Models & Labs
Google DeepMind Unveils Gemini 3.5 Flash Cyber
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Why it matters
- →Gemini 3.5 Flash Cyber offers a scalable and affordable solution for cybersecurity challenges.
- →It enables extensive codebase analysis, enhancing vulnerability detection and mitigation.
- →The model's deployment to trusted partners helps preemptively address potential threats.
Google DeepMind has launched Gemini 3.5 Flash Cyber, a lightweight cybersecurity model aimed at efficiently identifying and fixing software vulnerabilities. This model, based on the 3.5 Flash framework, is designed to be a cost-effective alternative to larger models, allowing for extensive codebase analysis and frequent scanning. Initially, it will be available to governments and trusted partners through a limited-access pilot program. This initiative aims to equip frontline defenders with advanced tools to address vulnerabilities before they can be exploited.
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Google DeepMind commits $40M to Genesis Mission
Google DeepMind is making a substantial investment in the future of scientific research by allocating $40 million in AI tokens and cloud credits to the Genesis Mission. This initiative is designed to accelerate the pace of American scientific discovery by providing advanced AI tools to researchers at the Department of Energy's National Laboratories. Tools such as AlphaEvolve and AlphaFold 3 are already being utilized to expedite complex mathematical and biological research. This commitment not only enhances the capabilities of scientists but also highlights the transformative potential of AI in driving scientific breakthroughs.
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Google DeepMind Launches Gemini 3.6 Flash Models
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llama.cpp b10083 Release Expands Platform Support
The latest b10083 release of llama.cpp continues its trend of broadening platform compatibility, making it a versatile choice for developers across different systems. Notably, this update includes support for Ubuntu with ROCm 7.2, enhancing performance for AMD GPU users. Windows users benefit from updated CUDA support, with DLLs for both CUDA 12.4 and 13.3, ensuring compatibility with the latest NVIDIA technologies. While no groundbreaking new features are introduced, the release solidifies llama.cpp's position as a flexible inference runtime across diverse hardware setups.
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llama.cpp b10085 release updates Qwen3-VL interpolation
The latest b10085 release of llama.cpp addresses a key issue with the Qwen3-VL vision model's position embedding interpolation. By aligning the interpolation method with the transformers reference, the update ensures more accurate grounding coordinates, particularly for larger and non-square images. This change is crucial for developers working with image processing tasks, as it reduces discrepancies in image scaling. While the update doesn't introduce new models, it enhances the precision of existing functionalities, making llama.cpp a more reliable tool for AI developers.