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[return to "OpenAI LP"]
1. jpdus+ew[view] [source] 2019-03-11 19:18:50
>>gdb+(OP)
Wow. Screw non-profit, we want to get rich.

Sorry guys, but before you were probably able to get talent which is not (primarily) motivated by money. Now you are just another AI startup. If the cap would be 2x, it could still make sense. But 100x times? That's laughable! And the split board, made up of friends and closely connected people smells like "greenwashing" as well. Don't get me wrong, it's totally ok to be an AI startup. You just shouldn't pretend to be a non-profit then...

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2. gdb+7D[view] [source] 2019-03-11 20:13:28
>>jpdus+ew
(I work at OpenAI.)

I think this tweet from one of our employees sums it up well:

https://twitter.com/Miles_Brundage/status/110519043405200588...

Why are we making this move? Our mission is to ensure AGI benefits all of humanity, and our primary approach to doing this is to actually try building safe AGI. We need to raise billions of dollars to do this, and needed a structure like OpenAI LP to attract that kind of investment while staying true to the mission.

If we succeed, the return will be exceed the cap by orders of magnitude. See https://blog.gregbrockman.com/the-openai-mission for more details on how we think about the mission.

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3. jackpi+jN[view] [source] 2019-03-11 21:26:23
>>gdb+7D
If we succeed, the return will be exceed the cap by orders of magnitude.

Are there any concrete estimates of the economic return that different levels of AGI would generate? It's not immediately obvious to me that an AGI would be worth more than 10 trillion dollars (which I believe is what would be needed for your claim to be true).

For example, if there really is an "AGI algorithm", then what's to stop your competitors from implementing it too? Trends in ML research have shown that for most advances, there have been several groups working on similar projects independently at the same time, so other groups would likely be able to implement your AGI algorithm pretty easily even if you don't publish the details. And these competitors will drive down the profit you can expect from the AGI algorithm.

If the trick really is the huge datasets/compute (which your recent results seem to suggest), then it may turn out that the power needed to run an AGI costs more than the potential return that the AGI can generate.

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