AI companies funding each other: Croft

Key Concepts

• Earnings Season: The period when publicly traded companies release their financial results.
• Artificial Intelligence (AI): Technology that enables machines to perform tasks typically requiring human intelligence.
• AWS (Amazon Web Services): Amazon's cloud computing platform.
• Supply Constraints: Limitations in the availability of goods or resources needed to meet demand.
• Rare Earths: A group of 17 chemical elements with unique properties crucial for many modern technologies.
• Circular Investment Trend: A practice where a company invests in another on the condition that the recipient company purchases the investor's products or services.
• Generative AI Models: AI models capable of creating new content, such as text, images, or code.
• Back Testing: The process of testing an investment strategy on historical data.
• Oracle: A technology company providing cloud services and enterprise software.
• OpenAI: An artificial intelligence research laboratory.
• Private Markets: Investment markets that are not publicly traded, such as venture capital and private equity.
• Debt Spreads: The difference in yield between different types of debt, indicating risk.
• Defaults: The failure to repay a loan or meet other financial obligations.

Market Focus and Earnings Season

The primary focus for investors currently is the ongoing earnings season. Richard Croft highlights that artificial intelligence (AI) continues to be the main driver of performance in the US equity market, with big tech companies leading the way. While reported numbers have generally exceeded expectations, this is not entirely surprising as company management often downplays projections before releases. However, some companies have experienced significant volatility due to results being "less than a whisper numbers" (meaning they fell short of even the lowest analyst expectations).

Amazon and AWS Growth

A notable example discussed is Amazon's recent earnings report, which showed much better-than-expected performance, particularly in AWS. The key takeaway from Amazon CEO Andy Jassy regarding the previous slowdown in AWS growth was that it was constrained by supply, not a lack of demand. This means Amazon did not have enough infrastructure (computing power, energy) to meet the demand. Croft points out that for a company of Amazon's size, supply constraints are surmountable due to their substantial capital. The fact that AWS performed well in the recent quarter suggests these supply issues have been addressed. Croft believes Amazon, with its diverse business segments, is poised to be a "surprise winner" and a "better winner" over the next year.

Raw Materials and Canadian Market

In contrast to the US market's AI focus, Croft suggests that raw materials, including the sale and use of rare earths, are likely to be beneficial for the Canadian market.

Circular Investment Trend and AI Financing

A significant concern and an interesting trend observed is the circular investment trend. This involves companies like Nvidia investing heavily in other companies on the condition that those companies purchase Nvidia's products. This practice is particularly prevalent in the current environment due to the substantial capital required for back testing and training generative AI models.

Oracle is presented as a case study. Its recent earnings report showed remarkable growth, with a large backlog of orders. However, this backlog was contingent on OpenAI utilizing Oracle's services for its AI development, which requires significant data center infrastructure. OpenAI is reportedly covering the costs associated with these data centers, positively impacting Oracle's income statement but also affecting its balance sheet.

The sustainability of this model hinges on OpenAI's ability to continue raising capital. Croft raises a concern about the future justification of equity investments in OpenAI, given its current private market valuation of approximately half a trillion dollars.

Private Market Debt and Transparency Concerns

Croft also notes that a considerable amount of debt financing for smaller companies involved in AI development is occurring in the private markets. This lack of transparency is a concern, as it makes it difficult to assess the impact of debt levels on the broader economy. Unlike public markets, where debt spreads (e.g., between junk debt and government debt) provide visibility into risk, this information is less accessible in the private sector. Defaults are already being observed in high-risk bonds within the private markets, indicating growing nervousness, often linked to the circular financing loops discussed.

Conclusion

The market is currently navigating a complex landscape driven by earnings season and the pervasive influence of AI. While big tech companies are leading performance, concerns exist around the sustainability of AI financing models, particularly the circular investment trend and the opacity of private market debt. Despite some cautionary signals, Croft maintains a mildly bullish outlook, seeing potential opportunities in specific sectors like raw materials for the Canadian market and continued growth for companies like Amazon.