Educating robots to navigate new environments is hard. You may 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 technique 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 true one.
Now, there’s doubtlessly a greater choice: a brand new system that makes use of generative AI fashions along 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 price than these educated utilizing extra conventional strategies throughout real-world exams.
Researchers used the system, referred to 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 method demonstrates how useful generative AI might be in relation to educating robots to do difficult duties. It additionally raises the likelihood that we might in the end practice them in totally digital worlds. Learn the total story.
—Rhiannon Williams
Africa’s AI researchers are prepared for takeoff
Once we discuss 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, growing instruments that reply the wants of Africans, in their very own languages. Their story will not be solely one in all persistence and innovation, however of preserving cultures and preventing to form how AI applied sciences are used on their very own continent. Nonetheless, they face many obstacles. Learn the total story.
—Melissa Heikkilä
Educating robots to navigate new environments is hard. You may 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 technique 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 true one.
Now, there’s doubtlessly a greater choice: a brand new system that makes use of generative AI fashions along 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 price than these educated utilizing extra conventional strategies throughout real-world exams.
Researchers used the system, referred to 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 method demonstrates how useful generative AI might be in relation to educating robots to do difficult duties. It additionally raises the likelihood that we might in the end practice them in totally digital worlds. Learn the total story.
—Rhiannon Williams
Africa’s AI researchers are prepared for takeoff
Once we discuss 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, growing instruments that reply the wants of Africans, in their very own languages. Their story will not be solely one in all persistence and innovation, however of preserving cultures and preventing to form how AI applied sciences are used on their very own continent. Nonetheless, they face many obstacles. Learn the total story.
—Melissa Heikkilä
