There is a healthy debate about the impacts of artificial intelligence on infrastructure, the global power grid, and business productivity. We at Halcyon welcome the discussion, which is earnest, data-driven, thoughtful and constructive. This week, I thought it worth reviewing the state of AI challenges, its impact on productivity, and why we need to remember that building AI infrastructure is not the same as what we build on top of it.
Energy asset developers have information needs in multiple timelines. Some needs are nearly instantaneous, such as price(s) and volume(s), and are ‘structured’ in data parlance. They are numbers, in forms easily accessed via download or API, and easily integrate into other structured data or models.
There are many challenges with energy transition information today. Verity is one: is the data that you have collected correct, and from a definitive source? Validity is another: is the data that you are seeking the right data for your strategic or analytical purposes?
The cover story of this week’s edition of The Economist is a long look at the present state and future trajectory of the global solar industry. I was fortunate to have the chance to speak with the newspaper and provide thoughts on an industry I’ve looked at closely for almost two decades.
This post is the first in a series examining the economics and environmental benefits of AI’s demand for electricity.
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