686 karma · joined May 4, 2009
-There are lower-paying sports where fitness does matter, and they all have fit athletes at the top.
-There are way more conventionally fit folks than there are pro athlete slots; It's not like the select few fit people in the world are being exhausted before they can fill the ranks of all professional athletics.
Your explanation is a great example -- if you want to look at the idea exclusively in those terms, that sure sounds problematic. But do you really think that's the only way it could have played out? Keep in mind, we are living in a system that causes massive aggregate harm to underrepresented people on a daily basis. And I'm just referring to the tech industry and particularly its hiring practices, let alone society as a whole.
Killing a new idea just because you can conceive of scenarios where it might be harmful (though I would argue not even that much more harmful than the status quo in this case) is probably unwise in general, but is almost certainly so in a space where the status quo is already so fraught. I work in this space, we need more/better ideas (among many other things), and I think this idea actually had a plausible chance of putting a dent in some of the problems at the core of these systemic issues. Sure, it's a small chance, but to just throw it away? That bums me out.
Edit just to be clear: I have no idea who the people behind this site are and had never heard of it before day. I just work on some of the same problems and would love to see the system improve more quickly.
Nobody thinks that.
To your 1): I think it's at least plausible that this would become common; many crazier-sounding ideas have succeeded. There's a big disconnect between talent identification/development industries and hirers, and something like this could help to bridge that gap.
To your 2): Trust me, I have done all of that. It helps, but it is far from a panacea. That is the conventional shit that has resulted in the tech industry barely making a dent in its diversity numbers for well over a decade now. There are so many people for whom I would have so much rather just invested money in them getting a job immediately than spend yet another hour walking through their latest interview experience and explaining why something innocuous they said or did was probably incorrectly treated as a red flag by their interviewer.
For example: Five years ago, I thought Tesla had a 30% chance of failing, 20% chance of being bought by a major auto manufacturer (for let's say ~30B), 30% chance of turning into a major auto manufacturer (est value ~100B), 10% chance of turning into the top auto manufacturer (est value ~300B), and 10% chance of turning into something that transcended auto manufacturing (est value ~1T). If you multiply this out, you get an expected value of 0+6+30+30+100 = 166B. At the time the market cap was around 40B, so I thought it was underpriced and bought some. Obviously I'm glossing over some things, but it's sensible enough and should illustrate how you can get there.
In terms of the notion of "what if you never find someone to buy it from you?" The short answer is that that's extremely unlikely. The longer answer is that you can also just price that into your probability distribution, but because of the low likelihood it's unlikely to affect your price much.
FWIW I don't know much about Rivian, but my sense is also that they are overpriced. You could go through the same little exercise above for Rivian and see if you agree. To summarize what my distribution would look like, I think they have a much higher chance of failure than Tesla in my example above (because they're much less far along), and not enough potential upside to justify the valuations being discussed. But I could easily be wrong.
What on earth would you call it then?
Is the corpus the only data you have, i.e. do you need to use it for training and validation as well?
In terms of the size of the data, if you want to store the corpus on the phone anyway, won't the index and model be relatively small in comparison?
Put another way, just because something is impossible to demonstrate conclusively and/or via observed reality does not automatically mean it can't be true, right? Of course it does mean that these claims warrant far more skepticism, and probably the large majority of them are untrue. But it seems obviously incorrect to automatically assume that they can not be true. Am I misunderstanding your reasoning in some way?
I could see arguing with the inevitability of the exploit -- Win95 botnets seemed much more inevitable to me than this Tesla mothership threat does. But it seems like you're arguing that they will both have similar impact if exploited. That doesn't make sense to me, because they're completely different threats, but it's possible I'm misunderstanding your argument in some way.