Tesla to introduce FSD v12

 


Tesla is set to introduce end-to-end AI in its Full Self-Driving (FSD) package with the upcoming FSD Beta v12, according to CEO Elon Musk. While FSD Beta already uses artificial intelligence for perception, which helps the vehicle detect its environment, the decision-making and driving input such as steering and braking, rely on regular programming. Previously, Musk stated that AI was not needed for this aspect of FSD. However, in his recent comments hyping the FSD Beta v11.4 update, Musk mentioned that FSD Beta v12 would include "end-to-end AI," from images in to steering, brakes, and acceleration out.

Musk did not provide a specific timeline for the introduction of the end-to-end AI update in FSD Beta v12. However, the company is already expanding the release of FSD Beta v11.4 beyond its internal fleet. Musk has also said that Tesla can achieve "full autonomy" this year, but it is unclear what he means by that at this point.

Tesla's FSD Beta has been in development for over a year, and while it has shown significant improvements in detecting its environment, its decision-making abilities still need improvement. The introduction of end-to-end AI in FSD Beta v12 could address this issue and significantly improve the performance of the autonomous driving system.

The use of AI in FSD Beta has been primarily for perception, which involves the vehicle detecting and interpreting its surroundings through cameras and sensors. With end-to-end AI, the decision-making and driving input would also rely on AI, which could result in faster and more accurate decision-making, particularly in complex driving scenarios.

However, there are concerns about the explainability of AI-based decision-making. Traditional rule-based programming is explainable, which means that any failure can be traced back to the specific rule that was violated. On the other hand, failure in AI-based decision-making is unexplainable, making it difficult to determine the cause of any issues that arise.

Despite the concerns, the adoption of AI in autonomous driving systems is becoming increasingly common, with several companies using deep learning models to improve their performance. End-to-end AI is also seen as the next step in the evolution of autonomous driving systems.

Tesla's move towards end-to-end AI in FSD Beta v12 is a significant shift from its previous approach of relying on regular programming for decision-making. The company's decision to adopt AI for this aspect of autonomous driving highlights the increasing importance of AI in the development of autonomous driving systems.

The success of FSD Beta v12 with end-to-end AI could have far-reaching implications for the future of autonomous driving. If Tesla can achieve full autonomy with the system, it could open up new opportunities for the use of autonomous vehicles in various industries, including transportation and logistics.

However, there are still several challenges that need to be overcome before fully autonomous vehicles become a reality. Regulatory issues, safety concerns, and the need for infrastructure improvements are just some of the challenges that need to be addressed.

Overall, Tesla's adoption of end-to-end AI in FSD Beta v12 is a significant step towards achieving full autonomy. While it is still too early to tell how successful the system will be, the adoption of AI in autonomous driving systems is expected to become increasingly common in the coming years.

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