DeepMind is advancing AI research by collaborating with game developers to create new gameplay experiences. Their focus is on developing AI agents like SIMA, which can interact with game environments in a human-like manner without requiring game-specific modifications. This could lead to more dynamic and responsive AI companions and NPCs in games. The initiative builds on DeepMind's history of using games to drive AI breakthroughs, such as AlphaGo and AlphaFold. By partnering with studios like Fenris Creations, DeepMind aims to enhance both gaming and AI research.
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Prism's Bonsai 2 27B model is now natively supported in llama.cpp, bringing a high-efficiency architecture to the local inference ecosystem. The release includes specific runtime optimizations for its Hadamard transformations, ensuring smooth execution across diverse hardware backends like CUDA and ROCm. This integration allows developers to run a specialized 27B parameter model without custom conversion scripts or external wrappers. It expands the practical toolkit for those needing compact yet capable models on consumer-grade GPUs.
This release quietly cements llama.cpp as the universal inference runtime by adding default builds for CUDA 13.4 and ROCm 10.0 alongside existing CUDA 12 support. The shift to hidden symbol visibility prevents internal API leaks, cleaning up the library's interface for downstream integrations. While KleidiAI on Apple Silicon is temporarily disabled, the broad hardware coverage ensures developers can target NVIDIA, AMD, and Intel GPUs without custom compilation. It’s a maintenance-heavy update that solidifies cross-platform compatibility rather than introducing new capabilities.
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