Co-Director Esben gives us his thoughts on how impactful donating to Apart Research is.

Our new Apart Lab Studio is designed to bridge the gap between weekend hackathon projects and a fully-fledged AI Safety research career.

This post details the top projects from our technical AI safety startups hackathon where researchers and entrepreneurs joined from across the world.

Read about how Big Tech's AI race leaves safety in the dust, non-profits struggle to keep up, and the challenges for-profit AI safety ventures must overcome to leverage resources and make a real impact.

This June, Apart Research and Apollo Research joined forces to host the Deception Detection Hackathon, bringing together students, researchers and engineers from around the world to tackle one of the most pressing challenges in AI safety: Preventing AI from deceiving humans.

A few months ago, Apart, in collaboration with METR, ran the Code Red Hackathon to engage talent across the world in impactful AI safety research. Our 128 participants submitted more than 200 project ideas, 100 detailed task specifications, and more than 20 complete implementations! In this post, we also get an exclusive interview with one of the winners.

Research hackathons are an amazing way to dive into a new field, collaborate with passionate people, and create impactful projects in just a short weekend. Having organized and participated in several AI safety hackathons with Apart Research, here are some key tips to help you get the most out of your hackathon experience:

Participate online or in-person on the weekend 3rd to 5th May in an exciting and intense AI safety research hackathon focused on demonstrating and extrapolating risks to democracy from real-life threat models. We invite researchers, cybersecurity professionals, and governance experts to join but it is open for everyone, and we will introduce starter code templates to help you kickstart your team's projects. Join at apartresearch.com/event/ai-democracy.

In this collaboration between METR and Apart, you get the chance to contribute directly to model evaluations research. Take part in the Code Red Hackathon, where you can earn money, connect with experts, and help create tasks to evaluate frontier AI systems.

Organizing a hackathon can bring a unique and exciting energy to people interested in AI safety research! This post summarizes how you can organize a successful hackathon.

AI development attracts more than $67 billion in yearly investments, contrasting sharply with the $250 million allocated to AI safety. This gap suggests there's a large opportunity for AI safety to tap into the commercial market. The big question then is, how do you close that gap?

With the research hackathon, your journey into the world of AI safety is definitely not over! Besides the chance to join the Apart Lab Fellowship, we have collected a bunch of resources here for you to dive even deeper into the field!

There are many reasons to run a hackathon but some of the main ones are that hackathons are an amazing way to engage the local groups in AI security research and create a sense of community. The participants get an amazing practical research experience and can show the finished projects off to potential employers and colleagues, and it's a really fun way to spend a weekend.

Written by Neel Nanda, who previously worked on mech interp under Chris Olah at Anthropic, who is currently a researcher on the DeepMind mechanistic interpretability team.

Check out the top projects from the "Scale Oversight" hackathon hosted in February 2023: Playing games with LLMs, scaling of prompt specificity, and more.

See the winning projects from the AI testing hackathon held in December 2022: Trojan networks, unsupervised latent knowledge representation, and token loss trajectories to target interpretability methods.

See winning projects from the language model hackathon hosted November 2022: GPT-3 shows sycophancy, OpenAI's flagging is biased, and truthfulness is sensitive to prompt design.

Read the winning projects from the interpretability hackathon hosted in November 2022: Automatic interpretability, backup backup name mover heads, and "loud facts" in memory editing.