Helping nonexperts build advanced generative AI models
MosaicML, co-founded by an MIT alumnus and a professor, made deep-learning models faster and more efficient. Its acquisition by Databricks broadened that mission.
MosaicML, co-founded by an MIT alumnus and a professor, made deep-learning models faster and more efficient. Its acquisition by Databricks broadened that mission.
The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
DenseAV, developed at MIT, learns to parse and understand the meaning of language just by watching videos of people talking, with potential applications in multimedia search, language learning, and robotics.
The technique characterizes a material’s electronic properties 85 times faster than conventional methods.
In the new economics course 14.163 (Algorithms and Behavioral Science), students investigate the deployment of machine-learning tools and their potential to understand people, reduce bias, and improve society.
Graduate student Nolen Scruggs works with a local tenant association to address housing inequality as part of the MIT Initiative on Combatting Systemic Racism.
A new “consensus game,” developed by MIT CSAIL researchers, elevates AI’s text comprehension and generation skills.
A new algorithm learns to squish, bend, or stretch a robot’s entire body to accomplish diverse tasks like avoiding obstacles or retrieving items.
TorNet, a public artificial intelligence dataset, could help models reveal when and why tornadoes form, improving forecasters’ ability to issue warnings.
A new technique can be used to predict the actions of human or AI agents who behave suboptimally while working toward unknown goals.