January 24, 2025
How Intel Uses PyTorch to Empower Generative AI through Intel Arc GPUs
Intel has long been at the forefront of technological innovation, and its recent venture into Generative AI (GenAI) solutions is no exception. With the rise of AI-powered gaming experiences, Intel sought to deliver an accessible and intuitive GenAI inferencing solution tailored for AI PCs powered by Intel’s latest GPUs. By leveraging PyTorch as the backbone for development efforts, Intel successfully launched AI Playground, an open source application that showcases advanced GenAI workloads.
January 21, 2025
Accelerating LLM Inference with GemLite, TorchAO and SGLang
Large Language Models (LLMs) are typically very resource-intensive, requiring significant amounts of memory, compute and power to operate effectively. Quantization provides a solution by reducing weights and activations from 16 bit floats to lower bitrates (e.g., 8 bit, 4 bit, 2 bit), achieving significant speedup and memory savings and also enables support for larger batch sizes.
January 14, 2025
GenAI Acceleration for PyTorch 2.5 on Intel® Xeon®Processors
This blog is the fifth in a series focused on accelerating generative AI models with pure, native PyTorch. We demonstrate the GenAI acceleration of GPTFast, Segment Anything Fast, and Diffusion Fast on Intel® Xeon®Processors.
January 09, 2025
Integrating Ascend Backend with Torchtune through PyTorch Multi-Device Support
In this blog, we will briefly introduce torchtune, the Ascend backend, and demonstrate how torchtune can be used to fine-tune models with Ascend.
January 06, 2025
High-Performance Low-Bit Operators for PyTorch
We are excited to announce the addition of embedding operators with low-bit weights (1-8 bit) and linear operators with 8-bit dynamically quantized activations and low-bit weights (1-8 bit) for Arm CPUs in TorchAO, PyTorch’s native low-precision library. These operators work seamlessly across all PyTorch surfaces, including eager, torch.compile, AOTI, and ExecuTorch, and are available to use in torchchat.
December 23, 2024
PyTorch Grows as the Dominant Open Source Framework for AI and ML: 2024 Year in Review
This past year was a monumental year for PyTorch from major releases to the flagship PyTorch Conference. We’ve seen incredible growth in contributions from more than 3,500 individuals and 3,000 organizations. It’s safe to say PyTorch has now become the dominant deep learning framework for AI/ML. PyTorch leads the model training space with a 63% adoption rate according to the recent Shaping the Future of Generative AI Report from the Linux Foundation.
