Beyond Nvidia: What Wall Street’s missing in the AI boom

Summary

In this insightful discussion, John McNeel, CEO of DVX Ventures, delves into the overlooked areas of artificial intelligence (AI) investment beyond Nvidia, emphasizing the AI data center infrastructure. He outlines how companies in power generation, fiber optics, networking, and substrates are crucial to AI's growth. McNeel also compares Tesla's advantages in the robo-taxi market, highlighting the debate between sensor versus camera technologies for autonomous vehicles. Lastly, he explores the potential impacts of EV tax credits on the broader market, including a possible 20-30% demand drop if such credits are removed.

Takeaways

• 😀 Nvidia is seen as a major player in the AI ecosystem, but there are other overlooked opportunities within AI infrastructure.
• 😀 John McNeel, CEO of DVX Ventures, highlights the need to look beyond companies like Nvidia and explore the full scope of AI infrastructure.
• 😀 AI data centers have specific requirements such as higher fiber, power, and cooling compared to regular data centers, influencing the broader AI investment landscape.
• 😀 The AIS ETF, co-founded by McNeel, provides exposure to companies contributing to AI data center infrastructure, such as power generation, electronics, and fiber providers.
• 😀 Companies like GE, ABB, Corning, and others play crucial roles in powering and supporting AI data centers, illustrating the diversity of investment opportunities in AI.
• 😀 McNeel emphasizes the importance of taking a holistic view of AI investments, not just focusing on chip suppliers like Nvidia, but also on the infrastructure that supports AI.
• 😀 Major players like Microsoft, Amazon, and Oracle are confirming their AI infrastructure investments, suggesting continued growth in the AI sector.
• 😀 Tesla's autonomous driving efforts face significant competition from companies like Waymo, who are ahead in terms of data and experience with autonomous rides.
• 😀 Tesla’s advantages in autonomous driving include having a large fleet of vehicles on the road, gathering massive amounts of data, and possessing powerful GPU clusters for AI development.
• 😀 The debate between sensors and cameras in autonomous vehicles highlights trade-offs in decision-making speed and safety, with Tesla preferring a camera-only approach and others integrating additional sensors like radar and LiDAR for better coverage in various conditions.
• 😀 If the EV tax credit is removed, it could lead to a 20-30% drop in consumer demand, as seen in markets where such credits were withdrawn, and it may harm US automakers as Chinese manufacturers like BYD continue to dominate.

Q & A

What is Nvidia's role in the AI ecosystem?

Nvidia is seen as a key player in the AI ecosystem, particularly in providing hardware like GPUs for AI processing. However, it is only a small part of the larger AI infrastructure, which involves many other components.

What other areas within AI is John McNeel focusing on?

John McNeel is focusing on the broader infrastructure needed to support AI, such as power generation, cooling systems, networking, and substrates, in addition to the hardware like GPUs that Nvidia is known for.

How does John McNeel approach investment in AI infrastructure?

John McNeel takes a holistic approach to investment, looking beyond just the popular names like Nvidia and examining the broader ecosystem, including power generation, networking, and cooling systems, all of which contribute to the AI infrastructure.

What companies are part of the AI infrastructure ETF that John McNeel co-founded?

The ETF includes about 60 stocks from various sectors that contribute to building AI data centers, including companies like GE for power turbines, ABV for power electronics, and Corning for fiber optics.

What are some of the key components of an AI data center?

Key components of an AI data center include power generation (e.g., gas turbines), power electronics (e.g., ABV), fiber optics (e.g., Corning), networking, and cooling systems.

How do Nvidia's investments compare to those of other large hyperscalers?

Other hyperscalers like Microsoft, Amazon, and Oracle are making similar long-term investments in AI infrastructure, confirming their commitments as they expand their AI capabilities.

What is Tesla's advantage in the autonomous vehicle market?

Tesla has a significant advantage in the autonomous vehicle market due to its large fleet of vehicles on the road gathering data and its vast GPU compute resources, including a 100,000 GPU cluster and plans for a million GPU cluster.

What is the difference between Tesla's approach and Waymo's approach to autonomous driving?

Tesla focuses on using cameras and software to drive autonomously, while Waymo, the leader in autonomous driving, uses additional sensors like radar and LIDAR for better safety and performance in various conditions.

What is the argument for using radar and LIDAR in autonomous vehicles?

Radar and LIDAR can help autonomous vehicles overcome the limitations of cameras, such as seeing in low light, through glare, or around corners, improving safety in various driving conditions.

What would be the impact on the EV market if the EV tax credit were eliminated?

If the EV tax credit were removed, demand for electric vehicles could drop by 20-30%, according to data from other markets where similar tax credits have been eliminated. This could also give a competitive advantage to Chinese EV manufacturers like BYD.