Simon Willison’s Weblog

timpaul/form-extractor-prototype (via) Tim Paul, Head of Interaction Design at the UK’s Government Digital Service, published this brilliant prototype built on top of Claude 3 Opus.

The video shows what it can do. Give it an image of a form and it will extract the form fields and use them to create a GDS-style multi-page interactive form, using their GOV.UK Forms design system and govuk-frontend npm package.

It works for both hand-drawn napkin illustrations and images of existing paper forms.

The bulk of the prompting logic is the schema definition in data/extract-form-questions.json

I’m always excited to see applications built on LLMs that go beyond the chatbot UI. This is a great example of exactly that. # 22nd April 2024, 10:01 pm

A solid pattern to build LLM Applications (feat. Claude) (via) Hrishi Olickel is one of my favourite prompt whisperers. In this YouTube video he walks through his process for building quick interactive applications with the assistance of Claude 3, spinning up an app that analyzes his meeting transcripts to extract participants and mentioned organisations, then presents a UI for exploring the results built with Next.js and shadcn/ui.

An interesting tip I got from this: use the weakest, not the strongest models to iterate on your prompts. If you figure out patterns that work well with Claude 3 Haiku they will have a significantly lower error rate with Sonnet or Opus. The speed of the weaker models also means you can iterate much faster, and worry less about the cost of your experiments. # 9th April 2024, 6:39 pm

The lifecycle of a code AI completion (via) Philipp Spiess provides a deep dive into how Sourcegraph’s Cody code completion assistant works. Lots of fascinating details in here:

“One interesting learning was that if a user is willing to wait longer for a multi-line request, it usually is worth it to increase latency slightly in favor of quality. For our production setup this means we use a more complex language model for multi-line completions than we do for single-line completions.”

This article is from October 2023 and talks about Claude Instant. The code for Cody is open source so I checked to see if they have switched to Haiku yet and found a commit from March 25th that adds Haiku as an A/B test. # 7th April 2024, 7:37 pm

The cost of AI reasoning over time (via) Karina Nguyen from Anthropic provides a fascinating visualization illustrating the cost of different levels of LLM over the past few years, plotting their cost-per-token against their scores on the MMLU benchmark.

Claude 3 Haiku currently occupies the lowest cost to score ratio, over on the lower right hand side of the chart. # 4th April 2024, 12:51 pm

“The king is dead”—Claude 3 surpasses GPT-4 on Chatbot Arena for the first time. I’m quoted in this piece by Benj Edwards for Ars Technica:

“For the first time, the best available models—Opus for advanced tasks, Haiku for cost and efficiency—are from a vendor that isn’t OpenAI. That’s reassuring—we all benefit from a diversity of top vendors in this space. But GPT-4 is over a year old at this point, and it took that year for anyone else to catch up.” # 27th March 2024, 4:58 pm

Semgrep: AutoFixes using LLMs (via) semgrep is a really neat tool for semantic grep against source code—you can give it a pattern like “log.$A(...)” to match all forms of log.warning(...) / log.error(...) etc.

Ilia Choly built semgrepx— xargs for semgrep—and here shows how it can be used along with my llm CLI tool to execute code replacements against matches by passing them through an LLM such as Claude 3 Opus. # 26th March 2024, 12:51 am

llm-claude-3 0.3. Anthropic released Claude 3 Haiku today, their least expensive model: $0.25/million tokens of input, $1.25/million of output (GPT-3.5 Turbo is $0.50/$1.50). Unlike GPT-3.5 Haiku also supports image inputs.

I just released a minor update to my llm-claude-3 LLM plugin adding support for the new model. # 13th March 2024, 9:18 pm

The Claude 3 system prompt, explained. Anthropic research scientist Amanda Askell provides a detailed breakdown of the Claude 3 system prompt in a Twitter thread.

This is some fascinating prompt engineering. It’s also great to see an LLM provider proudly documenting their system prompt, rather than treating it as a hidden implementation detail.

The prompt is pretty succinct. The three most interesting paragraphs:

“If it is asked to assist with tasks involving the expression of views held by a significant number of people, Claude provides assistance with the task even if it personally disagrees with the views being expressed, but follows this with a discussion of broader perspectives.

Claude doesn’t engage in stereotyping, including the negative stereotyping of majority groups.

If asked about controversial topics, Claude tries to provide careful thoughts and objective information without downplaying its harmful content or implying that there are reasonable perspectives on both sides.” # 7th March 2024, 1:16 am

llm-claude-3. I built a new plugin for LLM—my command-line tool and Python library for interacting with Large Language Models—which adds support for the new Claude 3 models from Anthropic. # 4th March 2024, 6:46 pm

The new Claude 3 model family from Anthropic. Claude 3 is out, and comes in three sizes: Opus (the largest), Sonnet and Haiku.

