Join the effort to make AI orchestration interpretable from the ground up—where judge models reveal their reasoning process and routing decisions become windows into AI decision-making!

This weekend-long collaborative research event provides a structured environment to develop novel economic frameworks, models, and insights that can inform our understanding of AI's transformative potential.

The purpose of this hackathon is to provide a space for students to advocate for solutions to AI policy issues that many lawmakers and technologists are thinking about, both in California and beyond.

Join the Georgia Tech AI Governance Hackathon and shape the future of AI policy! Collaborate with peers, experts, and mentors to develop innovative solutions for critical AI governance challenges. Whether you're a tech enthusiast, policy wonk, or ethical thinker, your ideas can make a real impact. Don't miss this opportunity to contribute to global AI safety and elevate Georgia Tech's role in the field. Register now and be part of the change!

How is AGI trying to manipulate you? Which red flags should you check for when using chatbots? How can AI agents reduce human autonomy in favor of profit, power, or self-preservation?

Join us in advancing the critical field of AI control through collaborative innovation. Together, we can develop more robust techniques to ensure AI systems remain safe and aligned, even as they become more capable.

Shape the future of safe and ethical AI development! Whether you're a researcher, developer, policy enthusiast, or new to AI safety - join us for an empowering weekend of innovation and collaboration. No prior AI safety experience required. Together, we can build the foundational tools and frameworks needed for responsible AI development.

Join us during this weekend where we will join you to kick off an ambitious journey into AI safety and security with other aligned and talented individuals from both science and business. We aim to bring solution-oriented deep tech to AI safety. This is your chance to literally change the world.

Join us for creating for the near future where our infrastructure is embedded with realistic levels of intelligence (i.e., only mildly creative but widely adopted) yet full of novel, wild design paradigms anyway.

Whether you're an AI researcher, a curious developer, or passionate about making AI systems more transparent and controllable, this hackathon is for you. As a participant, you will: Collaborate with experts to create novel AI observability tools Learn about mechanistic interpretability from industry leaders Contribute to solving real-world challenges in AI safety and reliability Compete for prizes and the opportunity to influence the future of AI development Register now and be part of the movement towards more transparent, reliable, and beneficial AI systems. We provide access to Goodfire's SDK/API and research preview playground, enabling participation regardless of prior experience with AI observability.

The purpose of this hackathon is to foster innovative policy solutions addressing the complex landscape of AI governance and safety, with a particular focus on practical implementations and regulatory frameworks.

Join us for a weekend of collaboration, problem-solving, and networking as you work with like-minded peers to tackle real-world policy challenges related to AI. Participants will submit either a policy paper or a technological product. This opportunity is a great way to build your professional network and explore new career paths!

During this hackathon, we'll put our research skills to the test by diving deep into the world of agents:

Hackathon for working on interpretability projects during ARENA v4. These could be training or interpreting SAEs, finding circuits in GPT2-Small, training & interpreting toy transformer models on algorithmic tasks, building visualization software / infra for interpretability research, or anything else you can think of!

The Concordia Contest is your opportunity to dive into the exciting world of cooperative AI. Whether you're an experienced AI researcher, a curious developer, or someone passionate about ensuring AI benefits humanity, this event is for you

Join us during this weekend where we will join you to kick off an ambitious journey into AI safety and security with other aligned and talented individuals from both science and business. We aim to bring solution-oriented deep tech to AI safety. This is your chance to literally change the world.

As frontier AI systems become rapidly more powerful and general, and as their risks become more pressing, it’s increasingly important for key decision-makers and the public to understand their capabilities. Let’s bring these insights out of dusty Arxiv papers and build visceral, immediately engaging demos!

Are you ready to reshape the future of alignment research? Join us for an exhilarating weekend at the Research Augmentation Hackathon, where we'll develop innovative tools and methods to accelerate progress in this critical field!

re you fascinated by the incredible advancements in AI? As AI becomes smarter and more powerful, it's essential that we make sure it always tells the truth and doesn't trick people. Imagine if an AI could manipulate narratives or try to scheme—that could lead to serious problems!

The Computational Mechanics Interpretability Hackathon takes a new approach to neural network interpretability based on a well-developed and principled framework called Computational Mechanics. Computational Mechanics formally describes the information processing and computational structure necessary for prediction. Come join us to contribute to this exciting new research program and your chance at winning cash prizes!

Inspired by the SafeBench competition, our hackathon brings together AI researchers and developers to create cutting-edge benchmarks that measure and mitigate AI risks.

Despite the many potential benefits of the technology (such as equalizing opportunity, creating wealth, and improving coordination), we are also facing significant risks from AI.

Join us at the LISA offices for InterpVis, the first mechanistic interpretability hackathon with a focus on creating visualisations.

Join us for weekends focused on LLM Psychology.

Join our groundbreaking hackathon to create tests that identify when AI can copy itself - a critical safety risk. Your innovative tasks could shape global AI standards. Make your mark, potentially collaborate with a prominent AI safety lab, and win big. Sign up now for an impactful weekend!

Securing multi-agent systems in deployment

Design, develop, guide, and predict AI governance in a three day research sprint

Expose the unknown unknowns of AI model behavior

Co-author research opportunity with Cooperative AI Foundation

Safeguarding human agency against A(G)I

Join us for the Distillation Writathon where you are tasked with writing more digestible versions of existing literature in AI safety research and theory!

Welcome to the research hackathon to devise methods for evaluating the risks of deployed language models and AI. With the societal-scale risks associated with creating new types of intelligence, we need to understand and control the capabilities of such models.

Join us to understand the internals of language models and ML systems!

Participate in the Alignment Jam on safety benchmarks to spend a weekend with AI safety researchers to formulate and demonstrate new ideas in measuring the safety of artificially intelligent systems.

Join us for the Distillation Writathon where you are tasked with writing more digestible versions of existing literature in AI safety research and theory!

Join us for this month's Alignment Jam as investigate verifiable safety!

Join us for this month's Alignment Jam to investigate how we can both formally and informally verify the safety of machine learning systems!

We focus on interpreting the innards of neural networks using methods developed from mechanistic interpretability

A weekend for exploring AI & society!

Join us for the fifth Alignment Jam where we get to spend 48 hours of intense research on how we can measure and monitor the safety of large-scale machine learning models. Work on safety benchmarks, models detecting faults in other models, self-monitoring systems , and  so much else!

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 #1

AI Testing

48 hours intense research in interpretability, the modern AI neuroscience.

Alignment Jam #1