DeepSeek open sources DSpark, a new framework to speed up LLM inference by up to 85%

DSpark can make decoding faster, but acceptance quality still determines how much speed the system actually realizes.
GitHub

Using YOLO and the ZED

This repository contains multiple samples demonstrating how to use YOLO models with the ZED camera, utilizing the highly optimized TensorRT library, as well as a Python sample that uses PyTorch and ...
Tech Times

Qualcomm Closes $3.9 Billion Modular Deal: Meta Validates Full-Stack CUDA Challenge

Qualcomm confirmed a $3.92 billion all-stock deal to buy AI software startup Modular, paired with a Meta Platforms CPU ...

OpenAI unveils first custom AI inference chip, Jalapeño, with Broadcom — and its development was sped-up with OpenAI's own models

The companies attributed this speed to a deep software-hardware co-development process that actively used OpenAI’s own models ...
GitHub

GitHub - facebookincubator/AITemplate: AITemplate is a Python framework which renders neural network into high performance CUDA/HIP C++ code. Specialized for FP16 TensorCore ...

High performance: close to roofline fp16 TensorCore (NVIDIA GPU) / MatrixCore (AMD GPU) performance on major models, including ResNet, MaskRCNN, BERT, VisionTransformer, Stable Diffusion, etc. Unified ...