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🆕 Introducing JAT, the first open-source multi-modal, multi-task multi-domain agent! 🤖 A step toward open generalist agents! 🚀 📰 Blog:

73,212 views • 2 years ago •via X (Twitter)

10 Comments

Quentin Gallouédec's profile picture
Quentin Gallouédec2 years ago

Huge kudos to @ClementRomac @edwardbeeching @Thom_Wolf for all the work you've done.

Quentin Gallouédec's profile picture
Quentin Gallouédec2 years ago

- 📄 Paper: - 💻 Code: - 🗂️ Dataset: - 🤖 Model:

Jeff Clune's profile picture
Jeff Clune2 years ago

Very cool! Did you consider using Go-Explore for the Atari trajectories? It solves all Atari games.

Quentin Gallouédec's profile picture
Quentin Gallouédec2 years ago

Go-Explore is definitely a golden choice for Atari. Having pre-trained Go-Explore agents and a trajectory dataset hosted of 🤗 Hub would allow JAT to be trained straight away with the Go-Explore data!

Bryan Kyritz's profile picture
Bryan Kyritz2 years ago

This video is so insane

Yutao Chen's profile picture
Yutao Chen2 years ago

Does JAT use the same network and same weight for all tasks (i.e. atari, mujuco, minigrid)? That's genuinely fascinating! I'm working on similar things recently, i.e. learning a world model to train multi-task RL agents, and your work looks really promising and inspiring 🤗

Quentin Gallouédec's profile picture
Quentin Gallouédec2 years ago

Yes, same weights for all tasks!

Ruben Hassid's profile picture
Ruben Hassid2 years ago

But all I want is a multi-fruit juice

Matt Shumer's profile picture
Matt Shumer2 years ago

@josh_bickett

Nicolay Rusnachenko's profile picture
Nicolay Rusnachenko2 years ago

Thanks for sharing and making aware of it! 👏👀

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