Editor’s note: “How Tesla’s New Supercomputer Could Upend the AI Race” was previously published in October 2023. It has since been updated to include the most relevant information available.
Last month, Morgan Stanley upgraded Tesla (TSLA) stock with a Street-high price target of $400. It’s since reduced that target to $380, but it remains the highest analyst target on TSLA stock. Why? Because Morgan Stanley understands how Tesla’s Dojo supercomputer could unlock $500 billion in economic value.
And while most investors were mesmerized by price target upgrade, I had something else on my mind.
If Dojo is the “real deal” – and I think it is – then this could mark the end of Nvidia’s (NVDA) rule as the leader of the “Artificial Intelligence Boom.”
Wall Street’s AI Boom began in late 2022 with ChatGPT’s launch. Since then, Nvidia has been the poster child for AI stocks. That’s all thanks to burgeoning demand for the firm’s next-generation GPUs, which are used to make and run robust AI models. NVDA stock has surged more than 210% higher this year alone.
But there is growing concern among some in the industry that demand for Nvidia GPUs is maxing out – and that the big players in the AI Race will start using different GPUs.
The New Kid on the Block
Previously, Tesla powered its self-driving operations with a large Nvidia GPU-based supercomputer. But now, Dojo is Tesla’s AI-powered supercomputer.
Being the “brain” behind Tesla’s self-driving operations, Dojo parses an incredible amount of driving data to help develop Tesla’s self-driving algorithms.
In other words, Tesla previously used Nvidia GPUs. But now, the EV firm has developed its own supercomputer that uses its own GPUs custom-built for its AI needs.
And that gets to the crux of the problem here: customization.
In the early innings of the AI boom, Nvidia won big by supplying very advanced but very general-use GPUs to companies looking to develop broad AI models.
But as this race has matured, those companies are now looking to develop more sophisticated and specialized AI models. For that, they need custom-built GPUs. And economically speaking, it doesn’t make sense for Nvidia to create custom-built GPUs for every single one of its customers.
So, Nvidia’s largest customers are developing their own custom-built GPUs to meet their own specialized AI needs.
Tesla and its Dojo supercomputer are just one example.
Custom-Built AI Tech Is on the Rise
In fact, every Big Tech firm building AI models that formerly relied on Nvidia are now developing their own custom-built chips.
Amazon (AMZN) has developed two chips customized specifically to build AI models on the firm’s cloud service, AWS. One is for high-performance inference (AWS Inferentia) and one is for deep-learning training (AWS Trainium). Together, Amazon believes these two chips could power all future AI functions on AWS.
Meanwhile, Alphabet (GOOGL) is already on the fifth generation of its custom Tensor Processing Units, or TPUs, for neural network development.
Reportedly, Microsoft (MSFT) has invested heavily in its own secretive AI chip development project, codenamed Athena. And news broke earlier this year that Meta (META) is developing its own custom chip for running AI models, dubbed the MTIA chip – or Meta Training and Inference Accelerator chip.
Big Tech has made its move. It’s going all-in on AI, and none want to depend on Nvidia to help them win the race.
They all want to do it themselves.
That’s why we believe you need to start looking for the top AI stocks to buy – that are not named Nvidia.
The Final Word
A major turning point has arrived for the AI Boom. And now all the money that was being piled into NVDA and other major chipmaker stocks will go somewhere else.
That’s the trillion-dollar question. And we aimed to answer it during our first-ever broadcast about this market reshuffling.
Therein, I unveiled the name, ticker symbol, and key business details of the No. 1 stock to buy to benefit from this $15.7 trillion market reshuffling. And it is a stock I’ve never recommended before in any of my services.
Trust me. If you want to make money in stocks over the next 12 months, be sure to catch the replay of this event to get prepared.
On the date of publication, Luke Lango did not have (either directly or indirectly) any positions in the securities mentioned in this article.
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