Tesla’s Supercomputer Will DWARF Everything

Tesla's Supercomputers

💡 Q: What is the scale of Tesla's new supercomputer project?

A: Tesla's Cortex 2 supercomputer at Giga Texas aims for 1 terawatt of compute with 1.4 billion GPUs, making it 3,300x bigger than today's top system.

💡 Q: How does Tesla's compute power compare to Chinese competitors?

A: Tesla's FSD uses 3x more compute than Huawei, Xpeng, Xiaomi, and Li Auto combined, with BYD not yet a significant competitor.

Full Self-Driving (FSD)

💡 Q: What is the significance of Tesla's compute power for FSD?

A: Tesla's compute power is essential for developing FSD that is 20 times better than human driving and training tens of thousands of robo taxis and Optimus robots.

💡 Q: What challenges does Tesla face in localizing FSD in China?

A: Tesla needs local Chinese driving video for training to overcome challenges like learning traffic laws and urban navigation.

💡 Q: How does Tesla's FSD perform in urban areas?

A: Tesla's FSD is capable of unsupervised driving on highways but needs improvement in urban areas to reduce violations like taking the wrong road.

Energy and Future Vision

💡 Q: What is Elon Musk's vision regarding energy usage?

A: Elon Musk envisions progressing from type one to type two on the Kardashev scale using solar energy and type three with space solar power.

Competitors and Technology

💡 Q: How does Tesla's FSD technology differ from competitors?

A: Tesla's FSD relies on neural nets and vision only, unlike competitors like Huawei and Li Auto, which use LAR and sensors.

💡 Q: How limited is BYD's current FSD capability?

A: BYD's FSD is limited to 8,000 out of 1.8 million vehicles sold, with only God's Eye A having the required compute for unsupervised FSD.

Supercomputer Expansion

💡 Q: Where else is Tesla expanding its supercomputing efforts?

A: Tesla plans to build Cortex 3 at Giga Nevada, complementing Cortex 2 at Giga Texas for broader global reach in FSD and Optimus training.

💡 Q: What is the role of Tesla's supercomputers in AI training?

A: Tesla's supercomputers provide necessary engineering resources to overcome training challenges for localizing FSD and Optimus across dozens and hundreds of cities worldwide.

General Insights

💡 Q: What is the status of Tesla's Cortex 2 supercomputer project?

A: The Cortex 2 project is approved and under construction at Giga Texas.

Tesla's Supercomputing Ambitions

🚀 Tesla's Cortex 2 supercomputer at Giga Texas aims for 1 terawatt of compute power, utilizing 1.4 billion GPUs and becoming 3,300x larger than today's top system.

💻 Tesla's current Full Self-Driving (FSD) system already uses 3x more compute power than Huawei, Xpeng, Xiaomi, and Li Auto combined, with BYD not yet considered a competitor.

🌍 Cortex 2 will provide the necessary resources to overcome the large training hurdle of localizing FSD for every city worldwide.

Energy and Civilization Advancement

⚡ Elon Musk's terawatt of compute goal equals all electrical power produced in America today, with 10 Starships potentially producing 1 terawatt of power.

☀️ Global solar energy output is projected to double to 2,000 terawatt hours in just 5 years, enough to power 200 million US homes for a year.

🌌 Musk envisions humanity advancing on the Kardashev scale, aiming to increase Earth's harnessed energy 100-fold, primarily through solar power.

Autonomous Driving Competition

🚗 Tesla's FSD hardware is installed in 3.5 million cars, ready for unsupervised driving, while Chinese competitors have significantly less compute power.

🇨🇳 BYD, despite selling 1.8 million vehicles last year, only equipped 8,000 with their advanced "God's Eye A" system capable of unsupervised FSD.

AI and Compute Power

🧠 Training AI models is 1 billion to 1 more compute-intensive than inference, highlighting the importance of Cortex 2 for Tesla's FSD and Optimus robots.

🌐 Cortex 2 will enable the aggressive scale-out of FSD and Optimus to dozens and hundreds of cities globally.

Future Energy Goals

🔋 Elon Musk aims to harness the entire sun's energy as a Type II civilization on the Kardashev scale, with solar energy being the main driver of Earth's energy future.

🛰️ The vision includes utilizing space-based solar power to capture and transmit energy back to Earth, potentially revolutionizing global energy production.

