-My AlphaGo moment was 5 January 2021, when OpenAI released [DALL-E](https://openai.com/blog/dall-e/) (by far the most significant news story of that week in January 2021). Previous AI milestones, like GANs for a _fixed_ image class, were easier to dismiss as clever statistical tricks. If you have thousands and thousands of photographs of people's faces, I didn't feel surprised that some clever algorithm could "learn the distribution" and spit out another sample; I don't know the _details_, but it doesn't seem like scary "understanding." DALL-E's ability to _combine_ concepts—responding to "an armchair in the shape of an avacado" as a novel text prompt, rather than already having thousands of avacado-chairs and just spitting out another one of those—viscerally seemed more like "real" creativity to me, something qualitatively new and scary.
+ But if ninety years is urgent, what about ... nine? Looking at what deep learning can do in 2023, the idea of Singularity 2032 doesn't seem self-evidently _absurd_ in the way that Singularity 2019 seemed absurd in 2010 (correctly, as it turned out).
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+My AlphaGo moment was 5 January 2021, when OpenAI released [DALL-E](https://openai.com/blog/dall-e/) (by far the most significant news story of that week in January 2021). Previous AI milestones, like GANs for a _fixed_ image class, were easier to dismiss as clever statistical tricks. If you have thousands of photographs of people's faces, I didn't feel surprised that some clever algorithm could "learn the distribution" and spit out another sample; I don't know the _details_, but it doesn't seem like scary "understanding." DALL-E's ability to _combine_ concepts—responding to "an armchair in the shape of an avacado" as a novel text prompt, rather than already having thousands of examples of avacado-chairs and just spitting out another one of those—viscerally seemed more like "real" creativity to me, something qualitatively new and scary.[^qualitatively-new]
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+[^qualitatively-new]: By mid-2022, DALL-E 2 and Midjourney and Stable Diffusion were generating much better pictures, but that wasn't surprising. Seeing AI being able to do a thing _at all_ is the model update; AI being able to do the thing much better 18 months later feels "priced in."