Designing for outer space
With NASA planning permanent bases in space and on the moon, MIT students develop prototypes for habitats far from planet Earth.
With NASA planning permanent bases in space and on the moon, MIT students develop prototypes for habitats far from planet Earth.
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.
A newly described technology improves the clarity and speed of using two-photon microscopy to image synapses in the living brain.
The dedicated teacher and academic leader transformed research in computer architectures, parallel computing, and digital design, enabling faster and more efficient computation.
The program focused on AI in health care, drawing on Takeda’s R&D experience in drug development and MIT’s deep expertise in AI.
Graduate engineering program is No. 1 in the nation; MIT Sloan is No. 5.
Three innovations by an MIT-based team enable high-resolution, high-throughput imaging of human brain tissue at a full range of scales, and mapping connectivity of neurons at single-cell resolution.
LLMs trained primarily on text can generate complex visual concepts through code with self-correction. Researchers used these illustrations to train an image-free computer vision system to recognize real photos.
The SPARROW algorithm automatically identifies the best molecules to test as potential new medicines, given the vast number of factors affecting each choice.
Leuko, founded by a research team at MIT, is giving doctors a noninvasive way to monitor cancer patients’ health during chemotherapy — no blood tests needed.
Combining natural language and programming, the method enables LLMs to solve numerical, analytical, and language-based tasks transparently.
In “Scientific InQueery,” LGBTQ+ MIT faculty and graduate students describe finding community and living their authentic lives in the research enterprise.
MIT scientists honored in each of the three Kavli Prize categories: neuroscience, nanoscience, and astrophysics, respectively.
The method uses language-based inputs instead of costly visual data to direct a robot through a multistep navigation task.
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.