People learn about Baidu’s artificial intelligence chatbot service Ernie Bot during the 2nd Global Digital Trade Expo at Hangzhou International Expo Center on November 23, 2023 in Hangzhou, Zhejiang Province of China.
China News Service | China News Service | Getty Images
Nvidia’s rocket-ship ride in the stock market underscores the extent to which chip quality and availability will dictate the winners in the generative AI era. But there’s another aspect to measuring early leads in the space. In China, which is angling to produce its own chips or get more from Nvidia, no dominant gen AI contender to OpenAI has emerged yet among dozens of Chinese tech titans and startups.
Late to the game, China is seeking to catch the lead of OpenAI in a wider U.S. AI market shaped by tech titansMicrosoft, Alphabet’s Google and Amazon, and well-financed startups including Anthropic, which this week received a $2.7 billion infusion of cash from Amazon.
In the fast-moving field, the gap between the U.S. and its tech rival China is seen as wide. “The leading Chinese companies are benchmarking against ChatGPT, which indicates how far behind they are,” said Paul Triolo, senior vice president for China and technology policy lead at Dentons Global Advisors in Washington, D.C.
“Not too many companies can support their own large language model. It takes a lot of capital. Silicon Valley is definitely well ahead of the game,” said Jenny Xiao, a partner at AI VC firm Leonis Capital in San Francisco.
The U.S. remains the biggest investment market. Last year, funding of gen AI upstarts accounted for nearly half of $42.5 billion invested globally in artificial intelligence companies, according to CB Insights. In the U.S., VCs and corporate investors drove AI investment to $31 billion across 1,151 deals, led by large outlays in OpenAI, Anthropic and Inflection. This compares with $2 billion in 68 deals in China, which marked a large drop from 2022’s $5.5 billion in 377 deals. The fall-off is partly attributable to restrictions on of U.S. venture investment into China.
“China is at a big disadvantage in building the foundation models for Gen AI,” said Rui Ma, an AI investor and co-founder of investment syndicate and podcast TechBuzz China.
But where China lags in foundational models, which are dominated by OpenAI and Google’s Gemini, it’s closing the gap by using Meta’s open source, large language model Llama 1, and Triolo said the Chinese contenders, if behind, are improving on the U.S. model.
“Many of the China models are effectively forks of Llama, and the consensus is that these forks are one to two years behind the leading U.S companies OpenAI and its video-to-text model Sora,” Ma said.
China does have the tech talent to make a difference in the AI rivalry in the years ahead.
A new study by think tank Marco Polo, run by the Paulson Institute, shows that the U.S. is home to 60% of top AI institutions, and the U.S. remains by far the leading destination for elite AI talent at 57% of the total, compared with China at 12%. But the research finds that China leads the U.S. by a few other measures, including being ahead of the U.S. in producing top-tier AI researchers, based on undergraduate degrees, with China at 47% and the U.S. lagging with 18%. Additionally, among top-tier AI researchers working at U.S. institutions, 38% have China as their country of origin, compared with 37% from the U.S.
New Chinese gen AI market entries can also reach mass adoption quickly. Baidu’s ChatGPT competitor, Ernie Bot, released in August 2023, reached 100 million users by the end of the year. Samsung is planning to integrate Baidu’s Ernie AI into its new Galaxy S smartphones while in another high-profile development that speaks to U.S.-China relations, Apple is in talks with Baidu about supplying the iPhone 16 with the Chinese company’s gen AI technology.
Within its current slate of AI contenders, Baidu’s Ernie Bot models are considered among the most advanced, according to Leong.
Several other Chinese companies are forging ahead, funded by major players in its own technology market. Large cloud companies such as such as Baidu and Alibaba, social media players ByteDance and Tencent, and tech companies SenseTime, iFlyTek, Megvii and Horizon Robotics, as well as research institutes, are all aiding the effort.
Moonshot AI, funded by China’s e-commerce giant Alibaba and VC firm Hongshan (previously Sequoia China), is building large language models that can handle long content inputs. Meanwhile, former Google China president Kai-Fu Lee has developed an open source gen AI model, 01.AI, funded by Alibaba and his firm Sinovation Ventures.
