In the series of articles I've been writing for Fast Company devoted to what I believe corporate AI should be, I've been touching on a very provocative idea: Perhaps the biggest problem of corporate AI as we know it so far is not intelligence, but the level at which we are programming it.
In the series of articles I've been writing for Fast Company devoted to what I believe corporate AI should be, I've been touching on a very provocative idea:
As we speak, frontier models, elastic cloud infrastructure, vector databases, managed APIs, and large amounts of computation are available to basically any serious company.
Perhaps the biggest problem of corporate AI as we know it so far is not intelligence, but the level at which we are programming it.
The page is ready to read now. The fuller skim-friendly version will appear here automatically.
In the series of articles I've been writing for Fast Company devoted to what I believe corporate AI should be, I've been touching on a very provocative idea: Perhaps the biggest problem of corporate AI as we know it so far is not intelligence, but the level at which we are programming it. As we speak, frontier models, elastic cloud infrastructure, vector databases, managed APIs, and large amounts of computation are available to basically any serious company.
As a substrate, this is extraordinarily powerful.
Open the app view to save this story, compare related coverage, and continue from the same source.