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Jan 20 - 23, 2023Online and in person

Mechanistic Interpretability Hackathon

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Machine learning is becoming an increasingly important part of our lives and researchers are still working to understand how neural networks represent the world.

Overview

Machine learning is becoming an increasingly important part of our lives and researchers are still working to understand how neural networks represent the world.

Alignment Jam hackathons

Join us in this iteration of the Alignment Jam research hackathons to spend 48 hour with fellow engaged researchers and engineers in machine learning on engaging in this exciting and fast-moving field!

Join the Discord where all communication will happen. Check out research project ideas for inspiration and the in-depth starter resources.

Using mechanistic interpretability, we will dive deep into how neural networks think and do. We work towards reverse-engineering the information processing of artificial intelligence!

We provide you with the best starter templates that you can work from so you can focus on creating interesting research instead of browsing Stack Overflow. Check the resources out here. You're very welcome to check out some of the ideas already posted!

Local groups

If you are part of a local machine learning or AI safety group, you are very welcome to set up a local in-person site to work together with people on this hackathon! We will have several across the world (list upcoming) and hope to increase the amount of local spots. Sign up to run a jam site here.

You will work in groups of 2-6 people within our hackathon GatherTown and in the in-person event hubs.

Resources

Check out the Quickstart Guide for Mechanistic Interpretability

Mechanistic interpretability is a field focused on reverse-engineering neural networks. This can both be how Transformers do a very specific task and how models suddenly improve. Check out our speaker Neel Nanda's 200+ research ideas in mechanistic interpretability.

Speakers

  • Esben Kran

    Esben Kran

    Organizer and Keynote Speaker

    Esben is the founder of Apart Research, which he launched at age 22 after leaving grad school. Apart accelerates AI safety research worldwide, producing 20+ papers, award-winning benchmarks like DarkBench, and engaging 4,000+ hackers in research sprints.

    Recently co-launched Seldon to fund critical infrastructure for humanity's future, with first investments in Andon Labs, Lucid Computing, Workshop Labs, and Asymmetric Security.

  • Neel Nanda

    Neel Nanda

    Speaker & Judge

    Team lead for the mechanistic interpretability team at Google Deepmind and a prolific advocate for open source interpretability research.

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  1. Sprint

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  2. Apart Fellowship

    6 to 16 weeks on your own project, with a research project manager, compute and publication support.