Wall Street doesn’t seem to have stopped raving about Nvidia over the past few weeks as the investment community seeks to capitalize on the growing AI trend taking the tech sector by storm. That praise has translated into stunning performance from the stock — after a 50% plunge in 2022, down nearly 86% this year and on course for its best quarter since 2001. Of course, the gains were helped by the market’s rotation after one returned to tech stocks after the worst years for the sector in over a decade, but booming demand for AI skills in the wake of ChatGPT’s stunning debut was the main catalyst. Investors are hungry for companies that can capitalize on this trend. AI isn’t just a buzzword like the Metaverse. Many have equated generative AI with the advent of the internet or cloud computing, with some considering ChatGPT his “iPhone moment”. As technology advances, it will open up a range of new economic opportunities. As the market grows, so does the opportunity for Nvidia, and that’s why some people believe there’s still room for further upside in the stock. A recent forecast by Goldman Sachs suggests that the broadest definition of artificial intelligence could generate around $7 trillion in global economic growth over the next 10 years. In a recent statement, Bernstein calculated that ChatGPT could spark a new market generating “tens of billions” annually. “This isn’t necessarily a bad thing for Nvidia,” said Srini Pajjuri, an analyst at Raymond James. “The pie is growing, even if they lose a little bit of share, they’re still going to grow very quickly.” NVDA YTD Mountain Nvidia shares are trading at an expected price-to-earnings ratio of about 58 times so far this year. As recently as last year, its rating was around 26 times. The contrast is even sharper when you consider that the multiple for the S&P 500 averages about 3 times. This fuels concerns about whether Nvidia is worth the premium investors are paying. Supporters say Nvidia’s early focus on GPUs allowed the company to build an efficient chip that was worth its price and gave it an edge over its rivals that should allow Nvidia to maintain its dominance. Building Unmatched AI Dominance Graphics processing units, or GPUs, refer to the chips that create images and graphics and are the foundation of many emerging artificial intelligence requirements. It’s an area the company invested in for games just over two decades ago, and one that will pay dividends as AI explodes. Data from New Street Research suggests the company already accounts for 95% of the market for GPUs that can be used for machine learning, with hundreds of these chips typically needed to train many new AI models. “They saw generative AI as potentially a really big deal, and they saw this years ago when the rest of us were just kind of ignorant of what generative AI could bring to the world,” said Karl Freund, senior analyst at Cambrian AI Research. Generative AI refers to systems that can generate text or image responses and is often associated with large language models or ChatGPT. The focus on Nvidia’s capabilities in this area has only grown since it unveiled new AI technologies at its GTC conference. This included the CUDA Quantum software and computing platform, which can be used to program GPUs. Following the conference, Goldman Sachs called the chipmaker a “major AI enabler,” while Bank of America said Nvidia’s AI dominance could “reshape the existing tech industry.” “Bottom line: NVIDIA continues to be 1-2 steps ahead of its competitors when it comes to accelerated computing chips/systems, software and ecosystems,” wrote JPMorgan’s Harlan Sur. A first-mover advantage While rivals like Advanced Micro Devices and Intel try to compete with the juggernaut, Nvidia’s lead will make it difficult to replicate or compete. Freund reckons that Nvidia will account for 90% of the overall market share over the long term, with competitors sharing the rest. That’s partly because Nvidia offers the engineering and end-user and research organization relationships, in addition to the hardware and software, which could thwart competitors’ plans from the start, Freund explained. “It’s hard for me to imagine how anyone can catch up,” he added. This software, commonly referred to as CUDA, handles the difficult task of programming GPUs and has a huge ecosystem of developers, explained Raymond James’ Pajjuri. This ecosystem continued to grow with AI, creating a “barrier to entry” for companies looking to break into the space. This first mover advantage is critical. With so many engineers already using Nvidia’s software, some companies may face resistance when attempting to switch to a new language, said Pieran Maru, an investment analyst at global wealth management firm GAM Investments. He said he has trimmed some of his overweight positions in Nvidia in recent weeks amid stocks’ sharp rise. But he said that despite the high valuation, he continues to bet on the stock as it is focused on disruptive growth. Paul Meeks, a portfolio manager at Independent Solutions Wealth Management, refrains from giving it a top weight in his portfolio due to its high PE, but considers its AI involvement a “slam dunk” and a “best-in-class” enabler. “The stock is a bit pricey, but also remember that the stock took such a bad hit last year that even if you come 80% off the bottom, we’re still well, well below the one-time high into the gold.” days lie.” he said. Nvidia’s forward PE ratio peaked at around 65.5 in November 2021, right around the time the Nasdaq Composite hit its all-time high. Last year the stock closed in October at a low of $112.27. But the high price point isn’t for everyone. Rather than bet on Nvidia, FBB Capital Partners’ Michael Brenner owns Taiwan Semiconductor and ASML, names involved in Nvidia’s supply chains that should benefit secondarily from the growing market. Regardless, Wall Street stands by the chip giant, with Bernstein’s Stacy Rasgon raising his price target on shares to $300 in a recent note to clients. The new target represents an 11% move higher from Wednesday’s close. Rasgon acknowledged that stocks are trading expensive but highlighted a large runway for opportunities that offer “upside”. “Many investors continue to look for the ‘best’ way to play these AI themes and we are struggling to find a better way than this at the moment, we remain buyers here too,” he wrote. – CNBC’s Michael Bloom contributed to the coverage
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