Tesla's FSD V 12 enables a major shift from rule-driven logic to an end-to-end neural network architecture. Previously, Tesla relied on more than 300,000 lines of C code to "fence" FSD and give driving instructions, while version 12 uses a method of allowing neural network AI to autonomously decide how to drive based on the real-time environment
Now Tesla's FSD has ushered in the blessing of Musk's xAI company's large model Grok 1.5 V, and the future of FSD is expected to be completely reshaped
The core of Grok-1.5V (xAI vision model) lies in the use of a "chain of thought" language that will help cars break down complex scenarios, use rules and counterfacts to reason, and explain their decisions, elevating the "pixel-to-action" mapping of autonomous driving to a new model of "pixel-to-language-to-action". This innovative approach not only enhances the perception and reasoning capabilities of autonomous driving systems, but also allows them to better explain their decision-making processes
Tesla's AI team's strengths in data accumulation and model training are clear. By annotating high-quality "human interpretation traces" on a large scale through Tesla's own data pipeline, Grok-1.5V can surpass existing language models and perform more nuanced multimodal inference in complex scenarios. This will not only help solve the "edge case" of autonomous driving, but also make the system's decision-making more transparent and credible
"Traces of human interpretation" refers to the manual annotation of a large number of autonomous driving scenarios with detailed textual descriptions to record how human experts analyze and solve these complex scenarios
That is, Tesla collects a large amount of video data on autonomous driving, and then invites human experts to take a closer look at the data and describe in words how they understand and process these scenarios. These rich textual explanations constitute "traces of artificial interpretation"
By accumulating these human-annotated explanatory data, Tesla's Grok-1.5V system can learn human reasoning and improve its perception and decision-making capabilities in complex scenarios. This approach is considered to have more potential than relying solely on machine learning to break through the "edge case" of autonomous driving
It's worth mentioning that the Grok-1.5V didn't happen overnight. Wayve had previously tried a similar LINGO-1 approach, but there were challenges in scaling. Tesla's strength lies in its powerful data flywheel, which is able to continuously expand training data and continuously improve the performance and reliability of the system
As Elon Musk explains, both synthetic and real-world data are invaluable resources in the field of autonomous driving. Tesla, with its large user base and excellent data collection capabilities, is building an unparalleled data ecosystem. This has given a strong impetus to the development of the Grok-1.5V, which is expected to be a key technology to usher in a new era of autonomous driving
By introducing language into the decision-making process of autonomous driving, Grok-1.5V can help vehicles better understand complex scenarios, apply rules and counterfactual reasoning, and provide clear explanations for their actions. This not only improves the safety and reliability of the system, but also points the way for the future development of autonomous driving technology
At the same time, the success of the Grok-1.5V could have broader implications. Language-driven reasoning models are expected to be applied in other fields, such as improving the interaction ability of robots, enhancing the interpretability of medical diagnoses, and optimizing the decision-making process for new drug development
epilogue
Tesla's FSD v13 is likely to be trained on the language "human interpretation traces". It can not only improve the performance of autonomous driving systems, but also bring new possibilities to application scenarios such as human-machine collaboration and intelligent decision-making. Looking forward to the future development and application of this technology, and how it will reshape our mobility and lifestyle.