Great analysis. You didn't mention behind the grid power generation as a major source of short-term energy supply. Specifically, utility scale natural gas power plants that are only providing power to data center and that are not necessarily connected to the grid. Many of the players you mentioned I'm sure will benefit from AI data center growth but what are your thoughts about energy producers playing a bigger role in the short term? It seems that the tech players are focusing on natural gas to supply the AI data center power load as the most cost effective and quickest way to scale. This was missing from your analysis and I think is worth a second look.
Interesting. Are there any big public players that are doing this?
I specifically ignored oil and gas companies as they are excessively affected by the commodity pricing and also we won't be able to accurately judge how much of their reveue is coming from data center deals.
When considering natural gas you should also consider the possibility of being curtailed due to gas pipelines serving residential heating before industrial gas fired generation. Take a good look at what happened in 2022 with Winter Storm Elliot. There are so many parameters to consider.
Matt, this was my thought as well. The only way I see the anticipated data center/AI build out working is if they include behind the grid power generation in their data center build out. Essentially building power plants, attached to natural gas pipelines, on their data center grounds. I can’t imagine the US grid being able to handle the anticipated demand any time close to data center build timelines.
In your model there's "% of Portfolio" only with no absolute portfolio value based on QTY of holdings - however, one can still suss out the median Dividend Yield to come in at ~1.12% This ups your overall blended return. The reason I bring this up is if you add in your big gas distribution networks and producers (i.e. ENB, XOM) with their long term, contracted take-or-pay revenue streams then your total portfolio would reflect larger returns with lower risk based on a larger ecosystem. Great work BTW.
Great. This research documents and reinforces with what solar / wind and any renewable needs to be prioritized and resonates with growing data storage requirements. ❤️
Great piece. Any thoughts on fuel cell player Bloom? Also, a big part of the buildout will be gas powered. Perhaps the buildout has multiple dimensions - 1. Grid infra (as you have covered). 2. Nat gas infra (best positioned midstream cos.) 3. Energy resources (eg. Comstock resources, maybe even Chevron) 4. Nuclear infra (uranium enrichment players such as Urenco and Centrus).
Great post, but I quibble with statement about “operating leverage.”
“AI models are expensive to build and train, but once they’re ready, serving additional users costs very little.”
Of course, creating the models are a significant expense. But, inference is no trivial matter either. In fact, many retail customers (not on the API)—even the small percent that are paying for a monthly subscription does not cover the cost generated by their inference use.
Agree with the energy thesis. Surprised the nuclear sector was mostly left out of your discussion and portfolio. Given nuclear is compelling as a long term solution why wasn’t it included?
Cameco (CCJ), NexGen (NXE) and sector ETF’s URA and URNM are examples worth exploring
Great analysis. You didn't mention behind the grid power generation as a major source of short-term energy supply. Specifically, utility scale natural gas power plants that are only providing power to data center and that are not necessarily connected to the grid. Many of the players you mentioned I'm sure will benefit from AI data center growth but what are your thoughts about energy producers playing a bigger role in the short term? It seems that the tech players are focusing on natural gas to supply the AI data center power load as the most cost effective and quickest way to scale. This was missing from your analysis and I think is worth a second look.
Great article on the topic of natural gas fueling hyperscaler DC's is on the A16Z substack, called "Gas-Fired Intelligence". Highly recommend
Interesting. Are there any big public players that are doing this?
I specifically ignored oil and gas companies as they are excessively affected by the commodity pricing and also we won't be able to accurately judge how much of their reveue is coming from data center deals.
GEV and BE seem to be serving the behind-the-meter and Bring Your Own Power (BYOP).
When considering natural gas you should also consider the possibility of being curtailed due to gas pipelines serving residential heating before industrial gas fired generation. Take a good look at what happened in 2022 with Winter Storm Elliot. There are so many parameters to consider.
https://www.naes.com/winter-storm-elliott-2022-the-impact-on-the-u-s-power-grid-and-recommendations-for-resilience/#:~:text=The%20winter%20storm%20of%20December%202022%2C%20known,challenges%20for%20both%20electric%20and%20gas%20utilities.
Matt, this was my thought as well. The only way I see the anticipated data center/AI build out working is if they include behind the grid power generation in their data center build out. Essentially building power plants, attached to natural gas pipelines, on their data center grounds. I can’t imagine the US grid being able to handle the anticipated demand any time close to data center build timelines.
Yes I like your ideas. Pick and shovel players make sense to me thanks!
Thanks William.
In your model there's "% of Portfolio" only with no absolute portfolio value based on QTY of holdings - however, one can still suss out the median Dividend Yield to come in at ~1.12% This ups your overall blended return. The reason I bring this up is if you add in your big gas distribution networks and producers (i.e. ENB, XOM) with their long term, contracted take-or-pay revenue streams then your total portfolio would reflect larger returns with lower risk based on a larger ecosystem. Great work BTW.
Great. This research documents and reinforces with what solar / wind and any renewable needs to be prioritized and resonates with growing data storage requirements. ❤️
Thanks.
This is amazingly useful. Congrats
Thanks Paul.
Yes, very well done. Would love to be able to track your portfolio in real time - is that possible?
Thank you. Yes. You can track it here:
https://docs.google.com/spreadsheets/d/1-eyFutbby_Ntbs_8cnO-zYPoUquN5DSZbTpxq_EC9mA/edit?usp=sharing
This is excellent research! Fantastic article
Thank you!
Do we have a good ETF for energy industry, similar to this portfolio?
Great piece. Any thoughts on fuel cell player Bloom? Also, a big part of the buildout will be gas powered. Perhaps the buildout has multiple dimensions - 1. Grid infra (as you have covered). 2. Nat gas infra (best positioned midstream cos.) 3. Energy resources (eg. Comstock resources, maybe even Chevron) 4. Nuclear infra (uranium enrichment players such as Urenco and Centrus).
Love the thorough analysis and insights! Super helpful
Great article. Amazing how quickly net zero fascination seems to be disappearing 😂 I’m liking a PM mining and power combo.
Great post, but I quibble with statement about “operating leverage.”
“AI models are expensive to build and train, but once they’re ready, serving additional users costs very little.”
Of course, creating the models are a significant expense. But, inference is no trivial matter either. In fact, many retail customers (not on the API)—even the small percent that are paying for a monthly subscription does not cover the cost generated by their inference use.
Agree with the energy thesis. Surprised the nuclear sector was mostly left out of your discussion and portfolio. Given nuclear is compelling as a long term solution why wasn’t it included?
Cameco (CCJ), NexGen (NXE) and sector ETF’s URA and URNM are examples worth exploring
Re: spreadsheet - Nuscale Power Corp. SMR
??
SMR is Nuscale's symbol. You had FLNC.