Solving a machine-learning mystery
Large language models like OpenAI’s GPT-3 are massive neural networks that can generate human-like text, from poetry to programming code. Trained using troves of internet data, these machine-learning models take...
3 Questions: Leo Anthony Celi on ChatGPT and medicine
Launched in November 2022, ChatGPT is a chatbot that can not only engage in human-like conversation, but also provide accurate answers to questions in a wide range of knowledge domains....
Helping companies deploy AI models more responsibly
Companies today are incorporating artificial intelligence into every corner of their business. The trend is expected to continue until machine-learning models are incorporated into most of the products and services...
Efficient technique improves machine-learning models’ reliability
Powerful machine-learning models are being used to help people tackle tough problems such as identifying disease in medical images or detecting road obstacles for autonomous vehicles. But machine-learning models can...
MIT-Takeda Program heads into fourth year with crop of 10 new projects
In 2020, the School of Engineering and Takeda Pharmaceutical Company launched the MIT-Takeda Program, which aims to leverage the experience of both entities to solve problems at the intersection of...
Integrating humans with AI in structural design
Modern fabrication tools such as 3D printers can make structural materials in shapes that would have been difficult or impossible using conventional tools. Meanwhile, new generative design systems can take...
Robot armies duke it out in Battlecode’s epic on-screen battles
In a packed room in MIT’s Stata Center, hundreds of digital robots collide across a giant screen projected at the front of the room. A crowd of students in the...
Large language models are biased. Can logic help save them?
Turns out, even language models “think” they’re biased. When prompted in ChatGPT, the response was as follows: “Yes, language models can have biases, because the training data reflects the biases...
New insights into training dynamics of deep classifiers
A new study from researchers at MIT and Brown University characterizes several properties that emerge during the training of deep classifiers, a type of artificial neural network commonly used for...
