User-friendly system can help developers build more efficient simulations and AI models
By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.
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By automatically generating code that leverages two types of data redundancy, the system saves bandwidth, memory, and computation.
A new approach, which takes minutes rather than days, predicts how a specific DNA sequence will arrange itself in the cell nucleus.
MIT CSAIL Principal Research Scientist Una-May O’Reilly discusses how she develops agents that reveal AI models’ security weaknesses before hackers do.
Projects from MIT course 4.043/4.044 (Interaction Intelligence) were presented at NeurIPS, showing how AI transforms creativity, education, and interaction in unexpected ways.
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.