You Could Make a Killing Solving the A.I. Context Problem
Predicting outcomes is a much more valuable proposition than creating content
There are a lot of reasons why the current hype around artificial intelligence is overblown.
Don’t get me wrong, the recent advancements in generative A.I. are impressive, game-changing, almost magical. But those advancements are advancements only in a specific niche of A.I., and they’re most definitely not magical.
You can still make a boatload of money with A.I., but it’s not snap-your-fingers money, it’s more like try-and-fail-a-dozen-times money.
As someone who has been diving deep into natural language generation since 2010, I’ve developed a unique insight into how far generative AI and NLG have come over the last decade and, more important, what the mainstream implications are for the current wave of A.I. advancements, which are basically just advancements in GPTs, which are basically just automated content producers across text, audio, video, code, etc.
I was part of the original team at Automated Insights, and I’m the co-inventor of the first NLG engine that went to market — an engine that still produces content like Yahoo Fantasy Football matchup recaps and Associated Press Quarterly Earnings Reports.
