How Should Entrepreneurs Use ChatGPT?

NLG isn’t magic, and its entrepreneurial implications are still TBD

When a new technology breaks into the mainstream, it seems like a sudden and transformative shift. Naturally, a gold rush follows, as corporations, venture capitalists, and enterprising entrepreneurs alike all scramble to invent the ideal use case, or at least the use case that can most quickly get to market and find traction.

You might remember not too long ago when an iced tea company tried to create the ideal use case for blockchain.

The rush is on with Natural Language Generation and the recent commercialization breakthrough heralded with ChatGPT. Believe me, everyone I know is trying to figure out how to weave the NLG wave into their own business model, including me.

But I’m a special case.

As a writer, I’ve got a bone to pick with ChatGPT. But as an entrepreneur, I hold a patent for the first commercial platform to use Natural Language Generation in a corporate environment. So I’m forced to play both sides.

A Brief History of NLG Commercialization

Back in 2010, sports data entrepreneur Robbie Allen and I, along with a handful of young developers, built a platform and an engine to create human-sounding content out of large sets of data, mostly sports data at that time.

We didn’t even call what we were doing NLG because we weren’t aware of the term yet. It had not yet been coined in 2010. We were just trying to do better sports data. We built a company around that platform called Automated Insights, which was acquired by private equity in 2015.

I wrote algorithms to analyze the data and determine what could be said and when it should be said, paying special attention to patterns, deltas, trends, and milestones. In the closed universe of sports — and eventually industries like finance, marketing, even healthcare — my algorithms could “write” some pretty amazing and magical content. And thanks to Robbie and the coding team, we could spit out those articles at the rate of tens-of-thousands per second, each one unique, each one reading like it was written by an industry professional.