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793 items tagged “generative-ai”

2022

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.

# 2nd August 2022, 9:12 pm / openai, dalle, generative-ai

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.

# 14th July 2022, 11:26 pm / openai, dalle, ai, prompt-engineering, generative-ai

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.”

# 10th July 2022, 4:33 am / openai, gpt-3, prompt-engineering, generative-ai, llms

Using GPT-3 to explain how code works

Visit 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.

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First impressions of DALL-E, generating images from text

Visit 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).

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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.

# 23rd June 2022, 6:05 pm / machine-learning, ai, google, dalle, generative-ai

How to use the GPT-3 language model

Visit 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.

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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.

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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.

# 5th January 2021, 8:31 pm / machine-learning, ai, openai, dalle, generative-ai

2020

How GPT3 Works—Visualizations and Animations. Nice essay full of custom animations illustrating how GPT-3 actually works.

# 30th July 2020, 12:58 am / machine-learning, ai, gpt-3, generative-ai, llms

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.

# 18th July 2020, 7:29 pm / machine-learning, max-woolf, gpt-3, ai, openai, generative-ai, llms

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.

# 31st January 2020, 2:13 am / llms, generative-ai, ai, max-woolf, gpt-2

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.

# 17th April 2018, 8:54 pm / machine-learning, ai, generative-ai