Instructing robots to navigate new environments is hard. You possibly can practice them on bodily, real-world knowledge taken from recordings made by people, however that’s scarce, and costly to gather. Digital simulations are a fast, scalable approach to train them to do new issues, however the robots usually fail after they’re pulled out of digital worlds and requested to do the identical duties in the actual one.
Now, there’s probably a greater choice: a brand new system that makes use of generative AI fashions together with a physics simulator to develop digital coaching grounds that extra precisely mirror the bodily world. Robots educated utilizing this methodology labored with the next success charge than these educated utilizing extra conventional strategies throughout real-world exams.
Researchers used the system, known as LucidSim, to coach a robotic canine in parkour, getting it to scramble over a field and climb stairs, regardless of by no means seeing any actual world knowledge. The strategy demonstrates how useful generative AI could possibly be in the case of educating robots to do difficult duties. It additionally raises the chance that we may in the end practice them in fully digital worlds. Learn the total story.
—Rhiannon Williams
Africa’s AI researchers are prepared for takeoff
Once we speak concerning the international race for AI dominance, the dialog usually focuses on tensions between the US and China, and European efforts at regulating the expertise. But it surely’s excessive time we discuss one other participant: Africa.
African AI researchers are forging their very own path, creating instruments that reply the wants of Africans, in their very own languages. Their story isn’t solely one among persistence and innovation, however of preserving cultures and combating to form how AI applied sciences are used on their very own continent. Nonetheless, they face many limitations. Learn the total story.
—Melissa Heikkilä
