Explore how neuromorphic chips and brain-inspired computing bring low-power, efficient intelligence to edge AI, robotics, and IoT through spiking neural networks and next-gen processors.
Deep learning emerges as an important new resource-intensive workload and has been successfully applied in computer vision, speech, natural language processing, and so on. Distributed deep learning is ...
According to @JeffDean, the influential 'The Tail at Scale' paper co-authored with @labarroso has been honored with the SIGOPS Hall of Fame award for its significant ...
Thinking Machines, the AI startup founded earlier this year by former OpenAI CTO Mira Murati, has launched its first product: Tinker, a Python-based API designed to make large language model (LLM) ...
What if you could train massive machine learning models in half the time without compromising performance? For researchers and developers tackling the ever-growing complexity of AI, this isn’t just a ...
A quiet shift in the foundations of artificial intelligence (AI) may be underway, and it is not happening in a hyperscale data center. 0G Labs, the first decentralized AI protocol (AIP), in ...
According to Jeff Dean on Twitter, the 2015 SOSP History Day event highlighted the extensive evolution of operating systems and distributed systems over the past 50 years, featuring talks from ...
The new capabilities are designed to enable enterprises in regulated industries to securely build and refine machine learning models using shared data without compromising privacy. AWS has rolled out ...
May 15, 2025 — The Argonne Leadership Computing Facility will host an overview of key AI frameworks, toolkits, and strategies to achieve high-performance training and inference on the Aurora exascale ...
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