5 ms·

Yeah, definitely. On one hand it's obvious such companies will want this data precisely to make their systems work. On the other hand... once they have the data

Yeah, definitely. On one hand it's obvious such companies will want this data precisely to make their systems work. On the other hand... once they have the data, we all know it also ends up wherever someone is willing to pay for it. Even if they say it's not the goal today... 10 years from now how do you know the owner of the data at that point will feel the same way? Doubly so since they don't seem to be making any privacy guarantees around the pricing, just attempts at anonymizing the high level things. I find it interesting how many people get worked up about the "skilled/unskilled" terminology though. Just walking to arbitrary waypoints is an extraordinary feet in itself - if you dropped me in the past and told me to build something which walks (or even just traverses) as such I would likely not achieve it in my lifetime, despite having great insight into how we've already accomplished this goal. At the same time, people know listing "mastered the ability to walk as a child, proficient in running" in the skills section of their resume does not make sense. It seems easy enough to understand the difference in meaning between the two contexts (skills an average human is expected to have over, say, a rock vs skills which differentiate one as able to start a job without waiting for several years of additional development) rather than seek to pick the least relevant interpretation. OTOH, there are definitely jobs which get conflated as having a low barrier to entry (for the average person) but actually take many years of training to be able to get a typical job in (and not just for the "high end" version of the job). That's definitely a misclassification, but not for something like cleaning homes where the average person is expected to be able to do it themselves.

ndsipa_pomu 5mo ago
> OTOH, there are definitely jobs which get conflated as having a low barrier to entry (for the average person) but actually take many years of training to be able to get a typical job in Isn't the barrier to entry due to the jobs not allowing for mistakes? Cleaning has a high tolerance for mistakes (e.g. missing bits, leaving streaks on windows etc) and so it's fine for an inexperienced cleaner to learn from their mistakes whilst doing the job. However, people would not be happy for a lawyer or surgeon to be learning from their mistakes whilst working - they are expected to already be competent and mistakes are generally very damaging.
- zamadatix 5mo ago
  Yeah, I'd say a job "does not allow for many mistakes" and "requires skill in the labor" are two ways of saying the same thing. If it's alright to do the job completely wrong most of the time and it still make sense to be hired then the base position in that job does not have a skills requirement.
deleted 5mo ago
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YeGoblynQueenne 5mo ago
>> Just walking to arbitrary waypoints is an extraordinary feet in itself - if you dropped me in the past and told me to build something which walks (or even just traverses) as such I would likely not achieve it in my lifetime, Sorry, I'm confused. Are you talking about bipedal robot walking specifically or path planning in general? The latter is a long-solved problem, right? And I'm sure bipedal walking was also basically solved in the 1980's.
- cpgxiii 5mo ago
  > And I'm sure bipedal walking was also basically solved in the 1980's. It isn't even efficiently solved now, in the general case. Bipedal walking on approximately flat surfaces with minimal geometry constraints is basically solved, but complex terrain and/or constraints on foot placement require slower methods that wouldn't really be considered "solved".
  - YeGoblynQueenne 5mo ago
    That's right, environment conditions play a huge role and modulate efficacy to a great degree. And the same applies to pathfinding with osbstacle avoidance otherwise we'd all have our robot maids and self-driving cars already. But we have the theory down pat, is what I was trying to say. There's a lot of engineering still that remains to do, but e.g. Dijkstra's algorithm... works. I had a longer comment in place of the one I made above, that tried to caveat this a bit more. I also linked to this survey: A Comprehensive Survey of Path Planning Algorithms for Autonomous Systems and Mobile Robots: Traditional and Modern Approaches https://www.sciencedirect.com/science/article/pii/S2590123025038034 https://www.sciencedirect.com/science/article/pii/S259012302... That's just one review, there's more. The striking thing is that there are so many approaches for robotics path planning. That means a) it's a problem for which many solutions are known but b) there's not one dominant approach. One reason for that is what you point out, that it doesn't always work that well. And that's just path planning, i.e. figuring out where to walk. Gait is a whole other ball game, figuring out how to get there.
    - cpgxiii 5mo ago

ndsipa_pomu 5mo ago

> OTOH, there are definitely jobs which get conflated as having a low barrier to entry (for the average person) but actually take many years of training to be able to get a typical job in Isn't the barrier to entry due to the jobs not allowing for mistakes? Cleaning has a high tolerance for mistakes (e.g. missing bits, leaving streaks on windows etc) and so it's fine for an inexperienced cleaner to learn from their mistakes whilst doing the job. However, people would not be happy for a lawyer or surgeon to be learning from their mistakes whilst working - they are expected to already be competent and mistakes are generally very damaging.

zamadatix 5mo ago
Yeah, I'd say a job "does not allow for many mistakes" and "requires skill in the labor" are two ways of saying the same thing. If it's alright to do the job completely wrong most of the time and it still make sense to be hired then the base position in that job does not have a skills requirement.

deleted 5mo ago

[deleted]

YeGoblynQueenne 5mo ago

>> Just walking to arbitrary waypoints is an extraordinary feet in itself - if you dropped me in the past and told me to build something which walks (or even just traverses) as such I would likely not achieve it in my lifetime, Sorry, I'm confused. Are you talking about bipedal robot walking specifically or path planning in general? The latter is a long-solved problem, right? And I'm sure bipedal walking was also basically solved in the 1980's.

cpgxiii 5mo ago
> And I'm sure bipedal walking was also basically solved in the 1980's. It isn't even efficiently solved now, in the general case. Bipedal walking on approximately flat surfaces with minimal geometry constraints is basically solved, but complex terrain and/or constraints on foot placement require slower methods that wouldn't really be considered "solved".
- YeGoblynQueenne 5mo ago
  That's right, environment conditions play a huge role and modulate efficacy to a great degree. And the same applies to pathfinding with osbstacle avoidance otherwise we'd all have our robot maids and self-driving cars already. But we have the theory down pat, is what I was trying to say. There's a lot of engineering still that remains to do, but e.g. Dijkstra's algorithm... works. I had a longer comment in place of the one I made above, that tried to caveat this a bit more. I also linked to this survey: A Comprehensive Survey of Path Planning Algorithms for Autonomous Systems and Mobile Robots: Traditional and Modern Approaches https://www.sciencedirect.com/science/article/pii/S2590123025038034 https://www.sciencedirect.com/science/article/pii/S259012302... That's just one review, there's more. The striking thing is that there are so many approaches for robotics path planning. That means a) it's a problem for which many solutions are known but b) there's not one dominant approach. One reason for that is what you point out, that it doesn't always work that well. And that's just path planning, i.e. figuring out where to walk. Gait is a whole other ball game, figuring out how to get there.
  - cpgxiii 5mo ago