1,004 posts tagged “llms”
Large Language Models (LLMs) are the class of technology behind generative text AI systems like OpenAI's ChatGPT, Google's Gemini and Anthropic's Claude.
2022
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.
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karpathy/minGPT (via) A “minimal PyTorch re-implementation” of the OpenAI GPT training and inference model, by Andrej Karpathy. It’s only a few hundred lines of code and includes extensive comments, plus notebook demos.
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.
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]Weeknotes: Datasette Cloud ready to preview
I made an absolute ton of progress building Datasette Cloud on Fly this week, and also had a bunch of fun playing with GPT-3.
[... 370 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.
[... 1,244 words]2020
How GPT3 Works—Visualizations and Animations. Nice essay full of custom animations illustrating how GPT-3 actually works.
When I was curating my generated tweets, I estimated 30-40% of the tweets were usable comedically, a massive improvement over the 5-10% usability from my GPT-2 tweet generation. However, a 30-40% success rate implies a 60-70% failure rate, which is patently unsuitable for a production application.
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.