10 items tagged “ai”
DALL·E: Creating Images from Text (via) “DALL·E is a 12-billion parameter version of GPT-3 trained to generate images from text descriptions, using a dataset of text–image pairs.”. The examples in this paper are astonishing—“an illustration of a baby daikon radish in a tutu walking a dog” generates exactly that. # 5th January 2021, 8:31 pm
When data is messy. I love this story: a neural network trained on images was asked what the most significant pixels in pictures of tench (a kind of fish) were: it returned pictures of fingers on a green background, because most of the tench photos it had seen were fisherfolk showing off their catch. # 7th July 2020, 7:03 pm
I have sometimes wondered how I would fare with a problem where the solution really isn’t in sight. I decided that I should give it a try before I get too old. I’m going to work on artificial general intelligence (AGI). I think it is possible, enormously valuable, and that I have a non-negligible chance of making a difference there, so by a Pascal’s Mugging sort of logic, I should be working on it.
Without deep understanding of the basic tools needed to build and train new algorithms, he says, researchers creating AIs resort to hearsay, like medieval alchemists. “People gravitate around cargo-cult practices,” relying on “folklore and magic spells,” adds François Chollet, a computer scientist at Google in Mountain View, California.
Relational databases are a commodity now, but they power a much larger fraction of the world’s economy that AI ever will. And no company has a “relational database strategy”.
Text to Image (via) Ridiculously entertaining demo by Cris Valenzuela that feeds any text you type to a neural network that then attempts to generate an image for your text. # 18th August 2018, 5:33 pm
Half of the time when companies say they need “AI” what they really need is a SELECT clause with GROUP BY.
The synthetic voice of synthetic intelligence should sound synthetic. Successful spoofing of any kind destroys trust. When trust is gone, what remains becomes vicious fast.
Originally, however, speech recognition was going to lead to artificial intelligence. Computing pioneer Alan Turing suggested in 1950 that we “provide the machine with the best sense organs that money can buy, and then teach it to understand and speak English.” Over half a century later, artificial intelligence has become prerequisite to understanding speech. We have neither the chicken nor the egg.