AI's Napster Moment

Napster’s fundamental disruption was building a world of abundance in the music industry, forever changing the access users expected to music.

Simultaneously, it destroyed the economic value of creating music in the first place.

It would be seven years between the launch of Napster (1999) and the business model that would save music — brought to us by $Spotify Technology S.A.(SPOT)$ . But it would be a full 22 years, not until 2021, that the music industry would fully recover from Napster’s fundamental disruption.

This fundamental disruptive tension has made its way to artificial intelligence.

What happens to artificial intelligence and the hundreds of billions of dollars being invested if there’s no payback on the initial breakthrough?

What happens when we all expect AI to be free, and available anywhere anytime with any capability?

We may need to start asking that question because of an innovation that came from an open-source developer in China.

AI Finds Its Napster

Napster’s innovation wasn’t creating content, it was the speed and abundance that it brought to distribution. I remember downloading thousands of songs in my college dorm room in 2000 when Napster was at its peak.

The change had a chilling effect on music.

1. Lowered the cost of content for users to zero.

2. Magnified distribution by making music abundant rather than scarce.

3. Destroyed monetary value for the original creator.

As I mentioned earlier, it wouldn’t be until Spotify made music subscriptions popular that the music industry truly recovered. In the meantime, at least musicians could tour because, without that, no money would be left.

What’s Next?

Here’s the conundrum in AI: If there’s no reward for spending multiple billions of dollars building foundation models because those models will just be used to train cheaper, better models, what’s the point of building the foundation model in the first place?

This is a question $Alphabet(GOOG)$ $Alphabet(GOOGL)$ $Meta Platforms, Inc.(META)$, OpenAI, Anthropic, and even $NVIDIA(NVDA)$ will need to answer.