EA - Apply for Cambridge ML for Alignment Bootcamp (CaMLAB) [26 March - 8 April] by hannah

Link to original articleWelcome to The Nonlinear Library, where we use Text-to-Speech software to convert the best writing from the Rationalist and EA communities into audio. This is: Apply for Cambridge ML for Alignment Bootcamp (CaMLAB) [26 March - 8 April], published by hannah on February 9, 2023 on The Effective Altruism Forum.TL;DR: A two-week machine learning bootcamp this spring in Cambridge, UK, open to global applicants and aimed at providing ML skills for AI alignment. Apply by 26 February to participate or TA.Following a series of machine learning bootcamps earlier this year in Cambridge, Berkeley and Boston, the Cambridge AI Safety Hub is running the next iteration of the Cambridge ML for Alignment Bootcamp (CaMLAB) in spring.This two-week curriculum expects no prior experience with machine learning, although familiarity with Python and understanding of (basic) linear algebra is crucial.The curriculum, based on MLAB, provides a thorough, nuts-and-bolts introduction to the state-of-the-art in ML techniques such as interpretability and reinforcement learning. You’ll be guided through the steps of building various deep learning models, from ResNets to transformers. You’ll come away well-versed in PyTorch and useful complementary frameworks.From Richard Ren, an undergraduate at UPenn who participated in the January camp:The material from the bootcamp was well-prepared and helped me understand how to use PyTorch and einops, as well as how backpropagation and transformers work. The mentorship from the TAs and peers was excellent, and because of their support, I think the time I spent at the camp was at least 3-5x as productive as focused time I would've spent outside of the camp learning the material on my own — propelling me to be able to take graduate-level deep learning classes at my school, read AI safety papers on my own, and giving me the knowledge necessary to pursue serious machine learning research projects.In addition, the benefits of spending two weeks in-person with other motivated and ambitious individuals cannot be overstated: alongside the pedagogical benefits of being paired with another person each day for programming, the conversations which took place around the curriculum were a seedbed for new insights and valuable connections.Richard continues:The mentorship from the TAs, as well as the chance conversations from the people I've met, have had a serious impact on how I'll approach the career path(s) I'm interested in — from meeting an economics Ph.D. (and having my worldview on pursuing a policy career change) to talking with someone who worked at EleutherAI in the Cambridge EA office about various pathways in AI safety. I loved the people I was surrounded with — they were ambitious, driven, kind, emotionally intelligent, and hardworking.Feedback from the end of the previous camp showed that:Participants on average said they would be 93% likely to recommend the bootcamp to a friend or colleague.Everyone found the camp at least as good as expected, with 82% finding it better than expected, and 24% finding it much better than expected.94% of participants found the camp more valuable than the counterfactual use of their time, with 71% finding it much more valuable.In addition, first and second place in Apart Research’s January Mechanistic Interpretability Hackathon were awarded to teams formed from participants and TAs from our January bootcamp.Chris Mathwin, who was part of the runner-up project, writes of the bootcamp:A really formative experience! Great people, great content and truly great support. It was a significantly better use of my time in upskilling in this field than I would have spent elsewhere and I have continued to work with some of my peers afterwards!If you’re interested in participating in the upcoming round of CaMLAB, apply here. If you have substantial ML experience and are interested in being a teaching assistant (TA), apply here. You can find more details below.Schedule & logisticsTh...