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 how to think of how these all fit together to form "robotics" and whether they are small elements of a larger thing, or large breakthroughs stacked over the course of many years (where they might appear small at that zoomed out level).

I think that if we take a snapshot in a specific time (e.g. 5 years) in robotics, there will often be one or very few large bottlenecks that are holding it back. Right now it is mostly ML/vision and batteries. 10-15 years ago, maybe it was the CPU real time processing latency or the motor power density. A bit earlier it might be gearbox. These things were fairly major bottlenecks until they got good enough that it switches to a minor revision/iteration regime (nowadays there's not much left to improve on gearboxes e.g., except for maybe in very specific use cases) 

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 envelope for interferences). If those are wrong, the best design will still be wrong. 

In more standardized engineering fields the requirements (and user needs) are much better known, so perhaps the bottleneck now becomes a bunch of small things rather than one big thing.  

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. 

Do you think there's some initial evidence for that? E.g. Voyager or others from Deepmind. Self play gets thrown around a lot, not sure if concretely we've seen much yet for LLMs using it.

But yes agree, good point regarding strategy games being a domain that could be verifiable

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

Good post, thanks for writing!

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 reasoning would transfer (as it should be universal), but I dont think reasoning is sufficient for some more fuzzy domains - the model also needs good heuristics. 

The AI Control agenda seems more promising now (for both this reason and some others). 

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. 

Steep / Shallow

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)