Featured image: MIT Technologies

MIT Technologies presents 35 brilliant young entrepreneurs, inventors, visionaries, humanitarians and pioneers who are working to make the world a better place. The list '35 Innovators Under 35' represents young people who are looking for ways to use technology to help people. Andrej Karpathy entered this list, in the nomination pioneer.

Andrej Karpathy is the director of artificial intelligence and Autopilot Vision at Tesla, specializing in deep learning and image recognition and understanding. Using his achievements, Tesla goes a different way than most other automakers.

Many computer scientists have been trying to teach computers to see for decades. But none of them was as successful as Karpathy. He developed an approach to deep neural networks that allows machines to make sense of what is happening in images.

As a graduate student at Stanford, Karpathy extended techniques for building what are known as convolutional neural networks (CNNs) —systems that broadly mimic the neuron structure in the visual cortex. (In 2015 he also designed and was the primary instructor for the first deep-learning class at Stanford.)

By combining CNNs with other deep-learning approaches, he created a system that was not just better at recognizing individual items in images (say, a dog or a person), but capable of seeing an entire scene full of objects — multiple dogs and people interacting with each other — and effectively building a story of what was happening in it and what might happen next.

Karpathy became a member of the Tesla team in 2017, now he oversees neural networks for the cars’ Autopilot feature. Tesla Autopilot is qualitatively different from others. Typically, cars with automatic control scan the environment using expensive laser rangefinders, create a virtual map, and then use the AI ​​to decide what to do. Tesla uses traditional cameras instead.

Source: Matroid/YouTube

Karpathy method lets the car spot objects in the road as a human driver would, and it can take in the entire scene (cars, people, intersections, stop signs, and more) and — if it works as intended — instantly infer what's taking place. Doing so requires nearly 50 neural networks to constantly process data coming in as the more than a million cars in the fleet look and learn.

Karpathy is a bright representative of the talented people who make up the team that seeks to change the world for the better - the Tesla team.

H/T Whole Mars / Twitter