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I think part of the problem might be people too often try to come up with some grand unifying theory all at once, without standing on the shoulders of giants. S
by xamuel 5y ago
I think part of the problem might be people too often try to come up with some grand unifying theory all at once, without standing on the shoulders of giants. Sort of like trying to write a gigantic codebase all in one sitting (no test suite, no syntax highlighting) and then sending it off for code review without even running it.
This preprint my co-authors and I are working on might offer something of a babystep, not toward consciousness itself but toward the simpler problem of self-reflection, and more specifically of measuring self-reflection in reinforcement learning agents: https://philpapers.org/archive/ALEEET-3.pdf https://philpapers.org/archive/ALEEET-3.pdf
- White_Wolf 5y agoNot sure how to describe it but I see it like more of a approach and limitations or tech problem. 1- can't study it,in details, live with 0 risk of damage 2- can't test injecting data without risk of damage 3- the live data that we can extract/record (while monitoring input) with current tech is limited. I'm thinking that we're still at the stage comparable with using a multimeter to test a 8 layer pcb, with no schematics, while it's powered on. I, personally, think science will get there at some point, but we'll need some serious tech advancements to do that.
- xamuel 5y agoThat's one of the reasons it's so nice to use reinforcement learning agents as guinea pigs. I can "pip install" a bunch of industry-standard RL agents and put them through the most bizarre scenarios, scenarios it would never be possible to put a human through. No ethical issues involved, since these RL agents are nothing more than a bunch of matrix multiplications.
- White_Wolf 5y agoOff topic: For some reason, when I read "pip install" my mind drifted off to "apt-get install kung fu" and I started grinning like an idiot.