Elon Musk’s Tesla has recently unveiled an innovative AI system that could revolutionize autonomous driving technology. The new system, known as FSD 12, utilizes a neural network that learns from billions of video frames depicting human driving behavior.
Rather than relying on conventional rules and codes, the FSD 12 system imitates the driving behaviors observed in millions of training examples. This groundbreaking approach aims to enhance the performance of self-driving vehicles by enabling them to navigate real-world scenarios more smoothly and reliably.
By utilizing a dataset of millions of videos and mimicking the behaviors of what are considered good drivers, the FSD 12 system can generalize effectively in unfamiliar situations. This means that the system can autonomously discern the most appropriate driving actions based on its training, rather than being constrained by predefined instructions.
Despite the potential benefits of this end-to-end approach, concerns have been raised about the system imitating potentially risky human driving behaviors, such as rolling through stop signs rather than coming to a complete halt. The National Highway Safety Board is currently investigating whether such behaviors are acceptable for self-driving cars.
While the technology behind autonomous vehicles continues to advance, some industry experts believe that current driverless technology is still in the early stages of development. Companies like Wayve, Waabi, and Ghost are focusing on neural networks to create more competent and cost-effective solutions, with hopes of surpassing current market leaders in the autonomous vehicle industry.
Investors have poured billions of dollars into developing autonomous vehicles, with the cost rivaling NASA’s moon landing mission. As self-driving cars face scrutiny for high-profile errors, the race to create safer and more reliable autonomous driving technology continues to intensify.
