MIT Schwarzman College of Computing
MIT Schwarzman College of Computing

New techniques efficiently accelerate sparse tensors for massive AI models

Complimentary approaches — “HighLight” and “Tailors and Swiftiles” — could boost the performance of demanding machine-learning tasks.

New technique helps robots pack objects into a tight space

Researchers coaxed a family of generative AI models to work together to solve multistep robot manipulation problems.

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

AI copilot enhances human precision for safer aviation

Designed to ensure safer skies, “Air-Guardian” blends human intuition with machine precision, creating a more symbiotic relationship between pilot and aircraft.

A more effective experimental design for engineering a cell into a new state

By focusing on causal relationships in genome regulation, a new AI method could help scientists identify new immunotherapy techniques or regenerative therapies.

From physics to generative AI: An AI model for advanced pattern generation

Inspired by physics, a new generative model PFGM++ outperforms diffusion models in image generation.

MIT scholars awarded seed grants to probe the social implications of generative AI

The 27 finalists — representing every school at MIT — will explore the technology’s impact on democracy, education, sustainability, communications, and much more.

Multi-AI collaboration helps reasoning and factual accuracy in large language models

Researchers use multiple AI models to collaborate, debate, and improve their reasoning abilities to advance the performance of LLMs while increasing accountability and factual accuracy.

AI-driven tool makes it easy to personalize 3D-printable models

With Style2Fab, makers can rapidly customize models of 3D-printable objects, such as assistive devices, without hampering their functionality.

How an archeological approach can help leverage biased data in AI to improve medicine

Although computer scientists may initially treat data bias and error as a nuisance, researchers argue it’s a hidden treasure trove for reflecting societal values.