New method accelerates data retrieval in huge databases
Researchers used machine learning to build faster and more efficient hash functions, which are a key component of databases.
MIT Schwarzman College of Computing
MIT professor to Congress: “We are at an inflection point” with AI
Aleksander Mądry urges lawmakers to ask rigorous questions about how AI tools are being used by corporations.
Matthew Kearney: Bringing AI and philosophy into dialogue
The computer science and philosophy double-major aims to advance the field of AI ethics.
Creating a versatile vaccine to take on Covid-19 in its many guises
Aided by machine learning, scientists are working to develop a vaccine that would be effective against all SARS-CoV-2 strains.
Large language models are biased. Can logic help save them?
MIT researchers trained logic-aware language models to reduce harmful stereotypes like gender and racial biases.
MIT-Takeda Program heads into fourth year with crop of 10 new projects
The program leverages MIT’s research expertise and Takeda’s industrial know-how for research in artificial intelligence and medicine.
Efficient technique improves machine-learning models’ reliability
The method enables a model to determine its confidence in a prediction, while using no additional data and far fewer computing resources than other methods.
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.