New training approach could help AI agents perform better in uncertain conditions
Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.
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Sometimes, it might be better to train a robot in an environment that’s different from the one where it will be deployed.
RAG retrieves data from a preexisting knowledge base (your data), combines it with the LLM’s knowledge, and generates responses with more human-like language. However, in order for generative AI to…
Associate Professor Luca Carlone is working to give robots a more human-like awareness of their environment.
Station A, founded by MIT alumni, makes the process of buying clean energy simple for property owners.
Starting with a single frame in a simulation, a new system uses generative AI to emulate the dynamics of molecules, connecting static molecular structures and developing blurry pictures into videos.
Providing electricity to power-hungry data centers is stressing grids, raising prices for consumers, and slowing the transition to clean energy.
Rapid development and deployment of powerful generative AI models comes with environmental consequences, including increased electricity demand and water consumption.
Assistant Professor Manish Raghavan wants computational techniques to help solve societal problems.
The startup NALA, which began as an MIT class project, directly matches art buyers with artists.
With their recently-developed neural network architecture, MIT researchers can wring more information out of electronic structure calculations.