
NVIDIA has launched its DGX GB300 supercomputer at the Naval Postgraduate School in Monterey, California. This deployment provides over 1,500 students and 600 faculty members with access to advanced AI computing capabilities. The supercomputer will support research in weather prediction, cybersecurity, and disaster response. This initiative is part of a broader collaboration to integrate AI into military education, equipping future leaders with the skills to utilize AI technologies effectively.
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This release quietly expands llama.cpp's hardware support to include Qualcomm's Hexagon NPU on Linux arm64, a significant step for local inference on Snapdragon devices. It also updates CUDA builds to version 13.4 and introduces ROCm 10.0 binaries, keeping the project aligned with the latest NVIDIA and AMD driver ecosystems. KleidiAI on Apple Silicon is temporarily disabled in this build, likely due to stability checks rather than a feature rollback. For developers targeting edge AI or diverse GPU stacks, this update ensures broader compatibility without requiring custom compilation.
© Lev SelectorNVIDIA introduced the NVFP4 4-bit format and SoL-Pi technology, which uses 2x fewer tokens for improved efficiency.
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