Top stories highlighted the Institute’s leading positions in world and national rankings; new collaboratives tackling manufacturing, generative AI, and quantum; how one professor influenced hundreds of thousands of students around the world; and more.
Concrete batteries, AI-developed antibiotics, the ozone’s recovery, and a more natural bionic knee were some of the most popular topics on MIT News.
From robotics to apps like “NerdXing,” senior Julianna Schneider is building technologies to solve problems in her community.
CSAIL researchers find even “untrainable” neural nets can learn effectively when guided by another network’s built-in biases using their guidance method.
MIT-IBM Watson AI Lab researchers developed an expressive architecture that provides better state tracking and sequential reasoning in LLMs over long texts.
The senior, who is involved in Dormitory Council, Hydrant, the Student Information Processing Board, and SuperUROP, is double majoring in computer science and engineering and in urban planning.
The consortium convenes industry, academia, and policy leaders to navigate competing demands and reimagine materials supply.
An AI-driven system lets users design and build simple, multicomponent objects by describing them with words.
Assistant Professor Yunha Hwang utilizes microbial genomes to examine the language of biology. Her appointment reflects MIT’s commitment to exploring the intersection of genetics research and AI.
Angela Koehler, Iain Cheeseman, and Katharina Ribbeck are shaping the collaborative as a platform for transformative research, translation, and talent development across MIT.
The “self-steering” DisCIPL system directs small models to work together on tasks with constraints, like itinerary planning and budgeting.
The new certificate program will equip naval officers with skills needed to solve the military’s hardest problems.
Tools for forecasting and modeling technological improvements and the impacts of policy decisions can result in more effective and impactful decision-making.
The technique can help scientists in economics, public health, and other fields understand whether to trust the results of their experiments.
By stacking multiple active components based on new materials on the back end of a computer chip, this new approach reduces the amount of energy wasted during computation.