How Tesla Integrates Machine Learning into Its Self-Driving Cars

The automotive industry is moving at an enormous pace, with technological outbreaks occuring rapidly. At the front of these technological outbreaks, however, is Tesla and their advancements in their FSD (full-self driving) department. But what is artificial intelligence built off of? Data. Today I will be talking about Tesla and how they utilize machine learning and artificial intelligence to improve their cars’ self-driving capabilities.

Tesla’s clear goal is a future where all cars are autonomous and they plan to accomplish this through their cars’ self-driving capabilities. To begin, the cars are equipped with sensors and cameras. Working with software, these cameras are able to see and identify everything around it. Through the data that these cameras have collected, Tesla has developed, and continues to improve, a system that runs their self-driving cars. This self-driving capability is built through artificial intelligence. Artificial intelligence, however, has a couple of subsets that need to be understood before we move onto the actual big picture of artificial intelligence. The fundamental subset being deep learning.

Essentially, the internet has large sets of unorganized data that are essentially useless. It’s too random to have any use for Tesla. What deep learning does, is it takes all this unstructured and useless data and it organizes it. It automatically identifies the patterns and the specific features in the data in order to create models. It’s almost like a chef creating a complex dish to serve. He’s given all these seemingly random ingredients to serve that aren’t so significant on their own. But by identifying the pepper that has a spicy feature to it and the lime that has sourness to it, he is able to use all these ingredients to create a dish that tastes good. This is similar to what Tesla deep learning is. Tesla’s deep learning model essentially obtains all the different features of the roads like other cars, pedestrians, traffic lights, stop signs, etc. The model then uses deep learning to identify and learn all these obstacles. It is constantly evaluating, learning, and improving in order to make self-driving work.

Although deep learning is a lot more complex than this, this is the basic idea for how Tesla utilizes it in order to operate its self-driving cars. Through deep learning, Tesla’s self-driving models are able to constantly improve in order to make self-driving safer and more viable in the future.