Browsing Tag
Google DeepMind
6 posts
Google DeepMind models, research, AI products, leadership, and policy coverage.
Gemini 3.5 Flash Makes Computer Use a Mainstream Agent Tool
Google has moved computer use into Gemini 3.5 Flash, letting developers build agents that can see screens and act across browser, mobile, and desktop environments. The useful question is how teams design the execution loop, safety gates, and sandbox around it.
Google’s AI Talent Losses Put Coding and Science Roadmaps Under Pressure
Google DeepMind lost Noam Shazeer to OpenAI and John Jumper to Anthropic in the same week. The moves matter because AI labs are competing for researchers who can steer coding agents, scientific AI, and frontier model strategy, not just write papers.
Google DeepMind’s A24 Deal Puts AI Inside the Filmmaking Workflow
Google DeepMind and A24 are launching a multi-project AI research partnership, with Google reportedly investing about $75 million in the studio. The deal is less about one AI movie tool than a test of whether creative AI can be shaped inside real film workflows without handing a tech company the studio library.
DeepMind’s AI Control Roadmap Makes Agent Security a Runtime Problem
Google DeepMind’s AI Control Roadmap treats powerful internal AI agents as systems that need monitoring, access limits, response plans, and shutdown paths. The framework is a signal for enterprises moving from chatbots to tool-using agents: alignment claims are no longer enough if the agent can touch code, data, infrastructure, or security workflows.
Google DeepMind’s AI Control Roadmap Treats Agents Like Insider Threats
Google DeepMind released an AI Control Roadmap for securing powerful internal AI agents. The plan borrows from cybersecurity, maps rogue-agent tactics to a MITRE ATT&CK-style taxonomy, and lays out detection and response tiers for systems that may soon act faster than human reviewers can supervise.
G7 AI Summit Turns Model Access Into a Sovereignty Fight
AI leaders are gathering at the G7 in France as Europe, Canada, and other allies question how much critical AI infrastructure should depend on U.S. model labs, cloud providers, chips, and export-control decisions.