News

DeepMind shifts research to applied AI

Financial Times reports that Google DeepMind is pivoting away from purely academic research toward applied AI products. CEO Demis Hassabis explained the lab is now focused on models and tools that solve “real-world” problems, aiming for commercial impact rather than only scientific breakthroughs. This signals a major shift in strategy as DeepMind moves closer to competing directly with OpenAI, Anthropic, and others.

Microsoft pushes ahead on AI hardware

The Information revealed that Microsoft is accelerating its in-house AI chip efforts. The “Athena” chip, designed to reduce reliance on Nvidia GPUs, is already in testing with some developers. If successful, this could significantly cut costs for Microsoft’s Azure AI services and reshape the competitive balance of AI infrastructure

California introduces AI safety bill

Reuters covered California’s passage of SB 53, a new law requiring major AI companies to disclose safety testing results and publish transparency reports. It’s one of the first state-level attempts to regulate frontier AI. Analysts expect this to become a model for wider regulation in the U.S.

Summary & Stage / Timeline

• DeepMind is moving from research-heavy projects to applied AI with commercial products (now and over the next 12–18 months).

• Microsoft’s Athena chip is in testing, rollout expected in 2025.

• California’s SB 53 takes effect in early 2026, creating compliance obligations for large AI labs.

Significance / What to Watch

• DeepMind: This pivot shows that pure research may no longer be enough to justify funding — commercial viability is the new benchmark. Expect a wave of practical DeepMind tools in 2025.

• Microsoft: Hardware differentiation could make Azure AI cheaper and more attractive, challenging AWS and Google Cloud.

• Regulation: With California taking the lead, U.S. AI companies face growing compliance pressure. This will influence not just labs, but also startups building on their APIs.

Prompt Tip of the Day

If you want to future-proof your prompts for applied AI products like DeepMind’s upcoming tools, structure them around specific real-world tasks instead of open-ended creativity. Example: instead of “generate a plan for productivity”, ask “generate a 3-step weekly productivity routine for a remote design team using Notion and Figma.”