If it’s a 9-inning game, we’re still at the bottom of the first: Portfolio manager

Key Concepts

• Artificial Intelligence (AI) Spending: The financial investment being made by companies in AI technologies and infrastructure.
• AI Bubble: Concerns about an overvaluation of AI-related assets, similar to past speculative bubbles.
• Picks and Shovels: A metaphor for investing in the foundational infrastructure and tools that enable a larger trend, rather than the trend itself.
• Bottleneck: A point of congestion or limitation in a system that restricts overall progress.
• Forward PE Ratio: A valuation metric that divides a company's current share price by its projected earnings per share.
• Inflection Point: A moment when a significant change or trend begins.
• Use Case: A specific application or scenario where a technology can be utilized.

AI Spending and Market Outlook

The discussion centers on the current state of AI spending, with Oracle's upcoming earnings report highlighted as a significant bellwether for the financial health of the AI sector. Concerns about an "AI bubble" have surfaced, with a credit risk gauge on Oracle's debt reaching its highest level since 2009. However, the guest, Mike Smith, with $329 billion in assets under management, expresses a contrarian view, stating he is "not afraid of the bubble."

Smith argues that the current AI boom is fundamentally different from past speculative bubbles, such as the dot-com bubble. He posits that the key distinction lies in the fact that AI spending is "driven by earnings," and "supply is chasing demand." This suggests a more sustainable growth trajectory, with Smith likening the current stage to the "bottom of the first inning" in a nine-inning game.

While acknowledging that publicly traded companies have earnings, Liz points out that companies like OpenAI are still unprofitable and losing money, serving as a foundation for other businesses. Smith counters that even if one player falters, others will step in, as "every one of the players in the race will tell you we could do more business with more supply." He emphasizes the need to monitor when demand and supply lines cross, but asserts that "we're just not there yet."

Investment Picks in the AI Ecosystem

Mike Smith outlines three distinct investment picks across different segments of the AI landscape:

1. Infrastructure: Quanta Services

• Focus: "Picks and shovels" of the AI revolution, specifically addressing the power bottleneck.
• Rationale: Smith believes that while NVIDIA has driven recent market gains, the focus is shifting towards infrastructure. He identifies "power" as the current bottleneck, which translates to "profits."
• Specifics: Quanta Services is highlighted for its work on "transmission lines," a business that was strong even before the AI boom due to aging infrastructure and safety concerns. AI has further enhanced this business, leading to a "very large backlog."

2. AI Suppliers: Snowflake

• Focus: "Map makers" that help companies manage and utilize their data.
• Rationale: Snowflake is crucial for turning AI investments into profits by identifying data locations and guiding its use. Smith believes they are "very well positioned right now."
• Valuation Perspective: Liz notes Snowflake's "rich" forward PE ratio of 184.64. Smith, however, views this as a positive aspect of growth investing, stating that "the best stocks are the ones that look expensive but aren't." He argues that despite short-term earnings valuations, Snowflake is at the "very beginning of a very strong inflection in their business."

3. Use Cases (Non-Traditional AI Companies): Radna

• Focus: Applying AI in healthcare for transformative use cases.
• Rationale: Smith finds the application of AI in "saving lives" to be particularly compelling. He sees "transformative opportunities in health care to deploy this technology."
• Specific Achievement: The transcript mentions a "20% improvement already in cancer diag[nosis]" as a notable achievement.

Conclusion

Mike Smith's perspective suggests a robust and sustainable growth phase for AI, driven by tangible earnings and a demand that outstrips current supply. He advocates for investing in the foundational infrastructure (Quanta Services), the data enablers (Snowflake), and the transformative applications in non-traditional sectors like healthcare (Radna). His investment philosophy emphasizes identifying companies at the early stages of significant business inflection points, even if their current valuations appear high. The key takeaway is that the AI revolution is still in its nascent stages, with ample opportunities for those who invest in its core components and impactful applications.