While China has accelerated development of its homegrown chip industry and advanced AI, its AI development has been limited in part by U.S. restrictions on exporting high-end AI chips, a market cornered by Nvidia, as part of a new battleground for tech supremacy between the U.S. and China.
“Despite efforts to develop indigenous solutions, Chinese AI developers still largely rely on foreign hardware, particularly from U.S. companies, which is a vulnerability in the current geopolitical climate,” said Bernard Leong, founder and CEO of tech advisory Analyse Asia in Singapore.
The ongoing tensions between the U.S. and China over technology innovation and national security issues is leading to a split in gen AI development, following the pattern of other impactful technologies caught up in superpower tech arms races. Given regulations and bans over sensitive, cutting-edge technologies, the likely outcome is two parallel ecosystems for gen AI, one in the U.S. and one in China. ChatGPT is blocked in China while Baidu’s Ernie Bot can only be accessed in the U.S. with a mainland Chinese cell phone number. “U.S. companies can’t go into China and Chinese companies can’t go into the U.S.,” Xiao said.
U.S. Secretary of Commerce Gina Raimondo has stated that a goal of U.S. curbs on AI chip exports is to prevent China from acquiring or producing advanced chips. As mainland China focuses on homegrown capabilities, Chinese companies SMIC or Huawei could be an alternative to Nvidia. But the future for alternates is likely uncertain if export controls cut off these companies from the most advanced designs for manufacturing. Triolo noted that Huawei recently developed a series of AI chips as a rival to Nvidia.
China is getting ahead in applying AI to certain categories, such as computer vision. “The chip shortage is very important for training foundational models where you need certain chips, but for applications, you don’t need that,” Ma said.
The “real killer app” for gen AI, according to Triolo, will be in companies that are willing to pay money to harness the technology as part of their business operations. Alibaba is focusing on integrating AI into its e-commerce ecosystem. Huawei, while competing more successfully against Apple’s iPhone in the consumer market in the past year, also has broader ambitions, developing AI for specific industries including mining, using its in-house hardware, Leong said.
Boston Consulting Group research suggests it may be a while before this wider gen AI market ramps outside of tech. Sixty percent of 1,400 executives surveyed are waiting to see how gen AI regulations develop, while only 6 percent of companies have trained their employees on gen AI tools.
AI and tech issues are front and center for China’s leadership, with the country’s release of guardrails on AI in 2023 after ChatGPT’s breakthrough, and then modifications of some measures.
The open source gen AI technology many Chinese developers use can encourage collaboration among globally and lead to shared insights as AI advances, but Leong said open source also leads to issues related to ensuring quality and security of the models, as well as managing bias and potential misuse of AI.
“China wants to make sure content is not spewing out. They also want their companies to lead and are willing to reign in draconian measures,” Triolo said.
Ethical and social concerns hinder gen AI advances in China as well as other regions, including the U.S., as see in the battle for control over OpenAI’s mission. Within China, there is another factor that could slow AI acceleration, according to Leong: maintaining control of gen AI applications, especially in areas sensitive to state interests.
Startup Figure AI is developing general-purpose humanoid robots.
Figure AI
Figure AI, an Nvidia-backed developer of humanoid robots, was sued by the startup’s former head of product safety who alleged that he was wrongfully terminated after warning top executives that the company’s robots “were powerful enough to fracture a human skull.”
Robert Gruendel, a principal robotic safety engineer, is the plaintiff in the suit filed Friday in a federal court in the Northern District of California. Gruendel’s attorneys describe their client as a whistleblower who was fired in September, days after lodging his “most direct and documented safety complaints.”
The suit lands two months after Figure was valued at $39 billion in a funding round led by Parkway Venture Capital. That’s a 15-fold increase in valuation from early 2024, when the company raised a round from investors including Jeff Bezos, Nvidia, and Microsoft.
In the complaint, Gruendel’s lawyers say the plaintiff warned Figure CEO Brett Adcock and Kyle Edelberg, chief engineer, about the robot’s lethal capabilities, and said one “had already carved a ¼-inch gash into a steel refrigerator door during a malfunction.”
The complaint also says Gruendel warned company leaders not to “downgrade” a “safety road map” that he had been asked to present to two prospective investors who ended up funding the company.
