Tesla is investing heavily in AI, with a $1 billion budget this year, giving them a significant advantage in building AI for self-driving and robo taxis, and potentially reworking energy grid models
Questions to inspire discussion
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How much is Tesla investing in AI?
—Tesla is investing over $1 billion in AI this year, potentially even more than reported.
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What advantage does Tesla have in AI?
—Tesla has a significant advantage in AI spending and development, giving them a strong position in building AI for self-driving and robo taxis.
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What is the importance of compute power in AI?
—Compute power is crucial for AI development, and Tesla is making significant investments in this area to stay ahead in the industry.
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How is Tesla using real-world data for AI?
—Tesla is using a network of cameras on their vehicles to collect real-world data for training their AI to drive like a human.
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What is the potential impact of Tesla's AI spending?
—Tesla's AI spending has the potential to rework energy grid models and lead to significant advancements in AI technology.
Key Insights
- 🤖 Tesla's AI spend is way more than people think, with 350,000 h100 gpus, 10 times more than other companies.
- 🤖 Tesla's AI supercomputer is allocated to hardcore machine learning workloads for the development of intelligence, giving them more bang for their Buck compared to competitors.
- 🚗 Every car that Tesla has shipped since 2019 has one of the most capable inference computers on the planet, trained by the drivers, giving them a significant advantage in AI development.
- 🔍 The ability to use a 5 million vehicle search engine to gather real-world data for training the neural net is a revolutionary approach in AI development.
- 🧠 Elon Musk's confidence in Tesla's hardware capabilities and vertical integration sets them far ahead of competitors, making it a unique ability to monetize.
- 💰 Tesla is spending $10 billion per year on AI efforts, a huge investment that sets them apart from others in the industry.
- 🔍 The amount of money Tesla is spending on data warehouses and AI development is mind-blowing.
- 🤔 The hardest part of solving full self-driving is interactions with other intelligent beings, not the physics.
- 🤖 The development of self-driving cars could lead to advancements in AGI and embodied AI, as it requires understanding the physics and context of the world.
#Tesla
XMentions: @HabitatsDigital @herbertong @HansCNelson
Clips
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00:00 🚗 Tesla's AI spending is higher than reported, with Elon Musk claiming they would be second highest in spending if measured correctly, and they have already spent over $1 billion on AI this year, potentially building new data centers for Dojo.
- Zuckerberg's meta is leading in compute power, but Elon Musk claims Tesla is second highest, with xai third, and Tesla has already spent over $1 billion on AI this year and may be building new data centers for Dojo.
- Meta (formerly Facebook) has 350,000 h100 gpus, which is 10 times more than Lambda or Google companies.
- Tesla's AI spending is higher than reported, with Elon Musk claiming they would be second highest in spending if measured correctly.
- Dojo would bring Tesla closer to Second, but it's hard to rank compute power based on h100s alone, as there are other forms of GPUs and new Nvidia GB 100 and 200 models coming out.
- Microsoft and OpenAI are not on the list, Google relies heavily on their own TPU for AI capability.
- Elon Musk has secured large allocations of Nvidia chips, contributing to the progress of FSD and xai, and Tesla is no longer compute constrained.
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06:47 🚗 Tesla's AI spending is $1 billion, giving them a significant advantage in building AI for self-driving and robo taxis.
- Elon Musk has been ahead of the game in predicting the importance of AI and securing compute power for Tesla and OpenAI.
- Nvidia has a large amount of compute power, and even if Tesla doesn't have the second most, they still have a massive amount.
- Tesla's AI spend is focused on hardcore machine learning workloads for the development of intelligence, which will likely result in more progress and efficiency compared to their competitors.
- Tesla's AI spending is actually $1 billion, as confirmed by Elon Musk, and the technology is the critical step in achieving Robo taxi.
- Tesla has invested over $10 billion in training, compute, data pipelines, and video storage for their fleet of 6 million cars, giving them a significant advantage in building AI for self-driving and robo taxis.
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12:20 🚗 Tesla's Hardware 3 cars have untapped capability that can be unlocked through better software, making them only a fraction as intelligent as they will be in the future, with an advantage in AI spending and development.
- The Hardware 3 computer in Tesla vehicles has three main chips - CPUs, GPUs, and neural net processing units (NNPUs) - with GPUs being 100 times faster than CPUs and NNPUs being 100 times faster than GPUs for parallelized workloads and AI problems, allowing for the complexity of software algorithms to be shifted from slow CPUs to fast NNPUs.
