The Future of Automobiles: Tesla’s New D1 Microchip

NVIDIA & Tesla

Currently, NVIDIA is the leading GPU and AI microchip manufacturers. However, since 2019 NVIDIA has not received any business from Tesla and will not in future. While Tesla is simply an automotive company, its processes are far from simple as its aim is to be seen as a tech giant. Tesla’s CEO and Techno-King (Official Title), Elon Musk, wants to take the company in the direction of vertical integration.

Elon Musk, CEO and Techno-King of Tesla

Tesla wishes to own and supervise all aspects of the AI automotive manufacturing process on-site at their Gigafactories. This includes the development, manufacturing, and integration of microchips. An impressive feat that is made even more impressive with the move from NVIDIA hardware to the addition of Tesla’s new D1 AI microchip. Tesla is also now manufacturing the chips used in their vehicles’ sensors.

Tesla D1 Microchip

Tesla D1 Microchip
Tesla D1 Microchip

The D1 chip has a large neural network inside the vehicle that uses 8 external sensors to maintain spatial awareness. Tesla has dubbed its massive neural network “The Transformer”. This network is shared amongst all tesla vehicles for efficient AI training. In training, developers must teach the chip’s AI to learn as many scenarios as possible before it is integrated into the vehicle.

AI Training

Many other large companies like Amazon, Microsoft, and Google are also seeing the benefits of developing their own machine learning microchips. However, Tesla goes above and beyond its competitors when it comes to AI training. Video and sensor data in tesla cars are fed back to a central data collection. From there, employees will train the AI by finding objects unfamiliar to the software and labeling them accordingly. Investments in neural networks and cloud computing can cost millions of dollars. But in the long run, it will be worth it for Tesla.

Up Next: Truck Platooning

With processors like Tesla’s D1 chip, the possibilities of AI applications expand and become more accessible. In our next article, we will elaborate on these applications in the form of truck platooning.

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