Helping scientists run complex data analyses without writing code
Co-founded by an MIT alumnus, Watershed Bio offers researchers who aren’t software engineers a way to run large-scale analyses to accelerate biology.
AI system learns from many types of scientific information and runs experiments to discover new materials
The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.
New tool makes generative AI models more likely to create breakthrough materials
With SCIGEN, researchers can steer AI models to create materials with exotic properties for applications like quantum computing.
How are MIT entrepreneurs using AI?
This year’s delta v summer accelerator offered an up-close look at how AI is changing the process of building a startup.
Helping data storage keep up with the AI revolution
Storage systems from Cloudian, co-founded by an MIT alumnus, are helping businesses feed data-hungry AI models and agents at scale.
Model predicts long-term effects of nuclear waste on underground disposal systems
The simulations matched results from an underground lab experiment in Switzerland, suggesting modeling could be used to validate the safety of nuclear disposal sites.
Accelerating scientific discovery with AI
FutureHouse, co-founded by Sam Rodriques PhD ’19, has developed AI agents to automate key steps on the path toward scientific progress.
Helping machines understand visual content with AI
Coactive, founded by two MIT alumni, has built an AI-powered platform to unlock new insights from content of all types.
Teaching AI models what they don’t know
A team of MIT researchers founded Themis AI to quantify AI model uncertainty and address knowledge gaps.
Vana is letting users own a piece of the AI models trained on their data
More than 1 million people are contributing their data to Vana’s decentralized network, which started as an MIT class project.