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A better criticism is it's impossible to come up with an objective definition for "top" for seed stage companies, it's really just their opinion of who they lik

A better criticism is it's impossible to come up with an objective definition for "top" for seed stage companies, it's really just their opinion of who they like the best and they're masquerading it as being successful investors. They don't have a track record and they're just regurgitating what every investor says - "we pick the best because it's our job!" They're spewing bullshit. That opening line alone tells me they're copying every other VC (and most VCs lose money) while simultaneously portraying themselves as being better than every other VC. YC succeeded by completely subverting what everybody thought VC had to be. You can't expect to be better by doing the same thing as everyone else.

sillysaurusx 5y ago
That is indeed a better criticism, but it happens to follow the same template as another common startup criticism: "It hasn't been tried before, so we don't know whether it will work." Yes. That's true. It might not work. And you're probably even correct. But that's always true, and the most valuable cases are those that work when most people don't expect them to. http://paulgraham.com/swan.html http://paulgraham.com/swan.html You say that every other VC does this. But if other VCs are training ML models, they don't seem to be publishing their results, so I'm inclined to say that this is new. Is it going to work? Well, we'll have to see. But as with most startups, the answer is "probably not, but the chance may be significantly better than random."
- _hyn3 5y ago
  > But that's always true, and the most valuable cases are those that work when most people don't expect them to. http://paulgraham.com/swan.html http://paulgraham.com/swan.html If they are looking for swans that work when people don't expect them to, they should probably be looking for those swans somewhere else*, not the top 3% of an incubator that probably graduates proportionately more successful startups than any university. The issue that everyone is calling out here is that they name themselves "Rebel" when they're doing exactly the same thing that every other VC firm is, but (apparently) not even as well -- at least they should say "Founder Friendly", etc. * Generally startups that might become unexpected swans will be found outside of startup hubs like silicon valley.

sillysaurusx 5y ago

That is indeed a better criticism, but it happens to follow the same template as another common startup criticism: "It hasn't been tried before, so we don't know whether it will work." Yes. That's true. It might not work. And you're probably even correct. But that's always true, and the most valuable cases are those that work when most people don't expect them to. http://paulgraham.com/swan.html http://paulgraham.com/swan.html You say that every other VC does this. But if other VCs are training ML models, they don't seem to be publishing their results, so I'm inclined to say that this is new. Is it going to work? Well, we'll have to see. But as with most startups, the answer is "probably not, but the chance may be significantly better than random."

_hyn3 5y ago
> But that's always true, and the most valuable cases are those that work when most people don't expect them to. http://paulgraham.com/swan.html http://paulgraham.com/swan.html If they are looking for swans that work when people don't expect them to, they should probably be looking for those swans somewhere else*, not the top 3% of an incubator that probably graduates proportionately more successful startups than any university. The issue that everyone is calling out here is that they name themselves "Rebel" when they're doing exactly the same thing that every other VC firm is, but (apparently) not even as well -- at least they should say "Founder Friendly", etc. * Generally startups that might become unexpected swans will be found outside of startup hubs like silicon valley.