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full-title:: [Edge 389: Understanding Large Action Models](https://omnivore.app/me/edge-389-understanding-large-action-models-18f0aa5d523)
site:: [thesequence.substack.com](https://thesequence.substack.com/p/edge-389-understanding-large-action?isFreemail=true&post_id=143872305&publication_id=54309&r=z2w67&token=eyJ1c2VyX2lkIjo1ODkyMTU2NywicG9zdF9pZCI6MTQzODcyMzA1LCJpYXQiOjE3MTM4Njk1OTMsImV4cCI6MTcxNjQ2MTU5MywiaXNzIjoicHViLTU0MzA5Iiwic3ViIjoicG9zdC1yZWFjdGlvbiJ9.M_pgg-o8pXy92umU-6UYJ6FvQAxnmyXe2c2BHxLPhto&triedRedirect=true)
author:: davide.diruscio@gmail.com
labels:: [[Newsletter]] [[LLMs]]
date-saved:: [[23-04-2024]]
date-archived:: [[07-05-2024]]
is-archived:: 10
source:: [[Omnivore]]
state:: [[archived]]
- ### Highlights
collapsed:: true
- > ### **Large Action Models and Autonomous Agents**
>
The ability to execute actions in a given environment is one of the hallmarks of autonomous agents. One of the key topics of debate in autonomous agent circles is how much of the action execution relies on external components versus being built into the model itself. One [⤴️](https://omnivore.app/me/edge-389-understanding-large-action-models-18f0aa5d523#4157a2d2-1c2d-45bb-8881-0d5200061a32)
omnivore-note:: [[LLM/LAM]] #omnivore-note-color