A Generalist Agent
Reed, Scott, Zolna, Konrad, Parisotto, Emilio, Colmenarejo, Sergio Gomez, Novikov, Alexander, Barth-Maron, Gabriel, Gimenez, Mai, Sulsky, Yury, Kay, Jackie, Springenberg, Jost Tobias, Eccles, Tom, Bruce, Jake, Razavi, Ali, Edwards, Ashley, Heess, Nicolas, Chen, Yutian, Hadsell, Raia, Vinyals, Oriol, Bordbar, Mahyar, de Freitas, Nando
–arXiv.org Artificial Intelligence
Inspired by progress in large-scale language modeling, 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 generalist policy. The same network with the same weights can play Atari, caption images, chat, stack blocks with a real robot arm and much more, deciding based on its context whether to output text, joint torques, button presses, or other tokens. In this report we describe the model and the data, and document the current capabilities of Gato. What is the capital of France?
arXiv.org Artificial Intelligence
Nov-11-2022
- Country:
- Asia > Middle East
- Jordan (0.04)
- Europe > France (0.24)
- Asia > Middle East
- Genre:
- Research Report (1.00)
- Industry:
- Health & Medicine (0.93)
- Leisure & Entertainment
- Games > Computer Games (1.00)
- Sports (1.00)
- Technology:
- Information Technology > Artificial Intelligence
- Cognitive Science (1.00)
- Machine Learning
- Neural Networks > Deep Learning (1.00)
- Reinforcement Learning (0.94)
- Natural Language
- Chatbot (0.66)
- Large Language Model (1.00)
- Representation & Reasoning (1.00)
- Robots (1.00)
- Information Technology > Artificial Intelligence