- Tesla's Hardware 3 cars have untapped capability that can be unlocked through better software, making them only a fraction as intelligent as they will be in the future.
- Tesla uses a network of cameras on their vehicles to collect real-world data for training their AI to drive like a human.
- Tesla has an advantage in AI spending and development, while Nvidia's approach may lead to unnecessary complexity and difficulties for other automakers.
- Tesla is providing hardware and software packages to automakers who are not technically sophisticated enough to solve the problem of AI, and there are not enough automakers committed to installing these packages in millions of vehicles to gather the necessary data.
- Tesla's AI technology is more complex and expensive, resulting in deferred revenue and higher car prices, but Elon Musk's forward thinking and insight into the future of the company is evident.
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19:02 🚗 Tesla is spending $10 billion per year on AI efforts, with the potential to make a lot of money from selling FSD to consumers, and their reliance on real-world data sets them apart from other companies.
- Elon Musk's confidence in Tesla's AI capabilities and hardware superiority gives him high confidence in the company's ability to monetize FSD and Robo taxis.
- Elon Musk believes Tesla is moving towards Robo taxis and is spending $10 billion per year on AI efforts, with the potential to make a lot of money from selling FSD to consumers.
- Tesla is spending a lot of money on data warehouses and real-world AI applications, which sets them apart from other companies.
- Generative AI for autonomous cars is complex and simulation can only take you 90% of the way, with the remaining 10% requiring physical touch points.
- Simulations cannot fully replicate the complexity and nuances of real-world experiences, so Tesla's AI relies on real data from the fleet to solve problems.
- Companies need consumer products at scale to gather real-world data for AI, and while startups and open AI lack this, Google and Apple have the potential for massive futures in this space.
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26:08 🚗 Achieving full self-driving is challenging due to simulating interactions with other intelligent beings, but it is a stepping stone towards achieving AGI and will also help with humanoid robots and embodied AI.
- The hardest part of solving full self-driving is simulating the interactions with other intelligent beings, which is just as hard if not harder to simulate than physics.
- Our brains can instantly recognize and model objects and their movements, similar to a neural network, without consciously performing complex physics equations.
- The CEO of a robotics company believes that self-driving cars are a stepping stone towards achieving AGI and will also help with humanoid robots and embodied AI.
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29:13 🚀 Tesla is investing in unique data centers to support their growing AI and technology needs, potentially with a factory-like approach, and may be working on a solar mega pack.
- Tesla is investing in and building unique data centers, potentially with a factory-like approach, to support their growing AI and technology needs.
- Tesla may be working on a solar mega pack, but there is not enough information to speculate further.
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31:39 🤖 Tesla is investing heavily in AI, with a 10 billion dollar budget this year, as advancements in AI technology are expected to surpass human intelligence by next year and could outpace the last 30 years of progress in the next 10 years.
- Elon Musk believes that AI technology is advancing at an unprecedented rate, with hardware and software breakthroughs occurring frequently.
- AI will likely surpass human intelligence by the end of next year, as shown by the rapid growth in AI computational capacity.
- The rapid advancement of hardware and software in the next 10 years could surpass the progress made in the last 30 years, with the potential for technological developments that may make the dawn of the internet look insignificant.
- Tesla is spending more than people realize on AI, with a budget of 10 billion dollars this year, including data warehouses and hiring for Dojo, and the real world application of AI in their cars.
- Future advancements in AI will happen much more quickly than people realize, and past performance is not indicative of future results.
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38:03 🚀 Tesla is heavily investing in AI infrastructure and data centers, potentially reworking energy grid models, while Amazon purchased a nuclear power data center for their cloud services.
- Tesla is investing heavily in data centers and infrastructure to support their AI and computing needs, including building out supercomputer clusters and utilizing Mega packs for clean and reliable power.
- Tesla is investing heavily in AI infrastructure and chips, and it could potentially use a variety of different chip manufacturers in the future.
- Tesla is working on a solution to solve their own data center electricity problem, which could potentially be provided to others, while Amazon is building a data center near a nuclear power plant due to the need for power.
- Tesla's AI spending is expected to be higher than anticipated, leading to a potential reworking of energy grid models.
- Amazon recently purchased a nuclear power data center to directly power their cloud services, illustrating the massive scale of these data centers.
- Tesla needs cheap and sustainable energy to support their business model, and the speaker encourages viewers to visit his website for comprehensive Tesla investment resources.
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Duration: 0:44:51
Publication Date: 2024-04-10T19:44:35Z
WatchUrl:https://www.youtube.com/watch?v=Fe-J-Ec75YM-------------------------------------