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Blockchain-Based Render Network’s Token Tracks Tech Stocks as Broader Crypto Market Decouples

Decentralized GPU-based rendering solutions provider Render Network’s native cryptocurrency RNDR has rallied in sync with technology stocks this month, defying the broader crypto market lull.

Data from TradingView show RNDR has gained 6.5% to $2.55, with prices hitting a 13-month high of $2.93 early this month. Wall Street’s tech-heavy index Nasdaq has gained nearly 8%. Meanwhile, bitcoin (BTC) has declined by 5%, decoupling from Nasdaq and the total market value of all cryptocurrencies has dropped by 3.5%.

“RNDR has been a good high beta Nasdaq play in recent weeks,” Decentral Park Capital’s portfolio manager Lewis Harland said in Friday’s market update, noting the artificial intelligence narrative as a catalyst for gains in both tech stocks and RNDR.

A week ago, the U.S.-based chipmaker Nvidia (NVDA), while forecasting surging revenue, said it is increasing supply to meet the spike in demand for its artificial intelligence (AI) chips used to power ChatGPT and similar services.

Since then, investors have been scrambling to take exposure to shares in Nvidia and other assets like Render’s RNDR token that align with the AI narrative.

“RNDR (Render Network) stands out due to its unique convergence of key narratives such as integrations with the Apple ecosystem, Metaverse involvement, artificial intelligence (AI) integration, and 3D rendering capabilities,” crypto fundamental analyst Jason Choi said in his research newsletter Blockcrunch VIP dated May 22.

“As demand for GPU computing power is expected to soar in fields like gaming, metaverse development, architecture, animation, product design, augmented reality (AR), and more recently, AI tooling, RNDR may present an accessible alternative to expensive computing equipment typically required for creating 3D graphics,” Choi added.

Note that RNDR has also benefited from speculation that Apple’s impending virtual reality headset will utilize Render Network’s decentralized graphics processing network.

Edited by Parikshit Mishra.

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