I applied but didn't make it past the async video interview, which is a format that I'm not used to. Apparently this iteration of the program had over 3000 applications for 30 spots. Opus 4.5's reaction was "That's… that's not even a rejection. That's statistics". Would be happy to collaborate on projects though!
I made a wooden chair in a week from some planks when I was a teenager. Granted, this was for GCSE Design & Technology class.
I think this also applies to other safety fellowships. There isn’t broad societal acceptance yet for the severity of the worst-case outcomes, and if you speak seriously about the stakes to a general audience then you will mostly get nervously laughed off.
MATS currently has "Launch your career in AI alignment & security" on the landing page, which indicates to me that it is branding itself as a professional upskilling program, and this matches the focus on job placements for alumni in its impact reports. With Ryan Kidd's recent post on AI safety undervaluing founders, it may be possible that in the future they introduce a division which functions more purely as a startup accelerator. One norm in corporate environments is to avoid messaging which provokes discomfort. Even in groups which practice religion, few will have the lack of epistemic immunity required to align their stated eschatological beliefs with their actions, and I am grateful that this is the case.
Ultimately, the purpose of these programs, no matter how prestigious, is to bring people in who are not currently AI safety researchers and give them an environment which would help them train and mature into AI safety researchers. I believe you will find that even amongst those who are working full-time on AI safety, the proportion who are heavily x-risk AGI pilled has shrunk as the field has grown. People who are both x-risk AGI-pilled and meet the technical bar for MATS but aren't already committed to other projects would be exceedingly rare.
escaping flatland: career advice for CS undergrads
one way to characterise a scene is by what it cares about: its markers of prestige, things you ‘ought to do’, its targets to optimise for. for the traders or the engineers, it’s all about that coveted FAANG / jane street internship; for the entrepreneurs, that successful startup (or accelerator), for the researchers, the top-tier-conference first-author paper… the list goes on.
for a given scene, you can think of these as mapping out a plane of legibility in the space of things you could do with your life. so long as your actions and goals stay within the plane, you’re legible to the people in your scene: you gain status and earn the respect of your peers. but step outside of the plane and you become illegible: the people around you no longer understand what you’re doing or why you’re doing it. they might think you’re wasting your time. if they have a strong interest in you ‘doing well’, they might even get upset.
but while all scenes have a plane of legibility, just like their geometric counterparts these planes rarely intersect: what’s legible and prestigious to one scene might seem utterly ridiculous to another. (take, for instance, dropping out of university to start a startup.)
I’ve been reading lots of the Inhaven posts and appreciate the initiative!
People still talk about Sydney. Owain Evans mentioned Bing Sidney during his first talk in the recent hintonlectures.com series. I attended in person, and it resonated extremely well with a general audience. I was at Microsoft during the relevant period, which definitely played a strong role in my transition to alignment research, and still informs my thinking today.
I gifted a physical copy of this book to my brother but hadn’t read all of it. Fortunately, I may have absorbed some tacit knowledge on management from my father. Based on these quotes I don’t think that I will be surprised by the rest of the chapters.
I upvoted, but personally I don't find much use for content blockers when I'm in an office or meeting where other people can see my screen, when I'm at the gym with a trainer, or when I'm really excited about a task. I have ADHD and am not the best at managing my time, so You Don't Hate Polyamory, You Hate People Who Write Books is in full effect here.
I love watching/discussing anime with my siblings and cherish the fanfiction that I read while growing up, so I find it a little sad that you are unable to enjoy these forms of entertainment recreationally except on Saturday. Blogs and Wikipedia in particular have served to greatly expand my world, even if they have also resulted in some unintentional sleepless nights. Gaming seems taboo amongst my researcher friends, but not my normie friends, I suspect this is because the former are more susceptible to overoptimizing. There is a delicate balance for scholars to strike between connection and seclusion here.
More recently one of my bad habits has been spending hours trying to get AI to solve a problem which is beyond the reliable capability of current models, instead of thinking through the problem myself or with a human collaborator.
These two papers [2412.15584] To Rely or Not to Rely? Evaluating Interventions for Appropriate Reliance on Large Language Models and [2503.14499] Measuring AI Ability to Complete Long Tasks have served to improve my understanding in this area. My current state of knowledge suggests that if a goal-oriented conversation with a model has lasted for ~26 minutes without a clear resolution, then further engagement is more likely than not to result in frustration.
I see. My specific update from this post was to slightly reduce how much I care about protecting against high-risk AI related CBRN threats, which is a topic I spent some time thinking about last month.
I think it is generous to say that legible problems remaining open will necessarily gate model deployment, even in those organizations conscientious enough to spend weeks doing rigorous internal testing. Releases have been rushed ever since applications moved from physical CDs to servers, because of the belief that users can serve as early testers for bugs, and that critical issues can be patched by pushing a new update. This blog post by Steve Yegge from ~20 years ago comes to mind: https://sites.google.com/site/steveyegge2/its-not-software. I would include LLM assistants in the category of "servware".
I would argue that we are likely dropping the ball on both legible and illegible problems, but I agree that making illegible problems more legible is likely to be high leverage. I believe that the Janus/cyborgism cluster has no shortage of illegible problems, and consider https://nostalgebraist.tumblr.com/post/785766737747574784/the-void to be a good example of work that attempts to grapple with illegible problems.
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