Tesla Is Building Its Own AI Chips For Self-Driving Cars (techcrunch.com)

Yesterday, during his quarterly earnings call, Tesla CEO Elon Musk revealed a new piece of hardware that the company is working on to perform all the calculations required to advance the self-driving capabilities of its vehicles. The specialized chip, known as "Hardware 3," will be "swapped into the Model S, X, and 3," reports TechCrunch. From the report: Tesla has thus far relied on Nvidia's Drive platform. So why switch now? By building things in-house, Tesla say it's able to focus on its own needs for the sake of efficiency. "We had the benefit [...] of knowing what our neural networks look like, and what they'll look like in the future," said Pete Bannon, director of the Hardware 3 project. Bannon also noted that the hardware upgrade should start rolling out next year. "The key," adds Elon "is to be able to run the neural network at a fundamental, bare metal level. You have to do these calculations in the circuit itself, not in some sort of emulation mode, which is how a GPU or CPU would operate. You want to do a massive amount of [calculations] with the memory right there." The final outcome, according to Elon, is pretty dramatic: He says that whereas Tesla's computer vision software running on Nvidia's hardware was handling about 200 frames per second, its specialized chip is able to crunch out 2,000 frames per second "with full redundancy and failover." Plus, as AI analyst James Wang points out, it gives Tesla more control over its own future.

Comments

Re:Building proprietary silicon could be dangerous

[RhettLivingston]

Every NN is proprietary, and that is where the functionality to worry about is at. The performance on "edge cases" in driving is directly related to how much compute power you can throw at it. Tesla is multiplying its compute power. The edge cases will improve. Staying with the general purpose GPU instead of true NN hardware will guarantee continued unhandled edge cases.

This HW is undoubtedly also more energy efficient. That is the real key. They could stack on more boards, but these units are already consuming a significant amount of the vehicle's energy. The trick is to get more compute power with the same or less energy. NN specific HW is going to be a requirement to have that happen.

Everyone in the industry has known that GPUs will not be used past the first generation or so. They are development HW. Someone will eventually come up with a general purpose NPU that will win the market, but it hasn't happened yet - mostly because NN implementations haven't settled.

Re:To what end?

[TomGreenhaw]

I bet that this allows them to have more cameras. 2000 fps for one camera could be 250fps for 8 cameras. it could also be used for much higher resolution cameras that have fisheye or insect like lenses.