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Author: Huang Yu

Nvidia is once again at the center of the AI war.

The GPU leader Nvidia had a roller coaster ride this week: a 7% drop on Tuesday, followed by a 13% rise on Wednesday, and then another nearly 7% drop on Thursday. The volatility of its stock price even exceeded that of Bitcoin. Data shows that Nvidia's 30-day option-implied volatility hit 71%, while the Bitcoin DVOL index (an indicator measuring 30-day implied volatility) fell to 49%.

Behind the violent fluctuations of Nvidia's stock price is the shadow of rising costs which looms over the technology giant. The market is increasingly worried about the return on the huge investment in AI.

The bearish camp, represented by Wall Street investment banks and hedge funds, believes that technology giants have invested heavily in AI but cannot generate enough returns. Moreover, the current application scenarios of AI are limited, and such a huge investment is very unwise and risky.

Meanwhile, the bullish camp, represented by major technology giants such as Mag 7, believes that adding capital expenditures to the AI field is necessary now, or they will miss the upcoming AI era.

On Wall Street, where money talks, the focus is on return on investment (ROI).

On the one hand, Wall Street is gradually losing patience, believing that the high capital expenditures of technology giants in the AI field have not brought corresponding returns and more efficient applications. In the past two years, only two phenomenal AI products have appeared, which are ChatGPT and Github Copilot.

Goldman Sachs pointed out in a report at the end of June that the development of AI technology may not be as rapid as expected, and its cost-effectiveness may not be as attractive as imagined.

It is predicted that in the next ten years, AI can only increase US productivity by 0.5%, and its contribution to GDP growth will only accumulate to 0.9%.

Barclays also pointed out in a report in August that the crazy investment in AI by technology giants is out of FOMO, fear of missing out on the development opportunities of AI.

Barclays' latest research report pointed out that although AI technology is still in its infancy, the capital expenditure of large factories on AI has shown an irrational prosperity, and FOMO sentiment dominates. As this sentiment fades, major factories will gradually cut back on AI investment next year.

Analysts predict that capital expenditures in the AI field will reach a cumulative total of 167 billion US dollars from 2023 to 2026. This number is based on optimistic expectations of demand for AI products.

However, in sharp contrast to this, it is expected that the incremental revenue of AI cloud services will only be 20 billion US dollars by 2026.

According to media reports on Friday, Elliott Management, a top Wall Street hedge fund, is even more radical, pointing out that large technology giants, especially Nvidia, are in a bubble, and that the artificial intelligence technology that is driving its stock price sky-high is being overhyped.

Elliott believes that the current artificial intelligence cannot really work efficiently and will consume a large amount of energy.

So far, artificial intelligence has failed to deliver on its promise of significant productivity gains. There are almost no practical use cases beyond summarizing meeting notes, generating reports, and helping computers code.

Artificial intelligence is actually a software that has so far not delivered the value commensurate with the hype.

AllianceBernstein's Strategy Director Jim Tierney said: "Technology giants are betting more on AI spending and creating an atmosphere of 'believe us'. But investors are still unclear about the corresponding business models and returns. However, from the perspective of total expenditure and return on investment alone, investors are still not reassured."

Silicon Valley's technology giants believe that AI will change the future and choose to continue to invest heavily in it.

On the other hand, under the pressure of questioning, technology giants who continue to be optimistic about the future of AI and choose to continue to invest heavily in it. Among them are Microsoft, Alphabet, Amazon, and Meta. In their latest quarterly reports, they revealed that capital expenditures in the first six months of 2024 increased significantly to a total of 106 billion US dollars, and investment will further increase in the next 18 months.

Google's parent company, Alphabet, saw its capital expenditures in the first half of 2024 surge by 90% to 25 billion US dollars.

Microsoft's capital expenditures in the fourth quarter alone grew by 78% to 33 billion US dollars.

In just the fourth quarter, Microsoft's capital expenditures increased by 78%, reaching $33 billion.

Amazon's real estate and equipment investments (including e-commerce and logistics network spending) surged 27% to $32.5 billion in the first half of this year, and capital expenditures are expected to grow significantly by 2024.

