<div id="readability-page-1"><div><div><p><strong>Nvidia Corp.</strong> <span>NVDA</span> faces pressure from custom silicon competitors as tech giants scale up alternative artificial intelligence chip production, according to <strong>SemiAnalysis</strong> founder <strong>Dylan Patel</strong>.</p><div><div><div><p>Trending Investment Opportunities</p></div></div></div><h2>Custom Silicon Orders Surge</h2><p>Google and Amazon are “massively” increasing orders for their proprietary chips, Patel said during a recent podcast with <strong>a16z</strong>, also known as <strong>Andreessen Horowitz</strong>, a popular venture capital firm in Silicon Valley. <strong>Amazon.com Inc. </strong><span>AMZN</span> produces millions of Trainium processors while <strong>Alphabet Inc.</strong> <span>GOOGL</span> <span>GOOG</span> manufactures millions of Tensor Processing Units.</p><p>“Google’s TPUs are clearly 100% utilized,” Patel noted. “Amazon’s Trainium isn’t there yet, but Amazon will figure out how to optimize usage.”</p><h2>Google’s TPU Market Potential</h2><p>Patel believes Google should sell TPUs directly to external customers rather than just cloud rental services. Such a move could theoretically generate higher market value than Google’s core business.</p><p>“Google is even discussing it internally,” Patel said. “It would require a big reorganization of culture and how Google Cloud works, but they could totally do it.”</p><p>“I think that’s the biggest threat to Nvidia is that people figure out how to use custom silicon more broadly,” Patel said.</p><p>Google’s latest TPU, Trillium, delivers 4.7x peak compute performance compared to previous generations and operates 67% more energy-efficiently. The company currently restricts TPU access to internal use and select cloud customers, including <strong>Apple Inc. </strong><span>AAPL</span>.</p><h2>Market Concentration Determines Winners</h2><p>The AI chip landscape depends heavily on customer concentration, according to Patel. Concentrated AI development among major tech companies favors custom silicon, while broader distribution benefits NVIDIA’s general-purpose GPUs.</p><p>Recent developments support both scenarios. <strong>OpenAI</strong> continues relying on Nvidia GPUs despite testing Google TPUs.</p><p>Amazon’s Trainium2 chips offer 30-40% better price performance than comparable GPU-based instances, positioning AWS as a formidable competitor in the training market.</p><ul> <li><strong>OpenAI Rolls Out $4.60 Subscription In India That Gives Access To ‘Most Popular Features’</strong></li> </ul><p><em>Photo courtesy: Shutterstock.com</em></p></div></div></div>

AMZN

NVDA

GOOGL

GOOG

<p>Nvidia Corp. faces increasing competition from Google and Amazon as they ramp up production of custom AI chips. Dylan Patel from SemiAnalysis highlights that Google’s Tensor Processing Units (TPUs) and Amazon’s Trainium processors are gaining traction. Patel suggests Google should sell TPUs directly to external customers, which could enhance their market value. He warns that the shift towards custom silicon poses a significant threat to Nvidia, especially as Amazon's Trainium chips show better price performance compared to GPUs. The AI chip market's dynamics are influenced by customer concentration among major tech firms.</p>

- Nvidia Corp. faces increasing competition from tech giants like Google and Amazon, who are ramping up production of custom AI chips.  
- Google’s Tensor Processing Units and Amazon’s Trainium processors are being utilized extensively, with potential plans for Google to sell TPUs directly to external customers.  
- The AI chip market's dynamics favor custom silicon among major companies, while Nvidia's GPUs remain essential for some, as evidenced by OpenAI's continued reliance on them.  

Nvidia's Reign At Risk? Dylan Patel Says Google's TPU, Amazon's Trainium Could Outshine GPUs If Sold To Public