[OPEN Bounty] - Benchmark our weightless NNs on a new dataset

[mi3law]

At AO Labs, we’re building AI systems that can learn after training. Post-training learning is a new frontier in AI, quite underexplored, and it’s an open question where continuous learning excels.

We’ve applied our weightless neural network agent to a range of datasets, from MNIST for image recognition to sentiment analysis to ARC-AGI. Now, we’re opening the door for developers to explore new datasets that our agents can be applied to; our team is ready to support intrepid developers ready to build the future.

Fork one of our apps to get started. Here is a link to our MNIST app for reference; more demos including ARC-AGI here.

Reward

$300

Project Details & Scope

• Identify and source a public dataset that is compatible with our agents’ functionality
• The dataset must be new (not one our agents have previously been applied to)
• You can double-check with us about the validity of the dataset before beginning the following step
• Build an app that runs AO agents on the dataset; a streamlit app like our MNIST app works well

Ready?

Should you work on this project, the AO team is here to support you throughout your development (addressing questions, providing more context, even pair-programming with you, etc.)-- say hi on discord or meet with our founder Ali here.

Our docs can be found at docs.aolabs.ai.

To take on this project, please comment on this issue or email [email protected].