Aneesh Muppidi

@aneeshers

Incoming PhD at @StanfordAILab. Rhodes Scholar @bold_lab_ai. prev @harvard

aneeshers.github.io

Joined May 2020

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Aneesh Muppidi
@aneeshers
Jun 30
Introducing Real-time RL. In the real world, time isn't free. The environment keeps "moving" even when you're computing your next action. We show how RL agents can learn to adaptively think in real-time games. 1/🧵
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Aneesh Muppidi
@aneeshers
Sep 14
Awesome notes @daphnesolves !
Daphne Cornelisse
@daphnesolves
Sep 14
Article
Lessons from reaching level 6 in Craftax through tabula rasa on-policy reinforcement learning
The policy below is playing Craftax. It obtains a total episode return of 162, which is 71% of the maximum achievable return. It crafts armour, learns to cast fireball, and defeats numerous enemies...
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Aneesh Muppidi
@aneeshers
Jul 27
Congrats @yiding_song and @DozenDucc!! This is such a brilliant team and awesome direction!
Hanming Ye
@DozenDucc
Jul 27
Introducing Waddle Labs: Claude Code for robots. Connect our API to your robot and enter a prompt, then our agents write code to achieve the task in 20 minutes. @yiding_song @theWaddleLabs
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Aneesh Muppidi
@aneeshers
Jul 17
Let’s go Nim!!
Nim Ravid
@Nim_Ravid1
Jul 16
Introducing Aidan, your newest AI employee Aidan is the first computer-using AI built for realtime conversation We’ve raised $45M from @sequoia and @8vc to bring Aidan to the world @NotionHQ and @DecagonAI already use Aidan to run customer interactions. This is how
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Aneesh Muppidi
@aneeshers
Jul 1
Now you can train robots on any preference you can describe in words (speed, precision, "delicateness") and even steer them at test time without retraining! Check out this awesome project from @marceltornev, @anubhamahajan01 and @AbhijnyaBhat!
Marcel Torné
@marceltornev
Jul 1
We should stop optimizing robot policies against a single overall reward. Trajectories differ along many axes, such as speed, precision, and subtask completion, and one can be better on some while worse on others. If we collapse all of that into a single overall axis we lose this
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