# The generative AI revolution has begun—how did we get here? | Ars Technica

<https://arstechnica.com/gadgets/2023/01/the-generative-ai-revolution-has-begun-how-did-we-get-here/>

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- Saved: February 2, 2023 (2023-02-02T15:36:56Z)
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## What Jamie wrote

Great article summarizing what got us so many advances in AI so quickly. What was the key enabling technology, as well as the approaches that allowed such quick progress.

> To sum up, the breakthrough with generative image models is a combination of two AI advances. First, there's deep learning's ability to learn a “language” for representing images via latent representations. Second, models can use the “translation” ability of transformers via a foundation model to shift between the world of text and the world of images (via that latent representation).

I found this interesting because it helps frame up domains that are more or less appropriate for these AI models. If you lack a similar structure in a domain, pursing an AI solution to work with it is going to be very difficult.

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- [WT240: Weekly Thing #240 / Shapes, Tags, Ubiquity](https://weekly.thingelstad.com/archive/240/), Notable

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## Elsewhere

- Wayback Machine: https://web.archive.org/web/*/https://arstechnica.com/gadgets/2023/01/the-generative-ai-revolution-has-begun-how-did-we-get-here/
