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Items tagged openai, llms

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Browse the BBC In Our Time archive by Dewey decimal code. Matt Webb built Braggoscope, an alternative interface for browsing the 1,000 episodes of the BBC’s In Our Time dating back to 1998, organized by Dewey decimal system and with related episodes calculated using OpenAI embeddings and guests and reading lists extracted using GPT-3. “Using GitHub Copilot to write code and calling out to GPT-3 programmatically to dodge days of graft actually brought tears to my eyes.” # 13th February 2023, 4:03 pm

OpenAI Cookbook: Techniques to improve reliability (via) “Let’s think step by step” is a notoriously successful way of getting large language models to solve problems, but it turns out that’s just the tip of the iceberg: this article includes a wealth of additional examples and techniques that can be used to trick GPT-3 into being a whole lot more effective. # 21st January 2023, 5:15 am

Weeknotes: AI hacking and a SpatiaLite tutorial

Short weeknotes this time because the key things I worked on have already been covered here:

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I Taught ChatGPT to Invent a Language (via) Dylan Black talks ChatGPT through the process of inventing a new language, with its own grammar. Really fun example of what happens when someone with a deep understanding of both the capabilities of language models and some other field (in this case linguistics) can achieve with an extended prompting session. # 6th December 2022, 7:30 pm

The primary problem is that while the answers which ChatGPT produces have a high rate of being incorrect, they typically look like they might be good and the answers are very easy to produce. There are also many people trying out ChatGPT to create answers, without the expertise or willingness to verify that the answer is correct prior to posting. Because such answers are so easy to produce, a large number of people are posting a lot of answers. The volume of these answers (thousands) and the fact that the answers often require a detailed read by someone with at least some subject matter expertise in order to determine that the answer is actually bad has effectively swamped our volunteer-based quality curation infrastructure.

StackOverflow Temporary policy: ChatGPT is banned # 6th December 2022, 12:16 am

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.

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Building A Virtual Machine inside ChatGPT (via) Jonas Degrave presents a remarkable example of a creative use of ChatGPT: he prompts it to behave as a if it was a Linux shell, then runs increasingly complex sequences of commands against it and gets back surprisingly realistic results. By the end of the article he’s getting it to hallucinate responses to curl API requests run against imagined API versions of itself. # 5th December 2022, 1:43 am

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.

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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.

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Getting tabular data from unstructured text with GPT-3: an ongoing experiment (via) Roberto Rocha shows how to use a carefully designed prompt (with plenty of examples) to get GPT-3 to convert unstructured textual data into a structured table. # 5th October 2022, 3:03 am

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.

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Twitter pranksters derail GPT-3 bot with newly discovered “prompt injection” hack. I’m quoted in this Ars Technica article about prompt injection and the Remoteli.io Twitter bot. # 16th September 2022, 6:33 pm

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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Prompt injection attacks against GPT-3

Riley Goodside, yesterday:

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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. # 17th August 2022, 7:06 pm

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

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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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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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