Google's DiffusionGemma proves you don't need to train from scratch to build a text diffusion model
Instead of training a new model from scratch, Google DeepMind retrofitted Gemma 4 into a diffusion model using less than 10 percent of the original training budget. DiffusionGemma generates 256 tokens in parallel instead of one at a time, hitting about 1,500 tokens per second. Quality still trails the original autoregressive model in benchmarks, especially on reasoning tasks.
Deepmind CEO Hassabis says "nobody in the world knows what happens next" so "cautious optimism" means building guardrails now
Google Deepmind CEO Demis Hassabis has published a sweeping proposal for how to handle advanced AI. He wants a new US standards body modeled after financial regulator FINRA that would develop evaluation protocols for frontier models and could coordinate a slowdown in AI development if needed. Startups and research models would be exempt.
Google Deepmind treats its own AI agents like rogue employees with office keys
Google Deepmind treats its own AI agents as potential insider threats. The company’s new “AI Control Roadmap” ties security measures to measurable AI capabilities, and an analysis of one million coding tasks shows most problems stem from overzealous agents, not malicious intent. Deepmind warns the window for global security standards is closing fast.