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Most people have played w Rubik’s cube & discovered it’s harder to unscramble than it appears, even tho manipulation is easy
that’s WHY cube is icon it is
@OpenAI played on our shared experience
=> why many feel they have been tricked by hype, once actual study explained (1/2)
the work itself is actually great. but the PR fits an ongoing pattern 1. making deep R learning sound omnipotent when it’s not 2. minimizing value of innate contributions 3. minimizing value of symbols 4. making small advances seem larger than they are 2/2
perhaps related to #3, games are designed by humans to be difficult for humans. they thus often play to the strengths of machines. and, perhaps 5, something about the ridiculousness of the giraffe?
i LOVE the giraffe. no way am I complaining about it.
Do you also have an estimate on how much Power in terms of energy is used to come to the used network they did actually use? Is it in the same scale that Google DeepMind used for the Warcraft & StarCraft games?
The paper claims 13000 years of experience, using 64 GPUs and many thousands of CPUs. It took them months to train.
All of which contributes to the general, blind faith that tech is more capable than it actually is, creating its own harm when AI is used in applications that matter, https://www.theguardian.com/technology/2018/mar/31/tesla-car-crash-autopilot-mountain-view ….
I think you should go back on @EconTalker again.
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