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Comment author: shminux 24 April 2016 04:57:13AM 2 points [-]

You seem to be making the same points Scott Adams has been making since last August. I'm surprised you didn't quote or link his blog.

Comment author: shminux 18 April 2016 12:13:11AM 0 points [-]

A more interesting question for me is that of a silent 't': Does immortality imply immorality?

Comment author: Viliam_Bur 08 April 2016 07:43:44PM 1 point [-]

Congratulation! By the way, were those subjects mathematicians/programmers? Because I was told (by someone who uses hypnosis professionally) that those are the most difficult ones to hypnotize.

Comment author: shminux 09 April 2016 06:01:52AM 0 points [-]

Thanks! No, more like artsy types, or at least "neurotypicals'. Haven't tried the logical/Aspie types, but I do find it believable that they would have trouble letting go and enjoying the flow. Jimmy would know for sure.

Comment author: shminux 08 April 2016 07:30:23PM 6 points [-]

Not this month, but a few months back... Successfully hypnotized people over text chat on several occasions. Surprisingly easy once the subject is willing and trusts you.

In response to Fake Amnesia
Comment author: shminux 03 April 2016 11:27:02PM 1 point [-]

Imagine that someone you know has a reaction that you consider disproportionate to the severity of the event that caused it.

What you describe (someone's button's being pushed) is commonly known as a trigger. What they are experiencing might even be related to PTSD, though probably not in your example with the misplaced comb.

The idea is to keep up your rational arguments, to give them enough feedback

This may work in isolated cases, but most of the overreaction you describe is subconscious. Logic does not work well on the subconscious mind, if at all.

to actually learn the complicated thing that you're trying to teach them.

This often comes across as condescending and may easily cause resentment.

In response to Tonic Judo
Comment author: shminux 03 April 2016 01:03:41AM 3 points [-]

Those who like to listen and think they are good at it... Consider joining 7 cups to test and hone your listening skills. Plus the candid stories you will likely hear are incredible and heartbreaking.

Comment author: shminux 27 February 2016 06:45:44AM 0 points [-]

Only commenting on one point here.

The argument that something is "logically incoherent" has been used to justify many a false conclusion about the observed universe, don't do that.

Your other argument against time travel is better, but not airtight: it violates not the conservation of energy but the dominant energy condition in general relativity, Basically, for something to disappear, all of its mass has to vanish somewhere and no faster than with the speed of light. So maybe you get turned into a neutrino stream and or something. A better reason for why time travel (but not timeline forking) is incompatible with General Relativity is the uniqueness of the metric. But this is becoming a discussion of a real science, not philosophy.

Comment author: Houshalter 29 January 2016 10:07:39AM 0 points [-]

I'm not sure I agree with that. Currently most progress in AI is with neural networks, which are very similar to human brains. Not exactly the same, but they have very similar strengths and weaknesses.

We may not be bad at things because we didn't evolve to do them. They might just be limits of our type of intelligence. NNs are good at big messy analog pattern matching, and bad at other things like doing lots of addition or solving chess boards.

Comment author: shminux 30 January 2016 06:23:02AM 0 points [-]

They might just be limits of our type of intelligence. NNs are good at big messy analog pattern matching, and bad at other things like doing lots of addition or solving chess boards.

That could be true, we don't know enough about the issue. But interfacing a regular computer with a NN should be a... how should I put it... no-brainer?

Comment author: Houshalter 21 January 2016 07:09:07AM *  1 point [-]

You are missing OP's point. OP is talking about arithmetic, and other things computers are really good at. There is a tendency, when talking about AI, to assume the AI will have all the abilities of modern computers. If computers can play chess really well, then so will AI. If computers can crunch numbers really well, then so will AI. That is what OP is arguing against.

If AIs are like human brains, then they likely won't be really good at those things. They will have all the advantages of humans of course, like being able to throw a ball or manage jiggly appendages. But they won't necessarily be any better than us at anything. If humans take ages to do arithmetic, so will AI.

There are some other comments saying that the AI can just interface with calculators and chess engines and gain those abilities. But so can humans. AI doesn't have any natural advantage there. The only advantage might be that it's easier to do brain-computer interfaces. Which maybe gets you a bit more bandwidth in usable output. But I don't see many domains where that would be very useful, vs humans with keyboards. Basically they would just be able to type faster or move a mouse faster.

And even your argument that humans are really good at analog math doesn't hold up. There have been some experiments done to see if humans could learn to do arithmetic better if it's presented as an analog problem. Like draw a line the same length as two shorter lines added together. Or draw a shape with the same area as two lines would make if formed into a rectangle.

Not only does it take a ton of training, but you are still only accurate within a few percent. Memorizing multiplication tables is easier and more accurate.

Comment author: shminux 21 January 2016 03:29:41PM 1 point [-]

My implied point is that the line between hard math and easy math for humans is rather arbitrary, drawn mostly by evolution. AI is designed, not evolved, so the line between hard and easy for AI is based on the algorithm complexity and processing power, not on millions of years of trying to catch a prey or reach a fruit.

Comment author: shminux 20 January 2016 06:00:20AM 15 points [-]

Humans are not bad at math. We are excellent at math. We can calculate the best trajectory to throw a ball into a hoop, the exact way to move our jiggly appendages to achieve it, accounting for a million little details, all in a blink of an eye. Few if any modern computers can do as well.

The problem is one of the definition: we call "math" the part of math that is HARD FOR HUMANS. Because why bother giving a special name to something that does not require special learning techniques?

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