<div id="readability-page-1"><div><div><p><strong>Tesla, Inc.</strong> (NASDAQ:TSLA) CEO <strong>Elon Musk</strong> is full of transformational ideas — but he’s &#34;increasingly confident&#34; one of them could work.</p><ul> <li><em>TSLA stock is moving. </em><em>Watch the real-time price action here. </em></li> </ul><p>Musk has explored a distributed AI inference approach that leverages Tesla's fleet of EVs. That means each car becomes a high-performance AI processing node when not driving. </p><p>He envisions Tesla’s millions of cars as a network like <strong>Amazon Web Services </strong>(AWS). Inference tasks—such as running generative AI models and complex data analysis—are handled not in traditional data centers but across vehicles themselves.​​</p><p>Early Wednesday morning, Musk revisited the idea in a post on X. </p><p>&#34;I am increasingly confident that this idea could work,&#34; he said, referring to a post explaining the distributed AI network. </p><h2>Concept and Technical Foundation</h2><p>Tesla vehicles are equipped with advanced hardware for autonomous driving, including the latest AI inference chips. </p><p>Each car has up to one kilowatt of inference capability, and with tens of millions of cars, the collective compute power could reach 100 gigawatts, exceeding current centralized data centers. </p><p>The power can be utilized when cars are not actively driving, often during charging, turning unused CPU resources into productive assets.​​</p><h2>Strategic and Economic Implications</h2><p>Tesla could avoid the enormous cost and energy requirements of building centralized AI data centers by utilizing cars for distributed inference. </p><p>Owners might opt in for their vehicles to participate, especially if paid for participation.</p><p>Even a fraction of Tesla's U.S. fleet participating could generate significant annual revenue and profit. </p><p>Concerns about battery drain and memory usage mean practical implementations would likely prioritize cars that are charging and equipped with adequate hardware.​</p><h2>Tesla's AI Future </h2><p>Tesla bull and Wedbush analyst<strong> Dan Ives</strong> has been increasingly focused on the company's AI initiatives and recently maintained an Outperform rating on Tesla with a $600 price target.</p><p>&#34;The Tesla story going forward is around the AI transformation being led by the autonomous and robotics initiatives,&#34; Ives said. </p><p>Musk's distributed inference vision certainly would position Tesla as more of an AI and robotics company than a traditional automaker. </p><ul> <li><strong>Trump’s White House Ballroom Donors Include Google, Micron, Palantir and More</strong></li> </ul><p><em>Photo: Shutterstock</em></p></div></div></div>

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<p>Tesla CEO Elon Musk is optimistic about a new idea to utilize the company's fleet of electric vehicles (EVs) as a distributed AI processing network, similar to Amazon Web Services (AWS). Each Tesla car could act as a high-performance AI node, potentially generating significant revenue by participating in inference tasks while not in use. This approach could save costs on centralized data centers and transform Tesla into a leader in AI and robotics, according to analysts. Musk's vision could redefine the company's future beyond traditional automotive manufacturing.</p>

- Tesla CEO Elon Musk is confident in a new distributed AI inference approach that utilizes the company's fleet of electric vehicles as high-performance AI processing nodes.  
- This system could potentially generate significant revenue by leveraging the collective compute power of millions of cars, avoiding the costs of centralized data centers.  
- Analysts suggest that this AI transformation could redefine Tesla's identity, positioning it as a leader in AI and robotics rather than just an automaker.

Elon Musk's Tesla Fleet Dream—AWS On Wheels