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 entry of Machine Readable is a conversation between Nat Bullard, Chief Strategy Officer, Halcyon, and Vicky Homan, GTM Lead, Halcyon. Among the many hats she wears, Vicky is an integral part of Halcyon’s customer-facing team and is also our record-holder for most queries submitted via Halcyon’s platform.
Information platforms that interact with large language models (LLMs) are built with a fundamental advantage: users can engage with them in natural language through written queries and requests. They can do so not just quickly and iteratively, but creatively as well.
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