Teaching AI simulations? Get free credits for your students and research projects.
We have ready-to-use materials for teaching LLM-based simulations with our open-source tools, and free credits for getting started. Earn more free credits by sharing your referral code!
Are you an instructor thinking about adding an LLM module to your course this fall? Or a student interested in learning how to do AI simulations as cheaply as possible? Read on!
Free research tools
Our open-source tools let you simulate surveys using AI agent personas and popular language models of your choice. Results are returned to you as formatted datasets specified by the question types that you choose (free text, multiple choice, linear scale, matrix, etc.), with columns of information about all the components of your survey: agent traits, model parameters, question details, answers, tokens, API costs, raw responses, and more.
The tools come with built-in methods for analyzing results, and also let you collect and compare responses from humans as needed. When you run your simulations at Expected Parrot your surveys and results are cached automatically, so you can retrieve and share them to let others reproduce and build on your work at no cost. You also get free credits for API calls to LLMs.
Some quick links:
EDSL package at GitHub: https://github.com/expectedparrot/edsl
EDSL documentation: https://docs.expectedparrot.com
Create an account: https://www.expectedparrot.com/login
Getting started: https://www.expectedparrot.com/getting-started
Getting started
The EDSL package is available at GitHub and PyPI and is free for anyone to use. Our docs page has tutorials for getting started and modifiable demo notebooks for exploring use cases and experimenting with AI agents and LLMs. You can run simulations on your own computer or create an account to run surveys at Expected Parrot and share projects and results with others.
Free credits
Your Expected Parrot account comes with $25 in credits for sending surveys to LLMs, and a unified key that provides access to all available models. You can also use your own keys for LLMs, and grant access to other users without sharing keys directly:
Credits are deducted from your account to cover API calls to LLMs using your Expected Parrot key. You can purchase more credits at your Credits page, and earn free credits by sharing your referral code. Each time someone signs up with your code and runs a first survey job we automatically add 1,000 ($10) in credits to your account:
(If you haven’t signed up yet, please feel free to use our friend Luke’s referral code :)
Teaching materials
If you’re looking for ready-to-use teaching materials:
We love making customized content for classes and use cases!
Get it touch anytime to let us know what you need.
Our documentation page provides a starter tutorial and notebooks for a variety of use cases.
Our blog has examples of methods and use cases too, including:
We have slides for teaching EDSL basics that we’re happy to share! Send us a message at [email protected] or post a message at our Discord channel.
Example class project
NYU researcher James Traina recently designed an MBA case study using EDSL to simulate complex market research scenarios. The exercise puts students in the role of product strategy managers at Thunder Bank, tasked with justifying a $75 million branch transformation using AI-powered customer insights. Read what the students thought about it!
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