MIT News·
To help robots do chores in places like homes and factories, a new approach from MIT uses one language model to clarify users’ instructions, then another to ignore irrelevant info.
Read full articleDuring a "Washington Post Live" panel discussion with ASU President Michael Crow, President Sally Kornbluth explored how universities are preparing the next generation of scientists to lead in America’s rapidly changing technological landscape.
A San Diego location of Altus charter schools, which are designed for students who have fallen behind academically, purchased a pair of robots for $500,000 to help with teaching, career planning and translation.
When Jaiveer Singh talks about robots, he doesn’t begin with spectacle. He begins with infrastructure: the boards inside machines, the software that lets developers see through a robot’s cameras and the engineering required before a robot can leave a demo floor to do something useful. As a robotics software engineer who leads the team behind […]
Flexion Robotics, a startup founded by ex-Nvidia engineers, has a clever way of training robots to do useful work.
Factory-floor applications of the technology could significantly enhance rich-world economies
General Intuition has raised $320 million to scale AI trained on millions of hours of gameplay, betting action data can help AI develop something closer to human intuition.
“Scientific American” showcases the history and future of America’s scientific engine, highlighting promising young scientists and icons at MIT and beyond.
To celebrate its new status as No. 1 in JD Power's initial quality ranking among mainstream automakers, Ford is opening up about the challenges it has faced in recent years, especially around its reliance on automated systems in production and design. It turns out that those automated systems were not as robust as previously assumed, requiring Ford to hire experienced technicians - sometimes bringing back former employees - to correct errors made by the company's robots. In Ford's view, AI is both powerful and prone to pitfalls. Its effectiveness depends entirely on the quality of the data used to train the AI models. In addition, the auto … Read the full story at The Verge.
