Market Call: Ivana Delevska's outlook on Technology Stocks

Key Concepts

• AI Value Chain: The interconnected network of companies involved in the development and deployment of Artificial Intelligence, spanning from chip design and manufacturing to data centers and applications.
• Capital Expenditure (CAPEX): Funds used by a company to acquire, upgrade, and maintain physical assets such as property, plants, buildings, and equipment.
• Hyperscalers: Large-scale cloud service providers like Amazon, Google, and Microsoft that operate massive data centers.
• Data Center Value Chain: The ecosystem of companies supporting the operation of data centers, including infrastructure providers, cooling solutions, and power management.
• Semiconductor Manufacturing Equipment: Machinery used in the fabrication of semiconductors (chips), a critical component of AI infrastructure.
• Space-Based Data Centers: The concept of locating data centers in orbit to leverage unique advantages like solar power and reduced latency.
• Memory (DRAM/NAND): A type of computer data storage that is volatile (DRAM) or non-volatile (NAND), essential for AI processing.
• Quantum Computing: A type of computing that uses the principles of quantum mechanics to solve complex problems beyond the capabilities of classical computers.
• SaaS (Software as a Service): A software distribution model where applications are hosted by a vendor and made available to customers over the internet.

Market Call Summary with Ivana Dylewska (Spear Invest)

Introduction

The episode of Market Call features Ivana Dylewska, Founder and CEO of Spear Invest, discussing investment opportunities within the rapidly evolving technology sector, particularly focusing on Artificial Intelligence (AI). The conversation centers on identifying areas of the AI value chain poised for growth, navigating cyclical trends, and assessing the potential of emerging technologies like space-based data centers and quantum computing.

1. AI Investment Strategy: Focusing on Capital Equipment

Dylewska advocates for investing in the capital equipment side of the AI value chain, specifically companies providing the machinery to build more memory capacity. She explains that investment has shifted from the hyperscalers (companies investing in chips) to the chip companies themselves, who are now increasing capacity. This is driven by the increasing demand for memory and chips required for AI applications, leading to higher CAPEX requirements. She believes this area offers a better risk-reward profile than directly investing in memory manufacturers themselves.

2. Memory Market Dynamics & Cyclicality

While acknowledging the current strong demand for memory, Dylewska cautions that this is a cyclical market. She predicts that as supply increases, memory stock prices will likely plateau. She emphasizes the importance of understanding these cycles and investing in the infrastructure supporting memory production (capital equipment) for a longer-term investment horizon. She notes that the capital equipment cycle typically outlasts the memory cycle itself.

3. Space-Based Data Centers: A Growing Opportunity

The discussion turns to the feasibility of data centers in space. Dylewska believes this concept is closer to reality than many perceive, as satellites already utilize solar power and onboard computing. The key challenge is reducing launch costs to make it economically viable. SpaceX is identified as a leading competitor, leveraging its expertise in launch and satellite operation, as well as Elon Musk’s knowledge of AI and chips. Google is also noted as an investor in AST SpaceMobile, a company building large satellites. Dylewska stresses that the opportunity lies in limited supply and launch capacity, creating potential for returns. She clarifies the thesis isn’t an immediate shift of all data centers to space, but rather increasing activity and potential returns.

4. Apple’s AI Strategy & Potential Risks

Dylewska expresses a negative outlook on Apple stock, citing the lack of a clear AI plan. She also highlights a potential risk stemming from increasing memory component costs, driven by demand from data centers. She explains that Apple, like other manufacturers, sources memory from the same factories, meaning higher data center memory prices will trickle down to consumer electronics. While Apple’s high gross margins mitigate some of this risk, the lack of an AI strategy remains a concern.

5. Semiconductor Stocks: TSMC vs. Micron

Regarding Taiwan Semiconductor Manufacturing (TSMC), Dylewska acknowledges its attractive position as a leading foundry but believes the stock is currently overvalued. She sees better value in other areas of the AI value chain. In contrast, she views Micron as potentially undervalued, but cautions about its cyclical nature. She advises monitoring capacity expansion announcements to identify when the market will rebalance. She emphasizes that capital equipment stocks offer a more stable investment opportunity.

6. Quantum Computing: A High-Risk, High-Reward Play

Dylewska discusses quantum computing, specifically mentioning Rigetti Computing. While acknowledging the sector’s potential, she notes that commercial contract momentum was slower than expected in the previous year, leading Spear Invest to trim its position. She emphasizes the higher risk associated with quantum computing compared to more established sectors like semiconductor manufacturing.

7. Software Sector Disruption & AI’s Impact

Dylewska highlights a significant shift in the software sector due to AI. She differentiates between software applications (like Salesforce and HubSpot) which are vulnerable to disruption by AI, and software infrastructure (like cybersecurity) which is poised to benefit. She advises investors to focus on infrastructure companies, as AI can easily replicate the functionality of many applications. She specifically mentions Constellation Software as potentially facing headwinds due to this trend.

8. Top Picks & Investment Rationale

Dylewska presents three top picks:

• Coherent (COHR): A leader in optical networking components, benefiting from increased data transmission demands. Valuation is more attractive than competitors like Lumentum and Sienna.
• Lam Research (LRCX): A key player in semiconductor manufacturing equipment, poised to benefit from the build-out of new chip and memory capacity. Strong earnings potential.
• Rocket Lab (RKLB): A space launch company developing a new, more cost-effective rocket (Neutron) that will enable broader access to space, particularly for data centers. She believes launch capacity will become constrained, driving demand.

9. Key Investment Principles

Dylewska emphasizes the importance of:

• Boots-on-the-ground research: Tracking where companies are investing their capital to identify emerging opportunities.
• Idea Velocity: Regularly rotating portfolio positions to maintain fresh ideas and capitalize on new trends.
• Understanding Cyclicality: Recognizing the cyclical nature of industries like memory and adjusting investment strategies accordingly.
• Risk Management: Considering volatility and ensuring investments align with risk tolerance.

Conclusion

Dylewska’s insights emphasize a strategic approach to investing in the AI revolution, focusing on the foundational infrastructure that supports its growth. She advocates for a nuanced understanding of cyclical trends, emerging technologies, and the evolving competitive landscape to identify opportunities with strong long-term potential. Her emphasis on capital equipment, optical networking, and space-based solutions provides a framework for investors seeking to capitalize on the transformative power of AI.