BG2Pod with Brad Gerstner and Bill Gurley Ep4. Tesla FSD 12, Imitation Learning Models, The Open vs. Closed AI Model Battle, Delaware’s anti Elon ruling, & a Market Update
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Mar 7, 2024 The conversation kicks off with a dive into the complexities of venture capital and the risk landscape in Delaware. Tesla’s Full Self-Driving V12 is discussed, focusing on its imitation learning techniques and the shift towards neural network models for enhanced driving autonomy. The podcast also highlights the fierce competition between open and closed AI models, emphasizing transparency and regulatory challenges. Finally, recent court rulings affect corporate governance, along with a macro market outlook that scrutinizes major tech companies and their innovation strategies.
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Tesla's Data Collection Strategy
- Tesla collects vast driving data but processes it on the edge, only uploading relevant outlier moments.
- This allows them to focus on unusual driving scenarios and improve the model's handling of corner cases.
Tesla's Fleet Size Advantage
- Tesla's large fleet size (5 million cars) gives them a significant data advantage in self-driving.
- Competitors like Waymo, with smaller fleets, struggle to collect enough data, especially for rare events.
FSD Adoption and Profitability
- Wider FSD adoption at a lower price point could significantly increase Tesla's profitability.
- Increased usage generates valuable data for further model improvement, creating a positive feedback loop.