Nvidia Shares Rebound 2% as AI Chip Competition Grows

Nvidia shares rose 2% to $209.09 after two losing sessions as investors weigh expanding AI-chip competition, including Amazon exploring sales of its in-house AI processors outside its cloud.

Nvidia shares rose 2% to $209.09 in early trading on Thursday, recovering after two consecutive losing sessions. The stock dipped to intraday lows near $204 before rebounding toward the $210 area where buyers stepped in.

Through Wednesday’s close, Nvidia is up 9.8% year to date and about 41% over the past 12 months. The PHLX Semiconductor Index has advanced roughly 170% over the same 12-month span, outpacing Nvidia over that period.

For much of the generative AI surge, Nvidia’s graphics processing units were the primary hardware used for large-scale model training and inference. Investor attention has moved to other companies that could claim portions of AI infrastructure spending, including Advanced Micro Devices, developers of custom chips, central processor makers adapting products for AI workloads and specialized hardware providers.

Large technology firms have expanded investment in proprietary processors to reduce the cost of training and running AI models. Peter DeSantis, Amazon’s vice president of infrastructure and AI, described the company’s stance in Paris: ‘We view AI infrastructure as rapidly evolving, and we’re constantly looking at ways to get to more customers.’ He declined to identify potential buyers.

Technical indicators improved during the bounce. The relative strength index climbed above 60, the MACD turned positive after a bullish crossover, and trading volume increased during the recovery from the session lows. The $210 area is the immediate level to watch, while resistance near $212 has kept the shares in a short-term range.

Investors and analysts are watching how AI infrastructure spending will be allocated across the semiconductor ecosystem and which companies will win contracts from cloud providers and large enterprises. Several major cloud operators accelerated development of custom chips after the launch of ChatGPT and the subsequent jump in demand for AI computing capacity.

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