In October 2021, we announced that we acquired the MuJoCo physics simulator, and made it freely available for everyone to support research everywhere. We also committed to developing and maintaining MuJoCo as a free, open-source, community-driven proje…
In October 2021, we announced that we acquired the MuJoCo physics simulator, and made it freely available for everyone to support research everywhere. We also committed to developing and maintaining MuJoCo as a free, open-source, community-driven proje…
If you want to be at DeepMind, go for it. Apply, interview, and just try. You might not get it the first time but that doesn’t mean you can’t try again. I never thought DeepMind would accept me, and when they did, I thought it was a mistake. Everyone d…
If you want to be at DeepMind, go for it. Apply, interview, and just try. You might not get it the first time but that doesn’t mean you can’t try again. I never thought DeepMind would accept me, and when they did, I thought it was a mistake. Everyone d…
In our recent paper, we explore how populations of deep reinforcement learning (deep RL) agents can learn microeconomic behaviours, such as production, consumption, and trading of goods. We find that artificial agents learn to make economically rationa…
In our recent paper, we explore how populations of deep reinforcement learning (deep RL) agents can learn microeconomic behaviours, such as production, consumption, and trading of goods. We find that artificial agents learn to make economically rationa…
Inspired by progress in large-scale language modelling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment …
Inspired by progress in large-scale language modelling, we apply a similar approach towards building a single generalist agent beyond the realm of text outputs. The agent, which we refer to as Gato, works as a multi-modal, multi-task, multi-embodiment …
To make RL more applicable to real-world applications like robotics, we propose using an intelligent evaluation procedure to select the policy for deployment, called active offline policy selection (A-OPS). In A-OPS, we make use of the prerecorded data…
To make RL more applicable to real-world applications like robotics, we propose using an intelligent evaluation procedure to select the policy for deployment, called active offline policy selection (A-OPS). In A-OPS, we make use of the prerecorded data…
