Hide table of contents

We’re excited to announce Cavendish Labs, a new research institute in Vermont focused on AI safety and pandemic prevention! We’re founding a community of researchers who will live together and work on the world’s most pressing problems.

Uh, why Vermont?

It’s beautiful; it has one of the cheapest costs of living in the United States; there’s lots of great people; it’s only a few hours away from Boston, NYC, and Montreal. There’s even a train that goes there from Washington D.C.! A few of us briefly lived in Vermont during the pandemic, and we found it to be a fantastic place to live, think, and work. Each season brings with it a new kind of beauty to the hills. There are no barriers to a relaxing walk in the woods. There's practically no light pollution, so the cosmos is waiting outside the door whenever you need inspiration.

A view of the village of Cavendish; the fire station is on the left.
A view of Cavendish village; the town offices and fire station are on the left.

What are you going to be researching?

We have a few research interests:

1. AI Alignment. How do we make sure that AI does what we want? We’ve spent some time thinking about ELK and inverse scaling; however, we think that AGI will most likely be achieved through some sort of model-based RL framework, so that is our current focus. For instance, we know how to induce provable guarantees of behavior in supervised learning; could we do something similar in RL?

2. Pandemic prevention. There’s been a lot of talk about the potential of Far-UVC for ambient disinfection. Understanding why it works on a molecular level, and whether it works safely, is key for developing broad-spectrum pandemic prevention tools.

3. Diagnostic development. We're interested in designing a low-cost and simple-to-use platform for LAMP reactions so that generalized diagnostic capabilities are more widespread. We envision a world where it is both cheap and easy to run a panel of tests so one can swiftly determine the exact virus behind an infection.

How’s this organized?

We'll be living and working on different floors of the same building—some combination of a small liberal arts college and research lab. To ensure we’re not too isolated, we’ll visit Boston at least once a month, and invite a rotating group of visitors to work with us, while maintaining collaborations with researchers around the world.

Sounds interesting!

We’re actively searching for collaborators in our areas of interest; if this sounds like you, send us an email at hello@cavendishlabs.org! Our space in Vermont isn’t ready until late spring, so in the meantime we’ll be located in Berkeley and Rhode Island.

At the same time, we’re looking for visiting scholars to come work with us in the summer or fall: if you’re interested, keep an eye out for our application!

(Left) A view from a nearby mountain, (Right) the Black River
(Left) A view from a nearby mountain; (Right) the Black River
Comments6


Sorted by Click to highlight new comments since:

I work on far-UVC safety. Dm me if you want to get in touch :)

Best of luck to you! I'd be interested in hearing in more depth about your team, specific project ideas, funding situation if you care to share. My particular interest is in the pandemic prevention/far UVC work.

Sounds good! Why the name Cavendish? Made me think of the Cavendish Laboratory (aka Cambridge Univeristy's Physics department - https://www.phy.cam.ac.uk/)

It's in Cavendish! A long-term goal is to beat them in Nobel prizes..

Of course! (I missed that)

This is awesome guys! Can't wait to visit during the summer :)

Curated and popular this week
 ·  · 38m read
 · 
In recent months, the CEOs of leading AI companies have grown increasingly confident about rapid progress: * OpenAI's Sam Altman: Shifted from saying in November "the rate of progress continues" to declaring in January "we are now confident we know how to build AGI" * Anthropic's Dario Amodei: Stated in January "I'm more confident than I've ever been that we're close to powerful capabilities... in the next 2-3 years" * Google DeepMind's Demis Hassabis: Changed from "as soon as 10 years" in autumn to "probably three to five years away" by January. What explains the shift? Is it just hype? Or could we really have Artificial General Intelligence (AGI)[1] by 2028? In this article, I look at what's driven recent progress, estimate how far those drivers can continue, and explain why they're likely to continue for at least four more years. In particular, while in 2024 progress in LLM chatbots seemed to slow, a new approach started to work: teaching the models to reason using reinforcement learning. In just a year, this let them surpass human PhDs at answering difficult scientific reasoning questions, and achieve expert-level performance on one-hour coding tasks. We don't know how capable AGI will become, but extrapolating the recent rate of progress suggests that, by 2028, we could reach AI models with beyond-human reasoning abilities, expert-level knowledge in every domain, and that can autonomously complete multi-week projects, and progress would likely continue from there.  On this set of software engineering & computer use tasks, in 2020 AI was only able to do tasks that would typically take a human expert a couple of seconds. By 2024, that had risen to almost an hour. If the trend continues, by 2028 it'll reach several weeks.  No longer mere chatbots, these 'agent' models might soon satisfy many people's definitions of AGI — roughly, AI systems that match human performance at most knowledge work (see definition in footnote). This means that, while the compa
 ·  · 4m read
 · 
SUMMARY:  ALLFED is launching an emergency appeal on the EA Forum due to a serious funding shortfall. Without new support, ALLFED will be forced to cut half our budget in the coming months, drastically reducing our capacity to help build global food system resilience for catastrophic scenarios like nuclear winter, a severe pandemic, or infrastructure breakdown. ALLFED is seeking $800,000 over the course of 2025 to sustain its team, continue policy-relevant research, and move forward with pilot projects that could save lives in a catastrophe. As funding priorities shift toward AI safety, we believe resilient food solutions remain a highly cost-effective way to protect the future. If you’re able to support or share this appeal, please visit allfed.info/donate. Donate to ALLFED FULL ARTICLE: I (David Denkenberger) am writing alongside two of my team-mates, as ALLFED’s co-founder, to ask for your support. This is the first time in Alliance to Feed the Earth in Disaster’s (ALLFED’s) 8 year existence that we have reached out on the EA Forum with a direct funding appeal outside of Marginal Funding Week/our annual updates. I am doing so because ALLFED’s funding situation is serious, and because so much of ALLFED’s progress to date has been made possible through the support, feedback, and collaboration of the EA community.  Read our funding appeal At ALLFED, we are deeply grateful to all our supporters, including the Survival and Flourishing Fund, which has provided the majority of our funding for years. At the end of 2024, we learned we would be receiving far less support than expected due to a shift in SFF’s strategic priorities toward AI safety. Without additional funding, ALLFED will need to shrink. I believe the marginal cost effectiveness for improving the future and saving lives of resilience is competitive with AI Safety, even if timelines are short, because of potential AI-induced catastrophes. That is why we are asking people to donate to this emergency appeal