Source: Wall Street See
Barclays pointed out that the "FOMO" (fear of missing out) emotion was fully displayed in the 2000 internet bubble and history may be repeating itself in today's AI field.
The current AI investment wave seems to be dominated by FOMO sentiment.
FOMO (Fear of Missing Out) describes a fear of missing out on investment opportunities, which often drives investors to make decisions without sufficient rational analysis.
Barclays' latest research report points out that although AI technology is still in its infancy, the capital expenditure of major companies on AI has already shown an irrational prosperity, dominated by FOMO sentiment. As this sentiment fades, there will be large companies gradually reducing AI investments next year.
Ross Sandler and other Barclays analysts pointed out in a report released last week that FOMO sentiment is not uncommon in investment decision-making, especially in rapidly developing fields of technology. Investors fear missing the next major innovation, and thus make a lot of investments in emerging technologies without fully understanding their long-term potential. This sentiment was fully demonstrated in the 2000 Internet bubble, and history may be repeating itself in today's AI field.
AI Capital Expenditure: A FOMO-Driven Carnival?
Barclays' report indicates that there is significant FOMO sentiment in capital expenditure forecasts for AI in the current market.
The report points out that analysts expect cumulative capital expenditures in the AI field to reach $167 billion from 2023 to 2026, based on optimistic expectations of demand for AI products.
However, in stark contrast, the expected incremental revenue from cloud services by 2026 is only $20 billion.
The huge gap between this capital expenditure and expected revenues has raised concerns in the market about overheated AI investments.
Barclays believes that although early AI companies may use user registration numbers and the growth of startups as evidence of demand, Wall Street's skepticism is on the rise.
This skepticism is based on a simple fact: in the past two years, only two phenomenon-level AI products, ChatGPT and Github Copilot, have appeared, but these are just the tip of the iceberg for large models. There are currently limited successful AI products in the market, and there is still a long way to go before widespread application of AI technology.
Future Capital Expenditure: Some May Retreat Next Year
Barclays analysts predict that by 2026, AI capital expenditures ($167 billion) will be sufficient to support over 12,000 ChatGPT-like products, with approximately $70 billion invested in training basic models and the remaining approximately $95 billion used for inference.
However, with the advancement of technology, the cost of AI inference may significantly decrease in the coming years, making current capital expenditure forecasts too optimistic.
Barclays pointed out that although there are expected to be many new AI-based services, and these services will drive positive development in the market and industry, there are doubts about whether 12,000 AI products of ChatGPT-like scale can appear in the market.
Based on these reasons, Barclays wrote:
We believe that by 2025 or later, major players will retreat and cut (AI) capital expenditure plans.
We also note that breakthroughs in smaller basic model fields in the near future may transfer a large number of products and queries from the cloud to edge technology (i.e. running locally on PCs or smartphones), which may further increase the demand pressure from the cloud for large-scale AI capacity before 2026.
Long-term Perspective: AI Technology is Still in Its Early Stages
Although the market may face adjustments in the short term, Barclays research reports also emphasize that AI technology is still in the "super" early stage in the long term and maintains an optimistic attitude in the medium term.$NVIDIA (NVDA.US)$Maintain an optimistic attitude.
Nvidia is unlikely to have any trouble in the midterm, because we expect AI capital spending to remain strong for several years before anyone starts retreating and cutting investment. The early stage of the new chip and technology cycle indicates that (technology giants) will continue to invest in AI in the foreseeable future.
What we need to be aware of is that (the AI wave) is still in its early stages. In the case of Apple, for example, it took nearly five years after the debut of the iPhone to have leading mobile-native applications, and today we are only 20 months into the AI wave.
Barclays also noted that the computational power needed to run AI agents far exceeds today's software and internet services.
To illustrate this dynamic, Character.ai is a popular high-engagement AI company with only about 5 million users, about 1/600th of Google Search, but it recently said that it handles nearly 1/5th of Google's request volume per day. This is because AI agent systems have no memory, need to cache interaction history, and rerun them through large language models to make the next step or message accurate.
Barclays believes that the development potential of AI technology is enormous, but it takes time to overcome technical challenges, market education, and cultivate user habits to realize this potential. In addition, the wide application of AI technology also needs to solve a series of problems including data privacy, ethics, and regulation.
Editor / jayden