Conducting world-class research requires solving difficult engineering problems. Tools and infrastructure developed by our engineering teams have successfully enabled our most significant research milestones, such as AlphaGo, AlphaStar, and AlphaFold.
These systems enable training of large-scale neural networks by unlocking scalable, parallel computation across diverse hardware. Internal tools for research empower our research team to run experiments seamlessly and make rapid scientific progress at scale.
Our multidisciplinary engineering team, with expertise ranging from software, hardware, and research engineers to designers, artists, and program managers, work across all DeepMind teams to deliver high-impact, state-of-the-art research. Many of our tools, libraries, environments, and papers are available open source.
Research engineers and software engineers on the Research team tackle unique engineering challenges that combine state-of-the-art computer systems and AI algorithms. This is done by developing prototypes and tools that allow our teams to perform rigorous experimentation at scale. This includes creating complex reinforcement learning agents and training pipelines alongside tools for visualisation, debugging, testing, and running reliable agents.
The Research Platform team’s mission is to create the most efficient platform for our research, maximising use of our resources and enabling new research ideas. Our core team is a group of software engineers within DeepMind Research who work to provide a best-in-class research workflow. We build tools, infrastructure, libraries, frameworks, services, and products to enable and accelerate the next generation of research ideas. We manage and leverage DeepMind’s massive computational resource pool to maximum effectiveness (TPUs, GPUs, and CPUs) and we collaborate with researchers to build innovative and lasting engineering solutions that advance research.
Progress in AI requires next-generation environments - rich, interactive virtual worlds in which we can test our systems and allow them to learn a wide variety of tasks. Our Worlds team, who are developers, designers, artists, QA technicians, and program managers with experience in engineering, games, and VFX companies, is responsible for creating these environments.
We collaborate with researchers to design and build a wide variety of environments and tasks using well-known video game engines such as Unity and Unreal, while creating new platforms and tools that empower researchers to build environments themselves. From bespoke mini-games aimed at answering specific research questions to expansive first-person games using modern 3D engines, the Worlds team plays a fundamental part in every research area at DeepMind.
The Robotics lab is a group of multidisciplinary research scientists, research engineers, and software engineers who pioneer new approaches in robotics.
Robotics is a critical part of developing general-purpose learning algorithms because systems must learn to deal with the incredible complexity and ever-changing conditions of the real world. We collaborate with multiple teams across DeepMind to endow our systems with the ability to learn, allowing them to respond and adapt to a variety of variable environments. In particular, we focus on learning complex manipulation and navigation tasks and understanding how systems respond to the physical world.