When it comes to processing power for artificial intelligence (AI) applications, speed is essential, but chipmaker Nvidia also wants to be first in terms of manufacturing.
Bank of America research analyst Vivek Arya has high hopes for Nvidia’s stock, especially with its strong focus on deployment of its products. If more bullishness is ahead for the stock, then this should benefit the Direxion Daily NVDA Bull 1.5X Shares (NVDU).
In 2023’s big tech comeback, AI has been a common refrain for its strong growth prospects. More industries are harnessing the capabilities of AI, which will require the need for chips from the likes of companies like Nvidia.
As mentioned, Nvidia is now focused on rapid deployment of its products. For this reason, Arya is forecasting upside ahead for the stock after viewing a company presentation to investors.
“The analyst referred to an updated investor presentation the company issued this month, which shows the chip maker is moving from its previous two-year product cycle to a one-year cadence for its AI chips,” Barron’s reported. “A slide in the document shows Nvidia will release successors to the current high-end H100 product in 2024 and 2025.”
“We believe the new data center roadmap disclosure suggests widening product breadth with an accelerated launch cadence that can continue to make it tougher for merchant competitors to catch-up,” Arya mentioned.
Market Dominance of Nvidia
The recent investor presentation should increase the future prospects of Nvidia’s stock moving forward. It already benefited from a strong run-up for the year, rising over 200% thus far.
Another strong growth catalyst is the sheer market dominance Nvidia has in terms of chips specifically focused on AI. The company has a strong foothold in the market due to its programming flexibility. And its plan to deploy its chips faster should help with customer retention.
“Nvidia currently dominates the market for chips used for AI applications. Start-ups and corporations prefer the company’s products because of its robust software programming ecosystem, CUDA,” Barron’s added. “Developers have been building and sharing AI-related tools and software libraries for over a decade on Nvidia’s proprietary platform, making it easier to build AI applications rapidly.”
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