Economics of AI: Capabilities, Trends, Price-Wars
Oliver Angélil on how AI models are built and trained, where moats and price wars come from, and why doing what's hard may be the lasting advantage.
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How is an AI model actually built, what makes it economically distinctive, and why do the prices keep falling? At this Ship26-Talk, Oliver Angélil takes the economics behind the tools most of us now use every day and lays them out for a room of builders.
How a model is built decides who can compete
Oliver starts with the big picture and the definitions that matter, then explains how models are trained and what that does to the economics of the whole industry. From there he turns to competition: the moats that hold, the price wars, and the trends worth watching if you build with AI or sell next to it.
Doing what's hard may be the strongest route to lasting advantage
The second half asks where value sits once capabilities get cheaper. Oliver's argument is that doing what's hard may be the most durable advantage there is. He closes with his predictions for where AI is heading and what that means for businesses, and Wednesday talks at the ship tend to turn into a conversation, so bring your questions.
About the speaker
Oliver Angélil is part of the crew at Ship26 and builds data science products. In August he took the room through passive investing and the spending ratio; this time the subject is the economics of the AI industry itself.
Ship26-Talks happen on Wednesday evenings at Schifflände 26, on the Limmat in Zürich's old town. Everything else that's coming up is on /events.