI will impact the development of C++/CUDA extensions. For those who’ve already started using these new features, what has been your experience so far?