Tesla and AMD are reportedly in the final stages of testing their first jointly developed autopilot chips, with the goal of achieving full self-driving capabilities by 2019. While neither company has officially confirmed or denied the collaboration, signs point to a strategic move by Tesla to reduce its reliance on Nvidia, which aligns well with its business strategy. This shift could mark a significant change in the automotive tech landscape.
In addition, it has been reported that Tesla may be moving away from using Nvidia’s chips for its in-vehicle entertainment systems, instead turning to Intel. Although this information remains unverified, it suggests that the relationship between Tesla and Nvidia is becoming more complicated. Analysts believe that if Tesla continues to distance itself from Nvidia, it could result in potential losses of hundreds of millions of dollars next year.
The situation has left Huang Renxun, CEO of Nvidia and a key figure in AI chip development, in an awkward position. Meanwhile, Tesla’s history of switching partners is well known. Last year, after parting ways with Mobileye, Nvidia stepped in with a strategic partnership. However, Tesla has always had its own plans and eventually brought in AMD to further its goals.
As a major player in the automotive industry, Tesla has consistently focused on key areas like AI and self-driving technology. Despite collaborations with companies like Nvidia and AMD, the company has always emphasized its own R&D efforts. According to reports, Tesla’s decision to partner with AMD was partly due to AMD’s strong IP in AI chips, signaling a broader desire for technological independence.
Nvidia, while dominant in the AI chip market, faces challenges in the automotive sector. Although it has strong technical capabilities, its lack of deep automotive manufacturing experience puts it at a disadvantage. However, Nvidia remains a powerful force in general-purpose GPUs and has established partnerships with several automakers, including Audi, Bosch, and ZF.
From a market perspective, Nvidia's Tegra series has long been a key player in automotive tech. The latest Tegra K1 chip has enhanced vehicle perception and processing power, and the launch of DrivePX2 and SoCXavier based on the Volt architecture has helped Nvidia regain momentum in autonomous driving.
Behind the scenes, Tesla has built a formidable team of AI chip experts. Jim Keller, who joined Tesla last year, brings extensive experience from AMD and Apple. His team includes top engineers from Apple, AMD, and even former colleagues from Intel and Nvidia. With such a strong team, it's hard to believe that Tesla isn’t actively developing its own chips.
Tesla’s recent challenges, including a fatal accident involving Autopilot, have increased pressure to innovate. Competitors like Waymo, Google, Apple, Uber, and Baidu are all pushing forward in the self-driving space. For Tesla, having control over core data processing and security is essential, making in-house chip development a natural step.
With so much at stake, the race for autonomy in the automotive industry is just beginning.
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