Speeding up planning decisions with AI

Unlocking UK house-building with AI-accelerated planning

UK government partners with Google DeepMind to build a new AI-powered prototype aimed at faster housing decisions.

Partnering with industry leaders to accelerate AI transformation

Google DeepMind partners with global consultancies to bring the power of frontier AI to organizations around the world.

Strengthening Singapore’s AI Future: A New National Partnership

Google DeepMind and Singapore partner to apply frontier AI to address complex challenges across health, education, and sustainability and more.

A complementary study on PlanGPT: Evaluation with defined Performance Metrics and comparison with a planner

arXiv:2606. 10489v1 Announce Type: new Abstract: Automated Planning is a subfield of Artificial Intelligence (AI) where the main objective is generating a sequence of actions, known as a plan, that helps us reach a goal state from an initial state.

Deepening our partnership with the UK AI Security Institute

Google DeepMind and UK AI Security Institute (AISI) strengthen collaboration on critical AI safety and security research

We’re expanding our presence in Singapore to advance AI in the Asia-Pacific region

Google DeepMind opens a new Singapore research lab, accelerating AI progress in the Asia-Pacific region.

We’re launching the Google DeepMind Accelerator program in Asia Pacific to tackle environmental risks

Accelerating discovery in India through AI-powered science and education

Google DeepMind brings National Partnerships for AI initiative to India, scaling AI for science and education

Announcing our partnership with the Republic of Korea

Google DeepMind and Korea partner to accelerate scientific breakthroughs using frontier AI models

Google DeepMind and A24 announce first-of-its-kind research partnership

DeepPlanner: Scaling Planning Capability for Deep Research Agents via Advantage Shaping

DeepPlanner is an end-to-end reinforcement learning framework designed to enhance the planning capabilities of deep research agents. It introduces an entropy-based advantage shaping mechanism that allocates larger updates to high-entropy planning tokens and selectively upweights sample-level advantages during planning-intensive rollouts. Experiments on seven deep research benchmarks show that DeepPlanner improves planning quality and achieves state‑of‑the‑art results with a lower training budget.

APIVOT: Adaptive Planning with Interleaved Vision-Language Thoughts

arXiv:2607. 08024v1 Announce Type: cross Abstract: Long-horizon robot planning requires jointly reasoning over semantic task structure and geometric feasibility.