The Future of Tesla FSD: A Merge with XAI Grok

Friday - April 26 2024, 19:58 UTC - 1 year ago

Elon Musk has expressed concerns about not having enough control over incorporating new AI ideas into Tesla, but the need for competitive self-driving technology will likely lead Tesla FSD to merge with XAI Grok. This collaboration could lead to advanced capabilities such as chain-of-thought reasoning and personalized driving experiences. The merge will also allow for improved pixel-to-action mapping and give FSD the ability to understand complex scenarios using language. With Tesla's highly mature data pipeline, Grok has the potential to surpass other language models and shape the future of self-driving technology.

In the world of self-driving technology, there is no doubt that Tesla is a pioneer and leader in the field. With their advanced Full Self-Driving (FSD) software, they have been able to achieve impressive feats in autonomous driving. However, the company is not stopping there and is constantly looking for ways to improve and advance their technology. One such way is through a potential merge with XAI Grok, a large multimodal model (LMM) created by John Gibb and Jim Fan.

While Elon Musk has expressed concerns about building too much of his new AI ideas into Tesla without having 25% voting control, the need to make a competitive AI will force Tesla FSD to work with XAI Grok. This collaboration could potentially lead to breakthroughs in self-driving technology, particularly in solving complex edge cases that may arise while driving.

It is likely that FSD v13 will either use an LMM or have one deeply integrated into its software. This will allow for advanced capabilities such as chain-of-thought reasoning and the ability for LMMs to retain conversations and long context windows, making the driving experience more personalized for each driver.

John Gibb and Jim Fan's explanation of the Grok and FSD merge is promising. They believe that Grok 1.5+ has been trained on FSD data and will be deeply integrated into the processing pipeline itself, instead of being a simple bolt-on feature. This will give the car the ability to understand complex scenarios, reason with rules and counterfactuals, and explain its decisions using language.

Another exciting aspect of Grok-1.5V is its potential to improve FSD's pixel-to-action mapping by incorporating language into the process. This could ultimately lead to a better understanding of edge cases and improve the overall performance of FSD.

With Tesla's highly mature data pipeline, there is plenty of potential for Grok to be finetuned and surpass other large language models such as GPT-4V and Gemini in multimodal FSD reasoning. While there have been previous efforts on similar ideas from other companies, Tesla's unparalleled data flywheel has the potential to scale far beyond anything we have seen before.

A video by Nextbigfuture provides more insights into the capabilities of XAI Grok and what it could mean for Tesla FSD. With this merge, the future of Tesla's FSD technology is looking even more promising.