An estimated 20% of every dollar spent on manufacturing is wasted, totaling up to $8 trillion a year, more than the entire annual budget for the U.S. federal government. While industries like healthcare and finance have been rapidly transformed by digital technologies, manufacturing has relied on traditional processes that lead to costly errors, product delays, and an inefficient use of engineers’ time.
Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence (AI) model inspired by neural oscillations in the brain, with the goal of significantly advancing how machine learning algorithms handle long sequences of data.
MIT researchers have created a periodic table that shows how more than 20 classical machine-learning algorithms are connected. The new framework sheds light on how scientists could fuse strategies from different methods to improve existing AI models or come up with new ones.
Essential for many industries ranging from Hollywood computer-generated imagery to product design, 3D modeling tools often use text or image prompts to dictate different aspects of visual appearance, like color and form. As much as this makes sense as a first point of contact, these systems are still limited in their realism due to their neglect of something central to the human experience: touch.
