And I doubt that Microsoft or Google have a program dedicated to “trying everything that look promising”, even though it is true that they have manpower and hardware to do just that. But would they choose to do that?
Actually I’m under the impression a lot of what they do is just sharing papers in a company slack and reproducing stuff at scale.
I’d love to have a better feel for how much of the promising things they try to reproduce at scale...
Unfortunately, I don’t have enough inside access for that...
My mental model of the hardware poor is they want to publicize their results as fast as they can so they get more clout, VC funding, or just getting essentially acquired by big tech. Academic recognition in the form of citations drive researchers. Getting rich drives the founders.
There are all kinds of people. I think Schmidhuber’s group might be happy to deliberately create an uncontrollable foom, if they can (they have Saudi funding, so I have no idea how much hardware do they actually have, and how much options for more hardware do they have contingent on preliminary results). Some other people just don’t think their methods are strong enough to be that unsafe. Some people do care about safety (but still want to go ahead; some of those say “this is potentially risky, but in the future, and not right now”, and they might be right or wrong). Some people feel their approach does increase safety (they might be right or wrong). A number of people are ideological (they feel that their preferred approach is not getting a fair shake from the research community, and they want to make a strong attempt to show that the community is wrong and myopic)...
I think most places tend to publish some of their results for the reasons you’ve stated, but they are also likely to hold some of stronger things back (at least, for a while); after all, if one is after VC funding, one needs to show those VCs that there is some secret sauce which remains proprietary...
Unfortunately, I don’t have enough inside access for that...
Yeah, with you there. I am just speculating based on what I’ve heard online and through the grapevine, so take my model of their internal workings with a grain of salt. With that said I feel pretty confident in it.
if one is after VC funding, one needs to show those VCs that there is some secret sauce which remains proprietary
IMO software/algorithmic moat is pretty impossible to keep. Researchers tend to be pretty smart, enough to figure it out independently, even if they manage to stop any researcher from leaving and diffusing knowledge. Some parallels:
The India trade done by Jane Street. They are were making billions of dollars contingent on the fact that no one else knows about this trade, but eventually their alpha also got diffused.
TikTok’s content algorithm which the Chinese government doesn’t want to export only took a couple months for Meta/Google to replicate.
if one is after VC funding, one needs to show those VCs that there is some secret sauce which remains proprietary
IMO software/algorithmic moat is pretty impossible to keep.
Indeed.
That is, unless the situation is highly non-stationary (that is, algorithms and methods are modified fast without stopping; of course, a foom would be one such situation, but I can imagine a more pedestrian “rapid fire” evolution of methods which goes at a good clip, but does not accelerate beyond reason).
I’d love to have a better feel for how much of the promising things they try to reproduce at scale...
Unfortunately, I don’t have enough inside access for that...
There are all kinds of people. I think Schmidhuber’s group might be happy to deliberately create an uncontrollable foom, if they can (they have Saudi funding, so I have no idea how much hardware do they actually have, and how much options for more hardware do they have contingent on preliminary results). Some other people just don’t think their methods are strong enough to be that unsafe. Some people do care about safety (but still want to go ahead; some of those say “this is potentially risky, but in the future, and not right now”, and they might be right or wrong). Some people feel their approach does increase safety (they might be right or wrong). A number of people are ideological (they feel that their preferred approach is not getting a fair shake from the research community, and they want to make a strong attempt to show that the community is wrong and myopic)...
I think most places tend to publish some of their results for the reasons you’ve stated, but they are also likely to hold some of stronger things back (at least, for a while); after all, if one is after VC funding, one needs to show those VCs that there is some secret sauce which remains proprietary...
Yeah, with you there. I am just speculating based on what I’ve heard online and through the grapevine, so take my model of their internal workings with a grain of salt. With that said I feel pretty confident in it.
IMO software/algorithmic moat is pretty impossible to keep. Researchers tend to be pretty smart, enough to figure it out independently, even if they manage to stop any researcher from leaving and diffusing knowledge. Some parallels:
The India trade done by Jane Street. They
arewere making billions of dollars contingent on the fact that no one else knows about this trade, but eventually their alpha also got diffused.TikTok’s content algorithm which the Chinese government doesn’t want to export only took a couple months for Meta/Google to replicate.
Indeed.
That is, unless the situation is highly non-stationary (that is, algorithms and methods are modified fast without stopping; of course, a foom would be one such situation, but I can imagine a more pedestrian “rapid fire” evolution of methods which goes at a good clip, but does not accelerate beyond reason).