Skip to content ↓

Topic

Computer science and technology

Download RSS feed: News Articles / In the Media / Audio

Displaying 1 - 15 of 1038 news clips related to this topic.
Show:

The Wall Street Journal

Prof. Armando Solar-Lezama speaks with The Wall Street Journal reporter Isabelle Bousquette about large language models (LLMs) in academia. Instead of building LLMs from scratch, Solar-Lezama suggests “students and researchers are focused on developing applications and even creating synthetic data that could be used to train LLMs,” writes Bousquette. 

Associated Press

Prof. Michael Cusumano speaks with Associated Press reporters Matt O’Brien and Sarah Parvini about a new approach to AI acquisitions and the impact on smaller AI startups. “To acquire only some employees or the majority, but not all, license technology, leave the company functioning but not really competing, that’s a new twist,” says Cusumano.

CNBC

Institute Prof. Daron Acemoglu speaks with CNBC Last Call host Brian Sullivan about what he describes as exaggerated claims about the macroeconomic effects of AI. “I am completely convinced that there are some impressive changes and there are some things that AI can really help us with, but it's not going to suddenly revolutionize everything we do,” Acemoglu says. “And if it's going to do it, it's going to take a while.”

Forbes

Forbes reporter Ulrich Boser spotlights Prof. Rosalind Picard and her work toward advancing “the capability of computers to recognize human emotions.” “AI can enhance learning, and chatbots can supplement many aspects of teaching and tutoring but true success lies in establishing better tutoring platforms to support – not replace – teachers,” writes Boser. 

NPR

Prof. Sherry Turkle joins Manoush Zomorodi of NPR’s "Body Electric" to discuss her latest research on human relationships with AI chatbots, which she says can be beneficial but come with drawbacks since artificial relationships could set unrealistic expectations for real ones. "What AI can offer is a space away from the friction of companionship and friendship,” explains Turkle. “It offers the illusion of intimacy without the demands. And that is the particular challenge of this technology." 

Popular Science

MIT scientists have created RoboGrocery, a robot prototype that can pack a bag of standard groceries, reports Mack DeGeurin for Popular Science. Using an RGB-D camera equipped with computer vision technology and grippers with pressure sensors, RoboGrocery’s “ability to assess items, determine their delicacy, and pack efficiently without causing damage sets it apart from conventional robotic packers,” explains Prof. Daniela Rus. 

TechCrunch

With Using multimodal sensing and a soft robotic manipulator, MIT scientists have developed an automated system, called RoboGrocery, that can pack groceries of different sizes and weights, reports Brian Heater for TechCrunch. Heater explains that as the soft robotic gripper touches an item, “pressure sensors in the fingers determine that they are, in fact, delicate and therefore should not go at the bottom of the bag — something many of us no doubt learned the hard way. Next, it notes that the soup can is a more rigid structure and sticks it in the bottom of the bag.”

Vox

Prof. Yoon Kim speaks with Vox reporter Adam Clark Estes on how to address hallucinations and misinformation within large language models. “I don't think we'll ever be at a stage where we can guarantee that hallucinations won't exist,” says Kim. “But I think there's been a lot of advancements in reducing these hallucinations, and I think we'll get to a point where they'll become good enough to use.”

Forbes

Researchers from MIT have developed RoboGrocery, a soft robotic system that “can determine how to pack a grocery item based on its weight, size and shape without causing damage to the item,” reports Jennifer Kite-Powell for Forbes. “This is more than just automation—it's a paradigm shift that enhances precision, reduces waste and adapts seamlessly to the diverse needs of modern retail logistics,” says Prof. Daniela Rus, director of CSAIL. 

Fast Company

Writing for Fast Company, Moshe Tanach highlights how researchers from the MIT Lincoln Laboratory Supercomputing Center are developing new technologies to reduce AI energy costs, such as power-capping hardware and tools that can halt AI training. 

BBC

MIT scientists have developed a “four-fingered robotic hand which is capable of rotating balls and toys in any direction and orientation,” reports Maisie Lillywhite for BBC News. “The improvement in dexterity could have significant implications for automating tasks such as handling goods for supermarkets or sorting through waste for recycling,” Lillywhite writes.

Wired

Prof. Dylan Hadfield-Menell is interviewed by Wired’s Will Knight about CriticGPT, a new tool developed by OpenAI that will assist human trainers in developing AI. “It might lead to big jumps in individual capabilities, and it might be a stepping stone towards sort of more effective feedback in the long run,” Hadfield-Menell says.

Forbes

Writing for Forbes, lecturer Guadalupe Hayes-Mota '08, SM '16, MBA '16 explores the role of artificial intelligence and biotechnology in transforming the healthcare industry specifically for venture capitalists (VCs). “The fusion of AI and biotechnology presents a wealth of opportunities for venture capitalists,” writes Hayes-Mota. “By staying attuned to emerging trends and adopting strategies for impactful investments, VCs can drive innovation and create transformative changes in healthcare.” 

New York Times

Research Scientist Neil Thompson speaks with New York Times reporter Hank Sanders about the economic and social impact of AI technology in the fast-food industry. Thompson explains that “voice A.I. is inaccurate often enough that it requires some level of human oversight, which decreases cost savings,” writes Hank.

Economist

MIT researchers have improved upon the diffusion models used in AI image generation, reports Alok Jha for The Economist. Working with electrically charged particles, the team created “Poisson flow generative models,” which “generate images of equal or better quality than state-of-the-art diffusion models, while being less error-prone and requiring between ten and 20 times fewer computational steps,” Jha explains.