Elon Musk Ordered Nvidia To Ship Thousands Of AI Chips Reserved For Tesla To X And xAI

Elon Musk wants to make Tesla a leader in robotics and artificial intelligence (AI), and he needs to invest a lot of money in Nvidia’s cutting-edge processors to make that happen. However, recent events indicate that Musk might have priorities that do not align with his objectives.

In April, Musk revealed intentions to double the number of Nvidia H100 AI chips in use from 35,000 to 85,000 by the end of the year during Tesla’s first-quarter earnings call. Additionally, he said in a post on X that Tesla will invest $10 billion this year in AI inference and training. Nvidia’s internal communications, however, suggest Musk might have exaggerated Tesla’s procurement plans to investors. According to the correspondence, Musk sent his social media business, X, a sizable shipment of AI processors for Tesla.

“Elon prioritizing X H100 GPU cluster deployment at X versus Tesla by redirecting 12k of shipped H100 GPUs originally slated for Tesla to X instead,” an Nvidia memo from December stated. This move delayed Tesla’s receipt of over $500 million in GPUs by months, likely impacting the development of its autonomous vehicles and robots.

Nvidia staff expressed concern over Musk’s claims. A late April email highlighted that Musk’s statements about AI spending conflicted with actual bookings and fiscal year forecasts, warning that ongoing layoffs at Tesla could further delay the company’s AI projects.

This situation has intensified tensions between Musk and some Tesla shareholders who question whether he can adequately manage his numerous ventures. Musk is also the CEO of SpaceX, Neuralink, The Boring Company, and the owner of X, which he acquired for $44 billion in 2022. Additionally, he founded the AI startup xAI in 2023, which is closely linked with X.

Critics argue that Musk’s multiple commitments undermine his role at Tesla, where he is seen as a part-time CEO. The company’s stock has dropped 29% this year amid declining sales and increased competition. Tesla’s reputation has also suffered in the U.S., partly due to Musk’s “antics” and political commentary, according to the Axios Harris Poll 100 survey.

Musk has emphasized the need for Nvidia’s GPUs to advance Tesla’s AI capabilities, which are in high demand from tech giants like Google, Amazon, Meta, Microsoft, and OpenAI. Nvidia CEO Jensen Huang mentioned the difficulty in meeting this demand, noting that customers are “consuming every GPU out there.”

Despite the high demand, Musk secured a significant allocation of Nvidia chips for his projects. To support Tesla’s AI development, he plans to build a $500 million “Dojo” supercomputer in New York and a dense, water-cooled supercomputer cluster in Texas. At xAI, Musk aims to construct “the world’s largest GPU cluster” in North Dakota by the end of 2024.

Musk’s diversion of resources to X has drawn criticism from legal experts. Joel Fleming, a securities litigator at Equity Litigation Group, highlighted the conflict of interest created by Musk’s dual roles, stating, “When you have someone like Mr. Musk who is a fiduciary to multiple companies, the law recognizes this creates conflict.”

Musk’s history of mixing resources among his companies is well-documented. Following his acquisition of Twitter, he reassigned dozens of Tesla employees to help with Twitter’s overhaul. Similarly, at xAI, Musk has recruited former Tesla employees, including machine-learning scientist Ethan Knight and others involved in Autopilot and big data projects.

A former Tesla supply chain analyst remarked that Musk often treats his companies as extensions of his persona, believing he can use them as he sees fit. This mindset led to Tesla’s controversial 2016 acquisition of SolarCity, where Musk was a major shareholder and chairman.

In response to the recent revelations, Musk posted on X that Tesla had no immediate use for the Nvidia chips, claiming they would have been stored in a warehouse. He added that Tesla’s Texas Gigafactory would soon house 50,000 H100 GPUs for self-driving technology training and that $3 billion to $4 billion of Tesla’s AI-related expenditures this year would go towards purchasing Nvidia hardware.