Roboticists imagine that, utilizing new AI strategies, they will unlock extra succesful robots that may transfer freely via unfamiliar environments and deal with challenges they’ve by no means seen earlier than.
However one thing is standing in the best way: lack of entry to the varieties of knowledge used to coach robots to allow them to work together with the bodily world. It’s far tougher to come back by than the info used to coach essentially the most superior AI fashions, and that shortage is among the important issues presently holding progress in robotics again.
Because of this, main firms and labs are in fierce competitors to search out new and higher methods to assemble the info they want. It’s led them down unusual paths, like utilizing robotic arms to flip pancakes for hours on finish. They usually’re working into the identical types of privateness, ethics, and copyright points as their counterparts on this planet of AI. Learn the complete story.
—James O’Donnell
My deepfake reveals how helpful our knowledge is within the age of AI
—Melissa Heikkilä
Deepfakes are getting good. Like, actually good. Earlier this month I went to a studio in East London to get myself digitally cloned by the AI video startup Synthesia. They made a hyperrealistic deepfake that regarded and sounded identical to me, with real looking intonation. The tip outcome was mind-blowing. It may simply idiot somebody who doesn’t know me properly.
Synthesia has managed to create AI avatars which are remarkably humanlike after just one yr of tinkering with the newest technology of generative AI. It’s equally thrilling and daunting fascinated about the place this expertise goes. However they increase a giant query: What occurs to our knowledge as soon as we submit it to AI firms? Learn the complete story.
This story is from The Algorithm, our weekly AI publication. Enroll to obtain it in your inbox each Monday.
