It turns out that I’ve been writing about Generative AI without even realizing there was something called Generative AI, such as articles about the robot artist Ai-Da, the AI image creator DALL-E, or patent protection for AI inventors. Generative AI refers to AI that strives not just to process and synthesize data but to actually be creative. It’s starting to both become more widespread and to attract serious attention from investors.
James Currier of investment firm NFX sees “Generative Tech” as the next big thing: “If crypto hadn’t happened, we’d probably be calling THIS Web3.” He distinguishes Generative AI from Generative Tech as:
Some have called it “Generative AI,” but AI is only half of the equation. AI models are the enabling base layers of the stack. The top layers will be thousands of applications. Generative Tech is about what will actually touch us – what you can do with AI as a partner.
He predicts Generative Tech will generate “trillions of dollars of value.” I’m hoping that healthcare is paying attention.
I can’t believe I somehow missed when OpenAI introduced DALL-E in January 2021 – a neural network that could “generate images from text descriptions” — so I’m sure not going to miss now that OpenAI has unveiled DALL-E 2. As they describe it, “DALL-E 2 is a new AI system that can create realistic images and art from a description in natural language.” The name, by the way, is a playful combination of the animated robot WALL-E and the idiosyncratic artist Salvator Dali.
This is not your father’s AI. If you think it’s just about art, think again. If you think it doesn’t matter for healthcare, well, you’ve been warned.
Here are further descriptions of what OpenAI is claiming:
“DALL·E 2 can create original, realistic images and art from a text description. It can combine concepts, attributes, and styles.
DALL·E 2 can make realistic edits to existing images from a natural language caption. It can add and remove elements while taking shadows, reflections, and textures into account.
DALL·E 2 can take an image and create different variations of it inspired by the original.”
Here’s their video:
I’ll leave it to others to explain exactly how it does all that, aside from saying it uses a process called diffusion, “which starts with a pattern of random dots and gradually alters that pattern towards an image when it recognizes specific aspects of that image.” The end result is that, relative to DALL-E, DALL-E 2 “generates more realistic and accurate images with 4x greater resolution.”