Even though stocks of Google, Microsoft, and Amazon were immediately sold off after the financial report was released, executives of these tech giants are still committed to expanding their investments in the AI field.

Google CEO Sundar Pichai said that AI products need time to mature and become more useful.

AI is expensive, but the risk of underinvestment is greater. Google may have invested too much in AI infrastructure, including purchasing NVIDIA GPUs. Even if the AI boom slows down, the data centers and computer chips the company has purchased can be used for other purposes. For us, the risk of underinvestment is far greater than the risk of overinvestment.

Amazon Chief Financial Officer Brian Olsavsky said that these expenditures will be mainly used for new cloud computing infrastructure. Generative AI is now a key business of Amazon.

Meta CEO Zuckerberg also stated last week that to ensure Meta's leading position in the AI field, the company has spent billions of dollars to purchase Nvidia's GPUs for developing and training advanced AI models. Nevertheless, he admits that hype around AI may result in excessive investment.

Meta is willing to take risks by increasing investment early rather than entering late, because the consequence of falling behind is that you will be at a disadvantage in the most important technology for the next 10 to 15 years. Meta's capital expenditures are expected to reach $40 billion this year.

Zuckerberg estimates that the computing power needed to train the next generation of large language models will be nearly 10 times that of the previous version, and he also admits that Meta's AI chatbots may take "years" to make money on their own.

Analysts at Dell'Oro Group predict that as much as $1 trillion may be invested in AI data centers and other infrastructure over the next five years.

What is the key to this "bull and bear battle" around AI?

Regardless of how Wall Street views the continued All in AI approach of tech giants, the key point in this tug of war ultimately focuses on whether the boom of financing can be sustained, and when AI technology can achieve greater breakthroughs in the future.

First of all, the confidence of tech giants in spending a lot of money comes from the relatively stable profitability of their main business.

For example, the core business of Meta, digital advertising market share, continues to grow, and the growth of this part of the business mainly comes from Facebook and Instagram. The 22% year-on-year growth in advertising revenue brought about by these two parts of the business led to a significant increase in Meta's net income in the second quarter, up 73% year-on-year to $13.47 billion.

Zuckerberg also emphasized on the earnings call how AI is helping to fuel advertising growth:

AI improves recommendation features, helping people find better content and making the advertising experience more effective. These products are already scaled.

In contrast, although Google's advertising revenue in the second quarter only increased by 11% to $64.6 billion, its core business is still healthy enough to bear the burden of expanding expenditures.

Although the tech giants have deep pockets and are willing to invest heavily in AI, analysts at Barclays expect that by 2025 or later, major players will withdraw and cut their (AI) capital expenditure plans.

Because with the advancement of technology, breakthroughs in the field of smaller basic models recently, in the next few years, a large number of AI products and search functions will be transferred from the cloud to run locally on PCs or mobile phones. The cost of AI inference may be significantly reduced, and huge capital expenditures may no longer be necessary.

As for when AI technology will achieve greater breakthroughs in the future, it is more like an unknown variable. After all, after investing a lot of resources in AI, currently only two phenomenon-level AI products, ChatGPT and Github Copilot, have emerged, and there is still a long way to go in the future.

Barclays expects that by 2026, AI capital expenditures ($167 billion) will be sufficient to support more than 12,000 ChatGPT-scale products, with about $70 billion invested in training basic models and about $95 billion used for inference.

By then, there will be many new services based on AI, and these services will drive positive development in the market and industry.

What can be determined, however, is that in the AI competition of tech giants, Nvidia is currently the biggest winner. Because of the investments made by Amazon, Google, Microsoft, and Meta in AI capital expenditures, most have gone to building datacenters and purchasing Nvidia's GPU products. This trend may continue into next year.

Although Nvidia's latest quarterly financial report will not be released until the end of August, analysts generally expect that Nvidia's datacenter revenue for the new quarter will reach nearly $25 billion, which is equivalent to the datacenter revenue for the whole year of 2023.

It is soon time to verify the validity of 'AI beliefs'.

Editor/Jeffy