Educating robots to navigate new environments is hard. You’ll be able to 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 strategy to educate them to do new issues, however the robots typically fail after they’re pulled out of digital worlds and requested to do the identical duties in the true one.
Now, there’s probably a greater possibility: a brand new system that makes use of generative AI fashions along side a physics simulator to develop digital coaching grounds that extra precisely mirror the bodily world. Robots skilled utilizing this methodology labored with a better success fee than these skilled utilizing extra conventional methods 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 might be with regards to educating robots to do difficult duties. It additionally raises the likelihood that we may in the end practice them in fully digital worlds. Read the full story.
—Rhiannon Williams
Africa’s AI researchers are prepared for takeoff
After we discuss in regards to the world race for AI dominance, the dialog typically focuses on tensions between the US and China, and European efforts at regulating the expertise. However it’s excessive time we speak about one other participant: Africa.
African AI researchers are forging their very own path, growing 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 preventing to form how AI applied sciences are used on their very own continent. Nevertheless, they face many obstacles. Read the full story.
—Melissa Heikkilä
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