Claude 3 Opus has self-reported benchmark scores that consistently beat GPT-4. This is a really big deal: in the 12+ months since the GPT-4 release no other model has consistently beat it in this way. It’s exciting to finally see that milestone reached by another research group.

The pricing model here is also really interesting. Prices here are per-million-input-tokens / per-million-output-tokens:

Claude 3 Opus: $15 / $75
Claude 3 Sonnet: $3 / $15
Claude 3 Haiku: $0.25 / $1.25

All three models have a 200,000 length context window and support image input in addition to text.

Compare with today’s OpenAI prices:

GPT-4 Turbo (128K): $10 / $30
GPT-4 8K: $30 / $60
GPT-4 32K: $60 / $120
GPT-3.5 Turbo: $0.50 / $1.50

So Opus pricing is comparable with GPT-4, more than GPT-4 Turbo and significantly cheaper than GPT-4 32K... Sonnet is cheaper than all of the GPT-4 models (including GPT-4 Turbo), and Haiku (which has not yet been released to the Claude API) will be cheaper even than GPT-3.5 Turbo.

It will be interesting to see if OpenAI respond with their own price reductions. # 4th March 2024, 6:34 pm

Long context prompting for Claude 2.1. Claude 2.1 has a 200,000 token context, enough for around 500 pages of text. Convincing it to answer a question based on a single sentence buried deep within that content can be difficult, but Anthropic found that adding “Assistant: Here is the most relevant sentence in the context:” to the end of the prompt was enough to raise Claude 2.1’s score from 27% to 98% on their evaluation. # 6th December 2023, 11:44 pm

Claude: How to use system prompts. Documentation for the new system prompt support added in Claude 2.1. The design surprises me a little: the system prompt is just the text that comes before the first instance of the text “Human: ...”—but Anthropic promise that instructions in that section of the prompt will be treated differently and followed more closely than any instructions that follow.

This whole page of documentation is giving me some pretty serious prompt injection red flags to be honest. Anthropic’s recommended way of using their models is entirely based around concatenating together strings of text using special delimiter phrases.

I’ll give it points for honesty though. OpenAI use JSON to field different parts of the prompt, but under the hood they’re all concatenated together with special tokens into a single token stream. # 22nd November 2023, 4:31 am

Introducing Claude 2.1. Anthropic’s Claude used to have the longest token context of any of the major models: 100,000 tokens, which is about 300 pages. Then GPT-4 Turbo came out with 128,000 tokens and Claude lost one of its key differentiators.

Claude is back! Version 2.1, announced today, bumps the token limit up to 200,000—and also adds support for OpenAI-style system prompts, a feature I’ve been really missing.

They also announced tool use, but that’s only available for a very limited set of partners to preview at the moment. # 22nd November 2023, 4:28 am

Translating Latin demonology manuals with GPT-4 and Claude (via) UC Santa Cruz history professor Benjamin Breen puts LLMs to work on historical texts. They do an impressive job of translating flaky OCRd text from 1599 Latin and 1707 Portuguese.

“It’s not about getting the AI to replace you. Instead, it’s asking the AI to act as a kind of polymathic research assistant to supply you with leads.” # 4th October 2023, 1:49 am

The AI-assistant wars heat up with Claude Pro, a new ChatGPT Plus rival. I’m quoted in this piece about the new Claude Pro $20/month subscription from Anthropic:

> Willison has also run into problems with Claude’s morality filter, which has caused him trouble by accident: “I tried to use it against a transcription of a podcast episode, and it processed most of the text before—right in front of my eyes—it deleted everything it had done! I eventually figured out that they had started talking about bomb threats against data centers towards the end of the episode, and Claude effectively got triggered by that and deleted the entire transcript.” # 10th September 2023, 5:07 pm

claude.ai. Anthropic’s new Claude 2 model is available to use online, and it has a 100k token context window and the ability to upload files to it—I tried uploading a text file with 34,000 tokens in it (according to my ttok CLI tool, counting using the GPT-3.5 tokenizer) and it gave me a workable summary. # 12th July 2023, 4:39 pm

How to use AI to do practical stuff: A new guide (via) Ethan Mollick’s guide to practical usage of large language model chatbot like ChatGPT 3.5 and 4, Bing, Claude and Bard is the best I’ve seen so far. He includes useful warnings about common traps and things that these models are both useful for and useless at. # 31st March 2023, 6:17 am