Phillip Isola
@phillipisola.bsky.social
Associate Professor in EECS at MIT. Neural nets, generative models, representation learning, computer vision, robotics, cog sci, AI.
https://web.mit.edu/phillipi/
https://web.mit.edu/phillipi/
Sharing some new work!
A big dream in AI is to create world models of sufficient quality that you can train agents within them.
Classic simulators lack visual diversity and realism. GenAI lacks physical accuracy. But combining the two can work pretty well!
Paper: arxiv.org/abs/2411.00083
A big dream in AI is to create world models of sufficient quality that you can train agents within them.
Classic simulators lack visual diversity and realism. GenAI lacks physical accuracy. But combining the two can work pretty well!
Paper: arxiv.org/abs/2411.00083
November 14, 2024 at 1:30 AM
Sharing some new work!
A big dream in AI is to create world models of sufficient quality that you can train agents within them.
Classic simulators lack visual diversity and realism. GenAI lacks physical accuracy. But combining the two can work pretty well!
Paper: arxiv.org/abs/2411.00083
A big dream in AI is to create world models of sufficient quality that you can train agents within them.
Classic simulators lack visual diversity and realism. GenAI lacks physical accuracy. But combining the two can work pretty well!
Paper: arxiv.org/abs/2411.00083