This clip captures Charles Hudson arguing that many data entrepreneurs are overly optimistic about demand for raw data. He suggests that data is valuable primarily when transformed into an input for another business process (e.g., training LLMs or self-driving car systems), rather than as a standalone business offering.
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But to Oren's point, my sense has been a lot of data entrepreneurs end up being overly optimistic about the universe of people who will see value in their data. And some of it feels very like an ex post rationalization. It's like, well, because I've gone through all this effort to collect this data, there must be people who will find it valuable. And if I think about what is what appears to be valuable today, it's the ability to transform data into some other useful input. Whether that's hey, we have a bunch of training data that you can use to train your LLM. We have a bunch of data we can use to train your self driving car. It appears that data that enables some other business process is valuable as an input, but as an input to another business, not as a business in and of itself. And.