7 results for “edge AI”
NVIDIA has introduced two new Jetson Thor modules aimed at bringing more capable AI workloads to robots and edge devices. The Jetson T3000 and T2000 are designed for systems that need to process vision, language and sensor data locally.
A developer known as slvDev has demonstrated a 28.9-million-parameter language model generating text at 9.88 tokens per second on an ESP32-S3. Running a language model on a sub-$10 microcontroller changes the cost floor for local AI.
Liquid AI has released the LFM2.5 model family, a comprehensive suite of open-weight models designed to run entirely on edge devices without cloud. The LFM2.5 releases address three critical constraints that have limited on-device AI.
NVIDIA says TensorRT Edge-LLM ran Qwen3.6-27B through the MLPerf Edge Agentic workload in 24 minutes 36 seconds on one Jetson AGX Thor. The 6.4x gap over llama.cpp puts long-context agent inference on edge.
PyTorch Foundation, Hugging Face, IBM, and Mitsubishi Electric will host PyTorch Day Japan 2026 in Tokyo on December 10.
Advanced Micro Devices (AMD) shares rose sharply on Monday after the company announced a major expansion of its strategic partnership with Microsoft (MSFT). This announcement is a critical validation for AMD's AI strategy.
In the high-stakes race to dominate artificial intelligence, two of the world's most valuable companies are pursuing fundamentally different strategies. Apple, known for its consumer devices, is reportedly taking a more cautious approach.