Google is now offering a distillation service for its Gemini models. This allows users to distill the capabilities of larger Gemini models into smaller, more efficient versions via the Google Cloud platform.
The feature is available through the Gemini Enterprise Agent Platform documentation.
Google has introduced three new models in its Flash series: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber, designed to improve token efficiency, latency, and reliability for production AI agents.
Google DeepMind and Google Cloud are committing $40 million in AI tokens and cloud credits to support the Department of Energy's Genesis Mission, aiming to double the pace of American scientific discovery within a decade. This expanded commitment provides DOE awardees with in-kind access to frontier AI tools, including AlphaFold 3 and AlphaEvolve, alongside Gemini for Government seats for tens of thousands of users across national laboratories.
This article provides an overview of the current state of simulation for Physical AI, explaining how simulation bridges the data gap for robotics by enabling scalable, photorealistic training environments. It outlines a three-computer paradigm (training, simulation, on-robot) and categorizes key simulation engines based on their specific capabilities and use cases.
Google has released three new models in its Flash tier—Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber—tuned for speed, cost efficiency, and high-volume agentic work rather than maximum reasoning depth.
Google has introduced Gemini 3.5 Flash Cyber, a lightweight cybersecurity model built on top of the 3.5 Flash architecture and fine-tuned to find, validate, and patch software vulnerabilities more efficiently than mainline Flash models.
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