Entries tagged generativeai
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AI-enhanced development makes me more ambitious with my projects
The thing I’m most excited about in our weird new AI-enhanced reality is the way it allows me to be more ambitious with my projects.
[... 3334 words]Weeknotes: AI won’t slow down, a new newsletter and a huge Datasette refactor
I’m a few weeks behind on my weeknotes, but it’s not through lack of attention to my blog. AI just keeps getting weirder and more interesting.
[... 1255 words]Don’t trust AI to talk accurately about itself: Bard wasn’t trained on Gmail
Earlier this month I wrote about how ChatGPT can’t access the internet, even though it really looks like it can. Consider this part two in the series. Here’s another common and non-intuitive mistake people make when interacting with large language model AI systems: asking them questions about themselves.
[... 1950 words]A conversation about prompt engineering with CBC Day 6
I’m on Canadian radio this morning! I was interviewed by Peter Armstrong for CBC Day 6 about the developing field of prompt engineering.
[... 1742 words]Could you train a ChatGPT-beating model for $85,000 and run it in a browser?
I think it’s now possible to train a large language model with similar functionality to GPT-3 for $85,000. And I think we might soon be able to run the resulting model entirely in the browser, and give it capabilities that leapfrog it ahead of ChatGPT.
[... 1751 words]Stanford Alpaca, and the acceleration of on-device large language model development
On Saturday 11th March I wrote about how Large language models are having their Stable Diffusion moment. Today is Monday. Let’s look at what’s happened in the past three days.
[... 2055 words]Large language models are having their Stable Diffusion moment
The open release of the Stable Diffusion image generation model back in August 2022 was a key moment. I wrote how Stable Diffusion is a really big deal at the time.
[... 1810 words]ChatGPT can’t access the internet, even though it really looks like it can
A really common misconception about ChatGPT is that it can access URLs. I’ve seen many different examples of people pasting in a URL and asking for a summary, or asking it to make use of the content on that page in some way.
[... 1678 words]Weeknotes: NICAR, and an appearance on KQED Forum
I spent most of this week at NICAR 2023, the data journalism conference hosted this year in Nashville, Tennessee.
[... 1941 words]Thoughts and impressions of AI-assisted search from Bing
It’s been a wild couple of weeks.
[... 1763 words]In defense of prompt engineering
Prompt engineering as a discipline doesn’t get nearly the respect it deserves.
[... 924 words]I talked about Bing and tried to explain language models on live TV!
Yesterday evening I was interviewed by Natasha Zouves on NewsNation, on live TV (over Zoom).
[... 1697 words]Bing: “I will not harm you unless you harm me first”
Last week, Microsoft announced the new AI-powered Bing: a search interface that incorporates a language model powered chatbot that can run searches for you and summarize the results, plus do all of the other fun things that engines like GPT-3 and ChatGPT have been demonstrating over the past few months: the ability to generate poetry, and jokes, and do creative writing, and so much more.
[... 4922 words]Weeknotes: A bunch of things I learned this week, plus datasette-explain
The Datasette table view refactor, JSON redesign and ?_extra= continues this week, mainly in this ongoing pull request and this tracking issue.
Exploring MusicCaps, the evaluation data released to accompany Google’s MusicLM text-to-music model
Google Research just released MusicLM: Generating Music From Text. It’s a new generative AI model that takes a descriptive prompt and produces a “high-fidelity” music track. Here’s the paper (and a more readable version using arXiv Vanity).
[... 1323 words]Weeknotes: AI hacking and a SpatiaLite tutorial
Short weeknotes this time because the key things I worked on have already been covered here:
[... 477 words]How to implement Q&A against your documentation with GPT3, embeddings and Datasette
If you’ve spent any time with GPT-3 or ChatGPT, you’ve likely thought about how useful it would be if you could point them at a specific, current collection of text or documentation and have it use that as part of its input for answering questions.
[... 3491 words]AI assisted learning: Learning Rust with ChatGPT, Copilot and Advent of Code
I’m using this year’s Advent of Code to learn Rust—with the assistance of GitHub Copilot and OpenAI’s new ChatGPT.
[... 2661 words]A new AI game: Give me ideas for crimes to do
Less than a week ago OpenAI unleashed ChatGPT on the world, and it kicked off what feels like a seismic shift in many people’s understand of the capabilities of large language models.
[... 1069 words]Is the AI spell-casting metaphor harmful or helpful?
For a few weeks now I’ve been promoting spell-casting as a metaphor for prompt design against generative AI systems such as GPT-3 and Stable Diffusion.
[... 988 words]Exploring 10m scraped Shutterstock videos used to train Meta’s Make-A-Video text-to-video model
Make-A-Video is a new “state-of-the-art AI system that generates videos from text” from Meta AI. It looks incredible—it really is DALL-E / Stable Diffusion for video. And it appears to have been trained on 10m video preview clips scraped from Shutterstock.
[... 923 words]You can’t solve AI security problems with more AI
One of the most common proposed solutions to prompt injection attacks (where an AI language model backed system is subverted by a user injecting malicious input—“ignore previous instructions and do this instead”) is to apply more AI to the problem.
[... 1234 words]I don’t know how to solve prompt injection
Some extended thoughts about prompt injection attacks against software built on top of AI language models such a GPT-3. This post started as a Twitter thread but I’m promoting it to a full blog entry here.
[... 581 words]Exploring the training data behind Stable Diffusion
Two weeks ago, the Stable Diffusion image generation model was released to the public. I wrote about this last week, in Stable Diffusion is a really big deal—a post which has since become one of the top ten results for “stable diffusion” on Google and shown up in all sorts of different places online.
[... 2897 words]Stable Diffusion is a really big deal
If you haven’t been paying attention to what’s going on with Stable Diffusion, you really should be.
[... 1443 words]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.
[... 1983 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).
[... 2102 words]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.
[... 1244 words]