\n
![](\"https:\/\/fortune.com\/img-assets\/wp-content\/uploads\/2024\/08\/GettyImages-1241460753-e1723811981686.jpg?w=2048\")
<\/p>\n [ad_1]
\n<\/p>\n
Eric Schmidt, the CEO of Google<\/a> until 2011, is many things but one thing he is not is a financial advisor licensed to provide investment advice. If he were, however, he made it pretty clear that AI training chip vendor Nvidia<\/a> is a stock he thinks belongs in every portfolio.<\/p>\n Speaking to Standford University students this week, the billionaire angel investor argued that the race to commercialize generative artificial intelligence and other forms of AI was still in its early stage. Even though the easy money might have already been made, in his opinion, there\u2019s still plenty of upside potential in the space.<\/p>\n That\u2019s particularly true for Nvidia, whose head start in graphic processing units (GPUs) like the benchmark H100, combined with its dominant software ecosystem CUDA, gives it an enormous lead as a data center\u2019s supplier of choice for AI training chips.<\/p>\n \u201cThe amount of money being thrown around is mind-boggling,\u201d Schmidt told students. \u201cI\u2019m talking to the big companies, and the big companies are telling me that they need $10 billion, $20 billion, $50 billion, $100 billion.\u201d\u00a0<\/p>\n Schmidt added that OpenAI chief executive Sam Altman even believes it will take $300 billion to develop artificial general intelligence, a machine capable of reasoning on its own.\u00a0<\/p>\n \u201cIf $300 billion is all going to Nvidia, you know what to do in the stock market,\u201d Schmidt continued, before quickly adding: \u201cthat\u2019s not a stock recommendation, I\u2019m not licensed.\u201d<\/p>\n Nvidia shares have been the primary beneficiary of the AI gold rush, with its stock nearly tripling this year to hit $135 by mid-July. That has been driven in part by debt-funded \u201ccarry\u201d trades, a\u00a0momentum play<\/a>\u00a0where investors borrow in cheap Japanese yen to invest in higher yielding, dollar-denominated U.S. growth stocks.<\/p>\n With the recent sharp rise in Japan\u2019s currency over the greenback, shares have pulled back from their highs when the company\u2019s $3.3 trillion market cap briefly made it more valuable than any other company in the world.<\/p>\n Yet Nvidia still has a chance to mark fresh highs should it smash earnings expectations when it reports quarterly results at the end of this month.<\/p>\n Judging by Schmidt\u2019s conversations with his contacts at Big Tech, he certainly expects demand for its AI training chips to remain robust, if not exponential.\u00a0<\/p>\n Referring to Percy Liang, a Stanford AI researcher, who has had to resort to Google\u2019s tensor processors (TPUs) due to a lack of availability of Nvidia chips, Schmidt said: \u201cIf he had infinite money he would pick the B200 architecture.\u201d\u00a0<\/p>\n The B200 is Nvidia\u2019s\u00a0next-generation training chip<\/a>.\u00a0It is so advanced even its packaging has to be done in the controlled conditions of a clean room, not just the creation of the wafer itself, according to Schmidt.<\/p>\n While Lisa Su\u2019s AMD may one day catch up on hardware, he said her company\u2019s software ecosystem doesn\u2019t have the user base of Nvidia and a compiler to translate CUDA into AMD\u2019s own programming language ROCm to aid developers doesn\u2019t yet work.\u00a0<\/p>\n Neither Nvidia nor AMD could immediately be reached for comment.\u00a0<\/p>\n Stanford took down the video following criticism levelled at Schmidt after he blamed his former employer blowing its headstart on AI on a\u00a0lackadaisical work ethic<\/a>\u00a0that enabled its staff to work from home rather than the office.<\/p>\n Google researchers invented in 2017 the so-called\u00a0transformer<\/em>\u00a0neural network that powers most GenAI models, only to \u201cthen put it on the shelf,\u201d as Marc Andreessen put it\u00a0last month<\/a>. The very name of OpenAI\u2019s own ChatGPT \u2014\u00a0generative pre-trained transformer<\/em>\u00a0\u2014 that launched in late 2022 reveals its Google ancestry.<\/p>\n Schmidt didn\u2019t comment on what kind of time horizon he had for his investment recommendations. It\u2019s safe to say, though, that as an angel investor funding various startups, it\u2019s longer than the average on Wall Street.<\/p>\n This was evident, for example, in a filing this week from Citadel. Ken Griffin\u2019s hedge fund has slashed its holdings in Nvidia by\u00a0two-thirds<\/a>\u00a0to $19 million at the end of June after selling about half a million shares. Last month Griffin told his firm\u2019s new class of potential talent he\u00a0doubted<\/a>\u00a0GenAI would be as revolutionary as others believe.\u00a0<\/p>\n Schmidt, whose net worth doesn\u2019t quite match Griffin\u2019s but is still estimated at\u00a0nearly $24 billion<\/a>, told Stanford students he takes a less targeted approach when shopping for the next AI leader: \u201cI essentially invest in everything, because I can\u2019t figure out who\u2019s going to win.\u201d<\/p>\n<\/div>\n\nAMD<\/a> cannot compete yet with Nvidia\u2019s dominant CUDA software<\/h2>\n
AI skeptic Ken Griffin slashes hedge fund Citadel\u2019s exposure to Nvidia <\/h2>\n