Simon Willison’s Weblog

Subscribe
Atom feed for llms

789 items 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

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.

[... 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

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.

[... 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.

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

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.

Max Woolf

# 18th July 2020, 7:33 pm / machine-learning, max-woolf, llms, ai, gpt-2

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