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. @OpenAI's main line of defense against my analysis is to suggest nobody could possibly have misunderstood PR about learning to solve Rubik's cube with a neural networks as... claiming to have learned to solve a cube w neural networks
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spoiler alert: many people did.
my last 10 or so RTs document some examples of people bothered by the gap between how the work was presented & what actually happened.
@openAI still refuses to own their mistake.
not a good look.
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Following your analysis on this whole rubix cube thing has really helped clerify some of the frustrations I've struggled with concerning AI. It's very hard to discern where the line between reality and fantasy is. Which makes it a bit exhausting just getting started in the field
You are right, and they are wrong. "Solved" means solving the puzzle part, not the manipulation. At least to most readers.
Agree. This was deliberately misleading from the start by choosing Rubik's Cube: people think of as hard but not because of the manipulation. More honest: tackle a problem in which the manipulation itself is generally thought of as hard, even for children, e.g. tying shoelaces.
Also it drops the cube a lot in a glass box.
I completely agree but I think a complication comes from the fact that many people who "learn to solve" Rubik's Cube merely learn to follow an algorithm of which they have limited understanding. In a way "solving" the Rubik's Cube has always been a small scale PR con.
It exemplifies a task that is simple yet genuinely very difficult for people to solve. The fact that people can learn algorithmic solutions exemplifies the importance of non-RL learning.
Some people simply cannot or will not admit error. <cough Trump cough>
The day will come, sooner=better, where term "Artificial Intelligence" be recognized across the board as nothing more than an umbrella term for unrefined tech definition. As in AI dev history some tech has been moved out from under it when well defined/understood. Bye black box!
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