1,246 posts tagged “generative-ai”
Machine learning systems that can generate new content: text, images, audio, video and more.
2022
Stable Diffusion Public Release (via) New AI just dropped. Stable Diffusion is similar to DALL-E, but completely open source and with a CC0 license applied to everything it generates. I have a Twitter thread (the via) link of comparisons I’ve made between its output and my previous DALL-E experiments. The announcement buries the lede somewhat: to try it out, visit beta.dreamstudio.ai—which you can use for free at the moment, but it’s unclear to me how billing is supposed to work.
Show HN: A new way to use GPT-3 to generate code (and everything else).
Riley Goodside is my favourite Twitter follow for GPT-3 tips. Here he describes a powerful prompt pattern he's designed which lets you generate extremely complex code output by asking GPT-3 to fill in $$areas like this$$ with different patterns, then stitch them together into full HTML or other source code files. It's really clever.
Building games and apps entirely through natural language using OpenAI’s code-davinci model. A deeply sophisticated example of using prompts to generate entire working JavaScript programs and games using the new code-davinci OpenAI model.
How I Used DALL·E 2 to Generate The Logo for OctoSQL (via) Jacob Martin gives a blow-by-blow account of his attempts at creating a logo for his OctoSQL project using DALL-E, spending $30 of credits and making extensive use of both the “variations” feature and the tool that lets you request modifications to existing images by painting over parts you want to regenerate. Really interesting to read as an example of a “real world” DALL-E project.
The DALL·E 2 Prompt Book (via) This is effectively DALL-E: The Missing Manual: an 81 page PDF book that goes into exhaustive detail about how to get the most out of DALL-E through creative prompt design.
GPT-3 prompt for spotting nonsense questions (via) In response to complaints that GPT-3 will happily provide realistic sounding answers to nonsense questions, rictic recommends the following prompt:
I'll ask a series of questions. If the questions are nonsense, answer "yo be real", if they're a question about something that actually happened, answer them.
Using GPT-3 to explain how code works
One of my favourite uses for the GPT-3 AI language model is generating explanations of how code works. It’s shockingly effective at this: its training set clearly include a vast amount of source code.
[... 1,983 words]First impressions of DALL-E, generating images from text
I made it off the DALL-E waiting list a few days ago and I’ve been having an enormous amount of fun experimenting with it. Here are some notes on what I’ve learned so far (and a bunch of example images too).
[... 2,102 words]How Imagen Actually Works. Imagen is Google’s new text-to-image model, similar to (but possibly even more effective than) DALL-E. This article is the clearest explanation I’ve seen of how Imagen works: it uses Google’s existing T5 text encoder to convert the input sentence into an encoding that captures the semantic meaning of the sentence (including things like items being described as being on top of other items), then uses a trained diffusion model to generate a 64x64 image. That image is passed through two super-res models to increase the resolution to the final 1024x1024 output.
How to use the GPT-3 language model
I ran a Twitter poll the other day asking if people had tried GPT-3 and why or why not. The winning option, by quite a long way, was “No, I don’t know how to”. So here’s how to try it out, for free, without needing to write any code.
[... 838 words]A Datasette tutorial written by GPT-3
I’ve been playing around with OpenAI’s GPT-3 language model playground for a few months now. It’s a fascinating piece of software. You can sign up here—apparently there’s no longer a waiting list.
[... 1,244 words]2021
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.
2020
How GPT3 Works—Visualizations and Animations. Nice essay full of custom animations illustrating how GPT-3 actually works.
Tempering Expectations for GPT-3 and OpenAI’s API. Insightful commentary on GPT-3 (which is producing some ridiculously cool demos at the moment thanks to the invite-only OpenAI API) from Max Woolf.
gpt2-headlines.ipynb. My earliest experiment with GPT-2, using gpt-2-simple by Max Woolf to generate new New York Times headlines based on a GPT-2 fine-tuned against headlines from different decades of that newspaper.
2018
Text Embedding Models Contain Bias. Here’s Why That Matters (via) Excellent discussion from the Google AI team of the enormous challenge of building machine learning models without accidentally encoding harmful bias in a way that cannot be easily detected.