Difference between revisions of "Gato"
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* [[Google]] | * [[Google]] | ||
* [http://storage.googleapis.com/deepmind-media/A%20Generalist%20Agent/Generalist%20Agent.pdf A Generalist Agent | DeepMind] | * [http://storage.googleapis.com/deepmind-media/A%20Generalist%20Agent/Generalist%20Agent.pdf A Generalist Agent | DeepMind] | ||
| − | * [http://www.louisbouchard.ai/deepmind-gato/ Deepmind's new model Gato is amazing!] | + | * [http://www.louisbouchard.ai/deepmind-gato/ Deepmind's new model Gato is amazing! | Louis Bouchard] |
DeepMind's “generalist” AI model 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. | DeepMind's “generalist” AI model 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. | ||
Revision as of 07:25, 24 May 2022
YouTube search... ...Google search
- Google's Tools and Resources
- A Generalist Agent | DeepMind
- Deepmind's new model Gato is amazing! | Louis Bouchard
DeepMind's “generalist” AI model 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.
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