Presented by:

Ken Kahn

from University of Oxford

Spoken instructions (see the comments) that are turned into Snap! movement scripts
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Using the web services library one can create blocks that send prompts to GPT-3, GPT-4, Cohere, Jurrassic 1, and other large language models. These blocks report the "completions" returned by these API calls. I'll present five sample projects using these blocks:

Conversations with and between personas using language models

Using Large Language Models to simulate debates

The Automated Generation of Illustrated Stories

Using large language models to control a Logo turtle

Demonstrating that GPT-3 can play Tic Tac Toe

Unlike using a large language model "playground" where you can enter text and receive completions, a programmatic use of large language models enables one to integrate the completions into a larger task. For example, the language model can be asked to generate a story and then asked to generate suggestions for illustration prompts for each paragraph and then contact a text-to-image model to receive costumes to use in an illustrated version of the story. And the story and illustrations can be co-developed by the user and the model. For example, the model can be prompted to suggest changes to a story, the user can approve or reject, and then the changes are implemented by another request to the model.

20 min
Snap!Con 2023