Gruendel worried that a “product safety plan which contributed to their decision to invest” had been “gutted” the same month Figure closed the investment round, a move that “could be interpreted as fraudulent,” the suit says.
The plaintiff’s concerns were “treated as obstacles, not obligations,” and the company cited a “vague ‘change in business direction’ as the pretext” for his termination, according to the suit.
Gruendel is seeking economic, compensatory and punitive damages and demanding a jury trial.
Figure didn’t immediately respond to a request for comment. Nor did attorneys for Gruendel.
The humanoid robot market remains nascent today, with companies like Tesla and Boston Dynamics pursuing futuristic offerings, alongside Figure, while China’s Unitree Robotics is preparing for an IPO. Morgan Stanley said in a report in May that adoption is “likely to accelerate in the 2030s” and could top $5 trillion by 2050.
Concerns about stock valuations in companies tied to artificial intelligence knocked the market around this week. Whether these worries will recede, as they did Friday, or flare up again will certainly be something to watch in the days and weeks ahead. We understand the concerns about valuations in the speculative aspects of the AI trade, such as nuclear stocks and neoclouds. Jim Cramer has repeatedly warned about them. But, in the past week, the broader AI cohort — including real companies that make money and are driving what many are calling the fourth industrial revolution — has been getting hit. We own many of them: Nvidia and Broadcom on the chip side, and GE Vernova and Eaton on the derivative trade of powering these energy-gobbling AI data centers. That’s not what should be happening based on their fundamentals. Outside of valuations, worries also center on capital expenditures and the depreciation that results from massive investments in AI infrastructure. On this point, investors face a choice. You can go with the bears who are glued to their spreadsheets and extrapolating the usable life of tech assets based on history, a seemingly understandable approach, and applying those depreciation rates to their financial models, arguing the chips should be near worthless after three years. Or, you can go with the commentary from management teams running the largest companies driving the AI trade, and what Jim has gleaned from talking with the smartest CEOs in the world. When it comes to the real players driving this AI investment cycle, like the ones we’re invested in, we don’t think valuations are all that high or unreasonable when you consider their growth rates and importance to the U.S., and by extension, the global economy. We’re talking about Nvidia CEO Jensen Huang, who would tell you that advancements in his company’s CUDA software have extended the life of GPU chip platforms to roughly five to six years. Don’t forget, CoreWeave recently re-contracted for H100s from Nvidia, which were released in late 2022. The bears with their spreadsheets would tell you those chips are worthless. However, we know that H100s have held most of their value. Or listen to Lisa Su, CEO of Advanced Micro Devices , who said last week that her customers are at the point now where “they can see the return on the other side” of these massive investments. For our part, we understand the spending concerns and the depreciation issues that will arise if these companies are indeed overstating the useful lives of these assets. However, those who have bet against the likes of Jensen Huang and Lisa Su, or Meta Platforms CEO Mark Zuckerberg, Microsoft CEO Satya Nadella, and others who have driven innovation in the tech world for over a decade, have been burned time and again. While the bears’ concerns aren’t invalid, long-term investors are better off taking their cues from technology experts. AI is real, and it will increasingly lead to productivity gains as adoption ramps up and the technology becomes ingrained in our everyday lives, just as the internet has. We have faith in the management teams of the AI stocks in which we are invested, and while faith is not an investment strategy, that faith is based on a historical track record of strong execution, the knowledge that offerings from these companies are best in class, and scrutiny of their underlying business fundamentals and financial profiles. Siding with these technology expert management teams, over the loud financial expert bears, has kept us on the right side of the trade for years, and we don’t see that changing in the future. (See here for a full list of the stocks in Jim Cramer’s Charitable Trust, including NVDA, AVGO, GEV, ETN, META, MSFT.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust’s portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.
