Tesla FSD v12 Rollout - FIRST THOUGHTS! (Ep. 752)

Summary

The video discusses Tesla's new FSD software version 12, which completely shifts to a neural net approach for full self-driving capabilities instead of relying on rules-based coding. Early testing results from a non-Tesla employee show impressive performance, but also times when FSD gave up control due to low confidence. The key challenge now is improving FSD through massive amounts of data, compute power, and enhancements so it rarely lacks confidence to handle complex situations. If Tesla can achieve major leaps in FSD capabilities this year, it would be an exciting advancement towards unsupervised autonomous driving.

Takeaways

• 😲 Tesla rolled out FSD version 12 software to select non-employees, marking a major milestone
• 🧠 FSD v12 shifts from rules-based to neural net end-to-end approach for entire planning process
• 🚗 This is monumental and ambitious, as driving is very complex
• 🤔 FSD v12 needs to drive as well or better than prior versions with guardrails to be safe
• 👍 Early FSD v12 results are promising enough for limited external testing
• ❓ Current weaknesses seem to be lower confidence in more complex situations
• 🌄 Goal is to improve confidence across most driving scenarios
• 📈 Rapid improvements expected as more data and compute is added
• 🔬 FSD team laser focused on data, compute, model improvements this year
• 😃 Exciting to see how fast FSD v12 abilities advance throughout 2022

Q & A

What is Tesla's FSD version 12?

FSD version 12 is Tesla's upcoming rewrite of their full self-driving software. It shifts their approach from rule-based coding to an end-to-end neural net.

Why did Tesla previously rely on rule-based coding for FSD?

The rules provided guard rails and instructions on how to drive safely. Without the rules, the car could potentially do something dangerous.

What are the challenges in moving from rule-based to neural nets?

The neural nets need to handle unguarded situations and new scenarios without thousands of hardcoded rules. They need to drive better and safer than with the rules.

When did Tesla decide to go all in on the end-to-end approach?

Around spring last year, after early testing showed promising results with the end-to-end neural net approach.

Why does FSD version 12 need massive amounts of data and compute?

To train the neural nets to handle driving safely without relying on hardcoded rules, which requires analyzing millions of video clips.

What are some initial weaknesses observed in FSD version 12?

It sometimes gives up with red hands when confidence drops below a threshold, rather than trying to push through low confidence situations.

How can Tesla improve FSD version 12?

By feeding more data to improve the neural nets, adding more compute power, and iterating to increase driving ability and confidence.

What is the goal for FSD version 12 this year?

To improve it dramatically, so it rarely gives up control and can confidently handle complex driving situations.

When could Tesla potentially reach full self-driving capabilities?

It's unclear, but rapid improvements this year could demonstrate the path and timeline to unsupervised, full self-driving.

Why is it exciting that FSD version 12 was given to non-employees?

It shows Tesla has enough confidence in the initial version to let people test it, despite still needing major improvements.