Tesla’s Staggering AI Ambitions

TL;DR

Arc Invest predicts Tesla's stock value to reach $2,000 per share in the next five years, driven by its expected 100 exaflops compute capacity and unrivaled data advantage.

Transcript

well our price target for Tesla over the next five years is that we think it has an expected value of roughly two thousand dollars per share and they're showing that by October 2024 they hope that their compute will reach 100 exaflops which is 20 times more than the 4.5 exoplops uh that it disclosed during AI day last September and really to put th... Read More

Key Insights

• 🧘 Tesla's expected compute capacity of 100 exaflops by 2024 positions the company as one of the leaders in AI computing and enables significant advancements in autonomous driving technology.
• 🤳 The volume and quality of data collected by Tesla's fleet give it a competitive edge over rivals in developing and improving its self-driving technology.
• 💻 Tesla's compute capacity and data advantage have implications beyond autonomous driving, as they can be leveraged in various AI applications.
• 🚦 The increase in compute capacity aligns with Tesla's vertical integration strategy, reducing dependency on external suppliers.
• 💻 Tesla's stock value is predicted to reach $2,000 per share within the next five years if the company continues to harness its compute capacity and data advantage effectively.
• 💻 The rapid growth of Tesla's compute capacity and data advantage indicates its seriousness in pursuing ambitious growth and dominance in the EV and AI industries.
• 🌍 Competitors like Cruise and Waymo may struggle to catch up with Tesla's compute capacity and data advantage, given the asymmetry in data collection and real-world testing.

Questions & Answers

Q: Why does Tesla need such a significant increase in compute capacity?

Tesla's compute capacity is vital for training and improving its full self-driving software. With a larger fleet of vehicles collecting real-world data, Tesla can address corner cases and novel situations to enhance the capabilities of its autonomous driving technology.

Q: How does Tesla's data advantage compare to competitors like Cruise and Waymo?

Tesla collects data at a much faster rate, accumulating one million real-world miles every 14 hours. In comparison, Cruise takes three months, and Waymo takes two and a half years to collect the same amount. This data advantage allows Tesla to address a broader range of scenarios and improve its self-driving capabilities.

Q: What are the implications of Tesla's compute capacity and data advantage?

Tesla's compute capacity and data advantage position the company ahead of its competitors in terms of autonomous driving technology. It opens doors to future opportunities, such as licensing its software and expanding into other AI-driven industries. Furthermore, it showcases Tesla's commitment to vertical integration and its ambitious growth plans.

Q: Will Tesla continue working with Nvidia for compute capacity?

Tesla is likely to supplement its compute capacity with in-house solutions, similar to its strategy with battery production. While Tesla may still work with Nvidia, the company aims to have additional capacity to avoid being dependent on external suppliers amidst the high demand for AI computing.

Summary & Key Takeaways

• Tesla plans to increase its compute capacity to 100 exaflops by October 2024, which is 20 times more than its previous capacity. This is seen as a crucial factor in advancing Tesla's full self-driving technology.

• Tesla's data advantage is unmatched, collecting one million real-world miles every 14 hours, surpassing the data collection of competitors like Cruise and Waymo.

• The compute capacity and data advantage will not only benefit Tesla's full self-driving technology but also expand into other areas of AI, such as computer vision for robots and optimizing various operations.