Teaching robots to navigate new environments is hard. You can prepare them on bodily, real-world knowledge taken from recordings made by people, however that’s scarce, and costly to gather. Digital simulations are a speedy, 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 probably a greater possibility: 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 skilled utilizing this methodology labored with the next success price than these skilled 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 method demonstrates how useful generative AI might be with regards to instructing robots to do difficult duties. It additionally raises the likelihood that we might in the end prepare them in totally digital worlds. Read the complete story.
—Rhiannon Williams
Africa’s AI researchers are prepared for takeoff
When 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’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 is just not solely considered one of persistence and innovation, however of preserving cultures and combating to form how AI applied sciences are used on their very own continent. However, they face many limitations. Read the complete story.
—Melissa Heikkilä