Foxconn and Nvidia are building 'AI factories' to accelerate self-driving cars | TechCrunch
Foxconn and Nvidia are building 'AI factories' to accelerate self-driving cars | TechCrunch
Can they build factories to brake too?
So can someone explain what an AI factory is, from an engineering perspective? The fact there's competition to build them suggests it's not just a marketing term, but I can't find a clear answer with a quick search.
It's just a marketing term.
Yep, just looked into Dojo. They don't use the same term at all. -1 to the journalist for making it sound like an industry standard thing.
Uh oh, if Foxconn is in charge of an AI factory then we're sure to see our first AI suicide attempt in no time.
First? Didn't a police robot roll into a pool?
🤖 I'm a bot that provides automatic summaries for articles: ::: spoiler Click here to see the summary Nvidia and Foxconn are working together to build so-called “AI factories,” a new class of data centers that promise to provide supercomputing powers to accelerate the development of self-driving cars, autonomous machines and industrial robots.
The AI factory tie-up builds off a partnership between Nvidia and Foxconn announced in January to develop autonomous vehicle platforms.
On Tuesday, Foxconn also committed to manufacturing ECUs with Drive Thor, Nvidia’s next-gen SoC, after production starts in 2025.
As part of that partnership, Foxconn — which has been steadily unveiling off-the-shelf EV platforms for automakers to purchase — said the vehicles it makes as a contract manufacturer will be built with Nvidia’s Drive Hyperion 9 platform, which includes not only Drive Thor, but also a suite of sensors like cameras, radar, lidar and ultrasonic that are necessary for self-driving capabilities.
Because these AI factories are essentially rivals to Tesla’s Dojo supercomputer, which the Elon Musk-owned automaker started production on over the summer.
“This is a factory that takes data input and produces intelligence as an output,” said Huang, as Liu nodded his assent.
Saved 68% of original text. :::
