School of Engineering
School of Engineering

A better way to study ocean currents

A new machine-learning model makes more accurate predictions about ocean currents, which could help with tracking plastic pollution and oil spills, and aid in search and rescue.

Joining the battle against health care bias

Leo Anthony Celi invites industry to broaden its focus in gathering and analyzing clinical data for every population.

3 Questions: Jacob Andreas on large language models

The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.

Study: AI models fail to reproduce human judgements about rule violations

Models trained using common data-collection techniques judge rule violations more harshly than humans would, researchers report.

Success at the intersection of technology and finance

Citadel founder and CEO Ken Griffin visits MIT, discusses how technology will continue to transform trading and investing.

Inaugural J-WAFS Grand Challenge aims to develop enhanced crop variants and move them from lab to land

Matt Shoulders will lead an interdisciplinary team to improve RuBisCO — the photosynthesis enzyme thought to be the holy grail for improving agricultural yield.

Training machines to learn more like humans do

Researchers identify a property that helps computer vision models learn to represent the visual world in a more stable, predictable way.

After Amazon, an ambition to accelerate American manufacturing

Jeff Wilke SM ’93, former CEO of Amazon’s Worldwide Consumer business, brings his LGO playbook to his new mission of revitalizing manufacturing in the U.S.

Researchers create a tool for accurately simulating complex systems

The system they developed eliminates a source of bias in simulations, leading to improved algorithms that can boost the performance of applications.

Researchers develop novel AI-based estimator for manufacturing medicine

A collaborative research team from the MIT-Takeda Program combined physics and machine learning to characterize rough particle surfaces in pharmaceutical pills and powders.