• 00:00 🚀 Tesla is developing Cortex 2 at Giga Texas to achieve terawatt-level supercomputing power, crucial for advancing its self-driving technology and AI-driven robotics.
  • Tesla is advancing its supercomputing capabilities with the approval of Cortex 2 at Giga Texas, aiming for a terawatt of compute power that would vastly exceed current supercomputers and enhance its full self-driving technology.
  • Cortex 2.0 is confirmed to be located at a new construction site in Texas, with permits obtained for further development by 2025.
  • Tesla is significantly expanding its computing capabilities to lead in AI-driven robotics, enhancing the development of robo-taxis and Optimus robots while aiming for superior safety and functionality compared to human drivers.
  • Tesla faces significant localization training challenges for its Full Self-Driving (FSD) rollout across numerous cities, requiring substantial engineering resources to address both software and infrastructure issues.
  • Tesla's future relies on advancements in compute power for successful self-driving technology, robo taxis, and the Optimus robot, which are crucial for the company's growth and stock performance.
  • The speaker apologizes for complicating the editing process.
• 08:02 ⚡ Tesla's superior computing power, aiming for a terawatt for full self-driving, positions it ahead of competitors, while also planning to enter the solar market amidst challenges in electricity generation.
  • Tesla's advantage in solving the robo-taxi challenge lies in its superior computing power compared to competitors in artificial intelligence development.
  • Tesla's focus on advanced computing for driving intelligence gives it a significant competitive advantage over Chinese automakers relying on more sensors.
  • Tesla aims to achieve a terawatt of compute power for its full self-driving technology, comparable to the total electrical output of the U.S.
  • Tesla is expected to enter the solar panel market as part of Elon Musk's energy generation strategy.
  • A terawatt of computing power equals 1.4 billion H100 GPUs, which is 3,300 times the capacity of the largest current supercomputer.
  • Generating a terawatt of electricity for advanced computing poses significant challenges due to current grid limitations, necessitating innovative solutions like on-site power generation.
• 15:09 ⚡ Elon Musk plans to build a terawatt supercomputer with 1.4 billion GPUs to revolutionize AI and energy storage for renewable sources.
  • To utilize solar power effectively for 24/7 use, it's essential to store energy generated during limited sunlight hours.
  • Scaling up battery production is essential to effectively store and utilize renewable energy from sources like solar and wind, ensuring power availability when needed.
  • Elon Musk aims to create a terawatt supercomputer using 1.4 billion H100 GPUs, leveraging exponential growth in AI technology and advanced chips to achieve unprecedented computing power.
  • The plan involves scaling from a million GPU cluster to a trillion GPU cluster through exponential technological advancements.
• 19:40 ⚡ Elon Musk envisions a future powered by abundant solar energy, positioning Tesla to lead in AI and robotics advancements despite current challenges in full self-driving technology.
  • Training AI models requires significantly more computational power than inference, making advancements in training crucial for efficiency.
  • Elon Musk predicts that solar energy will be the primary source of a 100-fold increase in energy harnessed on Earth, with potential for even greater advancements as humanity progresses on the Kardashev scale.
  • Humanity currently utilizes about 70% of the solar energy that reaches Earth, with potential to significantly increase energy consumption in the coming decades as we progress towards a Kardashev Type I civilization.
  • Elon Musk envisions a future where abundant energy powers advanced AI and robotics, drawing parallels to his ambitious past projects like Gigafactory and Starship.
  • Elon Musk is re-emerging with ambitious AI and full self-driving projects, positioning Tesla ahead of competitors, particularly in China, who are shifting focus to neural networks and vision-based systems.
  • FSD struggles with traffic rule compliance but excels in driving technology.
• 27:50 🚗 Tesla's full self-driving technology excels in safety and compute power, outpacing competitors despite challenges with urban regulations and local traffic rules.
  • Tesla's full self-driving technology demonstrates strong safety on highways but struggles with urban regulations and specific local driving conditions.
  • Tesla's full self-driving technology is performing well but faces challenges in learning Chinese traffic rules due to restrictions on local training data, though improvements are expected over time.
  • Tesla's core technology, particularly its FSD end-to-end model, remains superior in intelligence and compute requirements compared to Chinese competitors' autonomous driving systems.
  • Tesla's compute power significantly surpasses that of competitors like Huawei, Xiaomi, and Leo Auto, enabling advanced training for their vehicles.
  • BYD's FSD capabilities are limited, with only 8,000 out of 1.8 million vehicles equipped for unsupervised driving, while Tesla has 3.5 million cars ready for the same feature.
• 33:24 🚗 Tesla's lead in autonomous vehicle technology outpaces competitors like Waymo, which struggles with outdated systems and operational challenges.
  • Chinese companies often face lower reporting and compliance standards, leading to inflated perceptions of their capabilities compared to U.S. companies.
  • Tesla's advancements in autonomous vehicle technology position it ahead of competitors like Waymo, which struggles with outdated systems and lacks the necessary intelligence to compete effectively.
  • Waymo is testing its robo taxi service in Boston, facing challenges with mapping and routing, as demonstrated by a car getting stuck in circles.
• 36:35 🚗 Tesla's supercomputer aims to enhance self-driving intelligence, addressing current limitations in navigation and decision-making that require human intervention.
  • Remote operators may need to intervene in Tesla situations, similar to how Waymo addressed similar challenges.
  • Intelligence, not just advanced sensors, is crucial for self-driving cars, as demonstrated by the need for software updates after accidents, highlighting the importance of experience and deep learning in driving models.
  • Zoox's car collided with another vehicle because it failed to anticipate the other car's sudden stop, highlighting limitations in its understanding of the driving environment.
  • Autonomous driving systems struggle to navigate effectively due to underpowered computers and inflexible technology, despite attempts to enhance their perception of the environment.
• 40:49 🚗 Tesla's advanced AI and upcoming terawatt computing power will revolutionize self-driving technology, surpassing competitors by better understanding context.
  • Handling complex code requires writing numerous scenarios to ensure all rules align and addressing conflicts at their intersections.
  • Tesla's advanced AI and powerful computing enable a more human-like driving experience compared to traditional systems.
  • Tesla's self-driving technology outperforms Chinese competitors by understanding context better, and with the upcoming terawatt of compute power, its future capabilities are expected to be unprecedented.

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