I'd suggest updating the language in the post to clarify things and not overstate :)
Regarding the 3rd draft - opinions varied between people I work with but we are generally happy. Loss of Control is included in the selected systemic risks, as well as CBRN. Appendix 1.2 also has useful things, though some valid concerns got raised there on compatibility with the AI Act language that still need tweaking (possobly merging parts of 1.2 into selected systemic risks). As far as interpretability - the code is meant to be outcome based, and the main reason evals ...
FYI I wouldn't say at all that AI safety is under-represented in the EU (if anything, it would be easier to argue the opposite). Many safety orgs (including mine) supported the Codes of Practice, and almost all the Chairs and vice chairs are respected governance researchers. But probably still good for people to give feedback, just don't want to give the impression that this is neglected.
Also no public mention of intention to sign the code has been made as far as I know. Though apart from copyright section, most of it is in line with RSPs, which makes signing more reasonable.
Good point. Thinking of robotics overall, it's much more of a bunch of small stuff than one big thing. Though it depends how far you "zoom out" I guess. Technically Linear Algebra itself, or the Jacobian, is an essential element of robotics. But could also zoom in on a different aspect and then say that "zero backlash gearboxes" (where Harmonic Drive is notable as it's much more compact and accurate than prev versions - but perhaps a still small effect in the big picture) are the main element. Or PID control, or high resolution encoders.
I'm not quite sure ...
Other examples of fields like this include: medicine, mechanical engineering, education, SAT solving, and computer chess.
To give a maybe helpful anecdote - I am a mechanical engineer (though I now work in AI governance), and in my experience that isnt true at least for R&D (e.g. a surgical robot) where you arent just iterating or working in a highly standardized field (aerospace, hvac, mass manufacturing etc). The "bottleneck" in that case is usually figuring out the requirements (e.g. which surgical tools to support? whats the motion range, design env...
I had a great time at AISC8. Perhaps I would still find my way into a full time AI Safety position without it, but i'd guess at least 1 year later and significantly less neglected opportunity. My AI Safety Camp project later became the AI Standards Lab.
I know several others who benefitted quite a bit from it.
I was fairly on board with control before, I think my main remaining concern is the trusted models not being good enough. But with more elaborate control protocols (Assuming political/AI labs actually make an effort to implement), catching an escape attempt seems more likely if the model's performance is very skewed to specific domains. Though yeah I agree that some of what you mentioned might not have changed, and could still be an issue
With o1, and now o3, It seems fairly plausible now that there will be a split between "verifiable" capabilities, and general capabilities. Sure, there will be some cross-pollination (transfer), but this might have some limits.
What then? Can a superhuman mathematical + Coding AI also just reason through political strategy, or will it struggle and make errors/fallback on somewhat generic ideas in training data?
Can we get a "seed-AI style" consequentialist in some domains, while it fails to perform above human level in others? I'd like to believe reason...
Signal boost for the "username hiding" on homepage feature in settings - it seems cool, will see if it changes how I use LW.
I wonder also about a "hide karma by default". Though less sure if that will actually achieve the intended purpose, as karma can be a good filter when just skimming comments and not reading in detail.
LW Feature request/idea for a feature - In posts that have lots of in-text links to other posts, perhaps add an LLM 1-2 sentence (context informed) summary in the hover preview?
I assume that for someone who has been around the forum for many years, various posts are familiar enough that name-dropping them in a link is sufficient to give context. But If I have to click a link and read 4+ other posts as I am going through one post, perhaps the LW UI can fairly easily build in that feature.
(suggesting it as a features since it does seem like LW is a place that experiments with various features not too different from this - ofc, I can always ask for a LLM summary manually myself if I need to)
I have the Boox Nova Air (7inch) for nearly 2 years now - a bit small for reading papers but great for books and blog posts. You can run google play apps, and even set up a google drive sync to automatically transfer pdfs/epubs onto it. At some point I might get the 10inch version (the Note Air).
Another useful feature is taking notes inside pdfs, by highlighting and then handwriting the note into the Gboard handwrite-to-text keyboard. Not as smooth as on an iPad, but pretty good way to annotate a paper.
Hmm, in that case maybe I misunderstood the post, my impression wasnt that he was saying AI literally isn't a science anymore, but more that engineering work is getting too far ahead of the science part - and that in practice most ML progress now is just ML Engineering, where understanding is only a means to an end (and so is not as deep as it would be if it was science first).
I would guess that engineering gets ahead of science pretty often, but maybe in ML it's more pronounced - hype/money investment, as well as perhaps the perceived relative low stakes ...
While theoretical physics is less "applied science" than chemistry, there's still a real difference between chemistry and chemical engineering.
For context, I am a Mechanical Engineer, and while I do occasionally check the system I am designing and try to understand/verify how well it is working, I am fundamentally not doing science. The main goal is solving a practical problem (i.e. as little theoretical understanding as is sufficient), where in science the understanding is the main goal, or at least closer to it.
I'm trying to think of ideas here. As a recap of what I think the post says:
^let me know if I am understanding correctly.
Some ideas/thoughts:
Working at a startup made me realize how little we can actually "reason through" things to get to a point where all team members agree. Often there's too little time to test all assumptions, if it's even doable at all. Part of the role of the CEO is to "cut" these discussions when it's evident that spending more time on it is worse than proceeding despite uncertainty. If we had "the facts", we might find it easier to agree. But in an uncertain environment, many decisions come down to the intuition (hopefully based on reliable experience - such as founding ...
Sure! and yeah regarding edits - I have not gone through the full request for feedback yet, I expect to have a better sense late next week of which contributions are most needed and how to prioritize. I mainly wanted to comment first on obvious things that stood out to me from the post.
There is also an Evals workshop in Brussels on Monday where we might learn more. I've know of some some non-EU based technical safety researchers who are attending, which is great to see.