AI-powered cars are, in a strange way, here and not here. The technology works--millions of miles have been traversed by true self-driving vehicles in the past decade--and it shows up in places like Tesla. Most of us don't realize just how close AI is to becoming the future of driving. The price of AI modeling software and hardware, as well as the problem of implementation, make mainstream adoption move much slower than some of us would want. Although most of us think of AI-powered cars as using massive computers inside relatively complex vehicles, that's not always the case.

The Indy Autonomous Challenge has revealed the vehicle participating universities will have to program and race in October 2021: the Dallara IL-15 racecar. IAC has made the announcement during its press conference for CES 2021, where it also hosted discussions about the commercialization of autonomous vehicles and technology in motorsports. The competition, which has a $1.5 million prize purse, challenges universities to build AI algorithms that can power an IL-15 that has been fitted with hardware and controls that enable automation. Back in 2020, IAC announced that 37 universities from 11 countries registered to compete, with teams being composed of members with varying expertise. There are undergraduate and graduate student participants, as well as faculty and industry experts in AI, machine learning and robotics.

For more than a century, the life of a vehicle has begun in the factory. To ensure a smooth transition to the automotive life cycle of the future, manufacturers must carefully design, build and run datacenters optimized for training artificial intelligence at scale. Autonomous vehicles rely on deep neural networks to handle functions that a human driver would typically be responsible for. These algorithms can perceive the world around the car, plan the vehicle's motion and actuate that path. Before they can safely run in the car, deep neural networks must be rigorously trained in the datacenter, where they are shown millions of hours of driving data, enabling an autonomous vehicle to recognize and react to scenarios on its own.

NVIDIA isn't just content with making an artificial intelligence platform for cars and waiting for someone to use it. The company has unveiled a partnership with Audi that has the two working on AI-powered cars. You'll first see the fruits of their labor in an experimental Q7 SUV that has learned to drive itself in three days (it'll be putting around CES' Gold Lot), but their plans are much bigger. Ultimately, their goal is to have Audis with Level 4 autonomy (that is, full autonomy outside of extreme situations) on roads by 2020. That's only three years away, which is fairly aggressive compared to promises made by other German automakers.

NVIDIA isn't just content with making an artificial intelligence platform for cars and waiting for someone to use it. The company has unveiled a partnership with Audi that has the two working on AI-powered cars. You'll first see the fruits of their labor in an experimental Q7 SUV that has learned to drive itself in three days (it'll be putting around CES' Gold Lot), but their plans are much bigger. Ultimately, their goal is to have Audis with Level 4 autonomy (that is, full autonomy outside of extreme situations) on roads by 2020 -- that's only 3 years away, which is fairly aggressive compared to other German automakers. There's still a lot we don't know.