Every weekday, the CNBC Investing Club with Jim Cramer releases the Homestretch — an actionable afternoon update, just in time for the last hour of trading on Wall Street. Markets: The S & P 500 bounced back Friday, recovering from the prior session’s sharp losses. The broad-based index, which was still tracking for a nearly 1.5% weekly decline, started off the session a little shaky as Club stock Nvidia drifted lower after the open. It was looking like concerns about the artificial intelligence trade, which have been dogging the market, were going to dominate back-to-back sessions. But when New York Federal Reserve President John Williams suggested that central bankers could cut interest rates for a third time this year, the market jumped higher. Rate-sensitive stocks saw big gains Friday. Home Depot rose more than 3.5% on the day, mitigating a tough week following Tuesday’s lackluster quarterly release. Eli Lilly hit an all-time high, becoming the first drugmaker to reach a $1 trillion market cap. TJX also topped its all-time high after the off-price retailer behind T.J. Maxx, Marshalls, and HomeGoods, delivered strong quarterly results Wednesday. Carry trade: We’re also monitoring developments in Japan, which is dealing with its own inflation problem and questions about whether to resume interest rate hikes. That brings us to the popular Japanese yen carry trade, which is getting squeezed as borrowing costs there are rising. The yen carry trade involves borrowing yen at a low rate, then converting them into, say, dollars, and investing in higher-yielding foreign assets. That’s all well and good when the cost to borrow yen is low. It’s a different story now that borrowing costs in Japan are hitting 30-year highs. When rates rise, the profit margin on the carry trade gets crunched, or vanishes completely. As a result, investors need to get out, which means forced selling and price action that becomes divorced from fundamentals. It’s unclear if any of this is adding pressure to U.S. markets. We didn’t see anything in the recent quarterly earnings reports from U.S. companies to suggest corporate fundamentals are deteriorating in any meaningful way. That’s why we’re looking for other potential external factors, alongside the well-known concerns about artificial intelligence spending, the depreciation resulting from those capital expenditures, and general worries about consumer sentiment and inflation here in America. Wall Street call: HSBC downgraded Palo Alto Networks to a sell-equivalent rating from a hold following the company’s quarterly earnings report Wednesday. Analysts, who left their $157 price target unchanged, cited decelerating sales growth as the driver of the rerating, describing the quarter as “sufficient, not transformational.” Still, the Club name delivered a beat-and-raise quarter, which topped estimates across every key metric. None of this stopped Palo Alto shares from falling on the release. We chalked the post-earnings decline up to high expectations heading into the quarter, coupled with investor concerns over a new acquisition of cloud management and monitoring company Chronosphere. Palo Alto is still working to close its multi-billion-dollar acquisition of identity security company CyberArk , announced in July. HSBC now argues the stock’s risk-versus-reward is turning negative, with limited potential for upward estimate revisions for fiscal years 2026 and 2027. We disagree with HSBC’s call, given the momentum we’re seeing across Palo Alto’s businesses. The cybersecurity leader is dominating through its “platformization” strategy, which bundles its products and services. Plus, Palo Alto keeps adding net new platformizations each quarter, converting customers to use its security platform, and is on track to reach its fiscal 2030 target. We also like management’s playbook for acquiring businesses just before they see an industry inflection point. With Chronosphere, Palo Alto believes the entire observability industry needs to change due to the growing presence of AI. We’re reiterating our buy-equivalent 1 rating and $225 price target on the stock. Up next: There are no Club earnings reports next week. Outside of the portfolio, Symbotic, Zoom Communications , Semtech , and Fluence Energy will report after Monday’s close. Wall Street will also get a slew of delayed economic data during the shortened holiday trading week. U.S. retail sales and September’s consumer price index are scheduled for release early Tuesday. Durable goods orders and the Conference Board consumer sentiment are released on Wednesday morning. (See here for a full list of the stocks in Jim Cramer’s Charitable Trust.) As a subscriber to the CNBC Investing Club with Jim Cramer, you will receive a trade alert before Jim makes a trade. Jim waits 45 minutes after sending a trade alert before buying or selling a stock in his charitable trust’s portfolio. If Jim has talked about a stock on CNBC TV, he waits 72 hours after issuing the trade alert before executing the trade. THE ABOVE INVESTING CLUB INFORMATION IS SUBJECT TO OUR TERMS AND CONDITIONS AND PRIVACY POLICY , TOGETHER WITH OUR DISCLAIMER . NO FIDUCIARY OBLIGATION OR DUTY EXISTS, OR IS CREATED, BY VIRTUE OF YOUR RECEIPT OF ANY INFORMATION PROVIDED IN CONNECTION WITH THE INVESTING CLUB. NO SPECIFIC OUTCOME OR PROFIT IS GUARANTEED.