Sterling Proffer

The cycle is dizzying and numbing: The allure of authenticity invites fascination and then, inevitably, skepticism. All along, truth and trust aren’t celebrated; they’re destabilized.

To understand why foundation models represent a “phase change in ai”, in the words of Fei-Fei Li, the co-director of Stanford University’s Institute for Human-Centred ai, it helps to get a sense of how they differ from what went before.

3. Fund one-time projects and moonshot ideas: One of the benefits of crypto is giving fragmented groups of people the tools to rapidly coordinate around shared ideas. Artists, fans and music companies can use NFTs to crowdfund one-time projects and moonshot ideas.

Creators and communities do what they do because they love their world, and they want to invite more people into it. It’s about delivering non-replicable value to passionate audiences. As you scale, you will reach a point where it’s impossible — indeed, damaging — to devote more hours of the day to creative endeavors.

Emergent properties are linked to another highly promising feature: flexibility. Earlier generations of ai systems were good for only one purpose, often a pretty specific one. The new models can be reassigned from one type of problem to another with relative ease by means of fine tuning. It is a measure of the importance of this trait that, within... See more