Chris Lattner shows how MAX and Mojo extend PyTorch across vendor hardware at PyTorchCon 2026
PyTorch · x · 2026-10-21
At PyTorch Conference 2026, Chris Lattner (EVP of Advanced AI Software and Platforms at Qualcomm) demonstrated how developers can extend PyTorch with MAX and Mojo. Targeting the repeated performance work developers redo for each hardware backend, MAX and Mojo serve as a shared foundation for running code across hardware from multiple vendors: Mojo combines Pythonic code with systems-language speed and low-level control, while MAX provides model authoring and a graph compiler targeting multi-vendor hardware.
More from Infra
- Corporate token spending growth collapses from 42% to 0.2% as hyperscaler ROIC falls to 20% — SumitGup · 2026-10-21
- Qualcomm plans worldwide performance-based layoffs as it chases $5B AI data center revenue — rohanpaul_ai · 2026-10-21
- vLLM at PyTorchCon 2026: KV cache and kernel optimizations across TPU, AMD, and NVIDIA — PyTorch · 2026-10-21
- antirez to port DeepSeek Infer kernels to DGX Spark's SM121 for DwarfStar — antirez · 2026-10-21
- Ternary-Bonsai-2-9B: 2-bit ternary vision-language model trends on Hugging Face for on-device use — prism-ml · 2026-10-21
- General Compute x Positron: GPUs Handle Prefill, Memory-First Chips Tackle Decode-Bound LLM Inference — cneuralnetwork · 2026-10-21