3 Questions: Leo Anthony Celi on ChatGPT and medicine
The chatbot’s success on the medical licensing exam shows that the test — and medical education — are flawed, Celi says.
Solving a machine-learning mystery
A new study shows how large language models like GPT-3 can learn a new task from just a few examples, without the need for any new training data.
Automating the math for decision-making under uncertainty
A new tool brings the benefits of AI programming to a much broader class of problems.
Making computer science research more accessible in India
Passionate about creating educational opportunities in India, PhD student Siddhartha Jayanti recently explored multiprocessor speed limits, in a paper written in the Indian language Telugu.
When should data scientists try a new technique?
A new measure can help scientists decide which estimation method to use when modeling a particular data problem.
Putting clear bounds on uncertainty
Computer scientists want to know the exact limits in our ability to clean up, and reconstruct, partly blurred images.
Research, education, and connection in the face of war
“I wouldn’t let the aggressor in the war squash my dreams,” says Ukrainian mathematician and MITx MicroMasters learner Tetiana Herasymova.
MIT researchers develop an AI model that can detect future lung cancer risk
Deep-learning model takes a personalized approach to assessing each patient’s risk of lung cancer based on CT scans.
Computers that power self-driving cars could be a huge driver of global carbon emissions
Study shows that if autonomous vehicles are widely adopted, hardware efficiency will need to advance rapidly to keep computing-related emissions in check.
2022-23 Takeda Fellows: Leveraging AI to positively impact human health
New fellows are working on health records, robot control, pandemic preparedness, brain injuries, and more.
Q&A: A fresh look at data science
MIT Visiting Scholar Alfred Spector discusses the power of data science and visualization, as well as his new textbook on the subject.
Unpacking the “black box” to build better AI models
Stefanie Jegelka seeks to understand how machine-learning models behave, to help researchers build more robust models for applications in biology, computer vision, optimization, and more.
Manufacturing a cleaner future
Startups founded by mechanical engineers are at the forefront of developing solutions to mitigate the environmental impact of manufacturing.
MIT community members win 2023 IEEE medals and awards
Seven faculty and alumni are among the winners of the prestigious honors for electrical engineers and computer scientists.
Subtle biases in AI can influence emergency decisions
But the harm from a discriminatory AI system can be minimized if the advice it delivers is properly framed, an MIT team has shown.