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The S&P 500’s top gainer so far this year has even further to go on the next AI innovation, Evercore ISI says

Chaim Potok by Chaim Potok
April 24, 2023
in Investing
The S&P 500’s top gainer so far this year has even further to go on the next AI innovation, Evercore ISI says
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The top gainer in the S & P 500 could become the premier player in the artificial intelligence race and fuel another rally, according to Evercore ISI. The rise of investor interest in AI in the wake of the debut of Open AI’s ChatGPT late last year has helped drive Nvidia ‘s recent gains. Shares have added 89% since the start of the year. Evercore expects the outperform-rated stock to add another 18% in the coming months, based on its $320 price target. Nvidia shares closed Friday at $271.19. Analyst CJ Muse said the chipmaker’s exposure to AI means further advancements, specifically the rise of Auto-GPT, will deliver the lion’s share of the benefits to Nvidia. NVDA YTD mountain Evercore ISI thinks Nvidia can climb even higher despite already being the largest gainer in the S & P 500 so far this year. “While the stock has had a massive run-up YTD, we believe that we are clearly still in the very early innings of AI proliferation. As such, NVDA remains a Top Pick with plenty of room to run from here as NVDA’s opportunity morphs from a % of cloud capex to a % of worldwide IT spend,” Muse said in a Saturday note. Auto-GPT is the next iteration of language learn models that power ChatGPT. The key difference, Muse explained, is how Auto-GPT can string together multiple tasks or “thoughts” at once as opposed to the one-to-one question-and-answer functionality currently employed by ChatGPT. Since Auto-GPT will be able to handle several requests at once, the technology can more efficiently serve a user’s end goal and provide a step-by-step roadmap toward that end. Auto-GPT also has the ability to connect to the internet to solve tasks, vastly expanding its data library versus ChatGPT. The potential prominence of Auto-GPT will be enough to render ChatGPT “archaic,” Muse said. “NVDA remains our favorite way to play this dynamic as the compute arms dealer, with MRVL / AVGO also solid exposure to generative AI growth through networking,” Muse added. Still, limitations could arise, Muse said, citing as examples the difficulty integrating a wide breadth of applications and the steeper cost of processing requests for Auto-GPT, which “are somewhat prohibitive for commercial production.” — CNBC’s Michael Bloom contributed to this report.



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