QQQ - Energy Tech And AI: Use Cases And Markets

2023-06-14 11:19:04 ET

Summary

• The AI Day, where Nvidia's earnings announcements gave the Nasdaq market a new outlook, continues to spark analysis and firm announcements.
• LLMs at present cannot substitute for the discriminative power of human analysis, ie., deep subject matter expertise.
• The requirements of an increasing tech stack have implications for energy mix developments.
• Investment time horizons matter as does a value proposition that meets society's needs; energy is a need.
• A great shift is happening in how we produce energy. Tech can help point the way, alongside human discernment.

After a number of brushes with research from a conference, several ideas have emerged. Ultimately, most of these ideas have investment implications. But, with an investment approach vs. a trading approach, a key factor is investment time horizon.

The AI Day , where Nvidia's earnings announcements gave the Nasdaq market a new outlook, continues to spark analysis, including my own. I had crafted this article the day after Nvidia's rise but its posting was delayed into Memorial weekend.

Market Celebrates Artificial Intelligence (Video)

As mentioned in the article about generative AI and energy below, my approach is to add in baskets of tech into my energy portfolio. This is alluded to in the following article and video of June 2:

Reset And Regenerate: Themes After The Fed Conference (Video)

Observing the market's machinations, I've stepped back to consider other forces, particularly how this plays into energy. The following video backgrounder relays what I find important. We're stepping into the known unknowns. This video backgrounder relays some of the linkages.

AI, Chips and Energy: Part III

While the jockeying for the dominant tech in AI begins, the use cases are starting to happen as we have seen many announcements and partnerships. The media and content potential are clear. For a knowledge worker like me, it can be an assistant and boost productivity. But LLMs at present cannot substitute for the discriminative power of human analysis, ie., subject matter expertise. While they mirror some of the complexity of the human thought processes, there are limits and misuse cases. Hence the public debate about the regulation of AI.

About Energy

In the article "Reset and Regenerate..." the applications for AI and tech in general are quite vast. Over time, I'll be observing what use cases happen and how the energy mix changes to adapt. But, that's a very lengthy process which cannot break the bank, so to speak. Innovation and the geologics and biologics of energy have an inherent tension. The requirements of an increasing tech stack have Nth order effects, and we have started to see those cracks. In a recent video with CIO Jay Hatfield of [[AMZA]], the actively-managed MLP fund, we discuss the midstream space. An important point he discusses is the betas of energy and tech. This is the dynamic I and other analysts allude to about the [[QQQ]] vs. [[XLE]] argument.

The sentiment between energy and tech are at best superficial. In a longer horizon, the data suggests one cannot beat the market. Thus, I select energy powerhouses like Exxon Mobil ( XOM ), Chevron ( CVX ), and independents such as Pioneer ( PXD ) and Diamondback ( FANG ). After that, my indexes and ETFs reflect the general direction of tech and sustainable energy infrastructure; on the sustainable infrastructure front that's a dual basket with MLPs and resource-aware funds.

U.S. Hydrocarbon Energy Infrastructure: Really Long-Lived Assets (Link to video)

Hatfield makes the case for investing in energy infrastructure from an income-generating point of view. One has to decide how much growth and risk they can carry in an investment portfolio. Investment time horizons matter as does a value proposition that society needs. Energy is a need. While some tech has been "wants," gains can and are being made in this enterprise market. Having said that, as mentioned in the AI-chip video, the consumer market has been funding the R&D for this next iteration. [I was a bit unclear in my delivery owing to my brain being in overdrive about all of this. This is the state noted in regard to LLMs (large language models) about hallucination.]

The productivity gains of the transistors/chip dynamic, as noted in the AI-Chip video, of the last 30 years has been a significant economic boost. The world has become more connected in many ways. The firm-level applications of AI, broadly speaking, can revolutionize the world of work. The speed at which the iterations can happen are potentially rapid. But, as we saw in energy with the Ukraine invasion, disruption can happen, the risk side. Disruption can be disrupted with policy, technology and economic risk. The financial markets are really going to be put to work in this area, to determine the firms moving the needle and then the right kind of adoption. I'm siding with firms that adopt with a capital discipline mantra but a weather eye on the horizon.

For further details see: