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[-] Mr_Blott@feddit.uk 175 points 2 weeks ago* (last edited 2 weeks ago)

Another one is levelling.

A lot of people can see a picture frame is about 0.5° out of level and their fucking eye twitches until they fix it

Me included

That's nuts when you think about it

[-] ArmoredThirteen@lemmy.ml 77 points 2 weeks ago

I purposefully slightly tilt most my wall hangings. I like watching guests squirm when they mention it and I do nothing

[-] superkret@feddit.org 47 points 2 weeks ago

Sorry cousin, unfortunately I will get the flu this Christmas and won't be able to come visit.

[-] staticsoar@sh.itjust.works 32 points 2 weeks ago

I respect and hate this. I could never

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[-] brbposting@sh.itjust.works 21 points 2 weeks ago
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[-] Senseless@feddit.org 62 points 2 weeks ago

See, I live in an old apartment. The corners aren't 90°, the wall a picture is hanging on is convex. When I'm lying in bed and look at the picture it looks like it's crooked but I used a level several times on it and it's as straight as can be. It's driving me insane.

[-] Hawke@lemmy.world 36 points 2 weeks ago* (last edited 6 days ago)

But “level” isn’t what you need. If the floor and ceiling aren’t level, it’ll look wrong.

[-] Anticorp@lemmy.world 28 points 2 weeks ago

This is when you set it relative to the rest of the unleveled stuff in your view to make it look level.

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[-] Eranziel@lemmy.world 18 points 2 weeks ago

I worked on an industrial robot once, and we parked it such that the middle section of the arm was up above the robot and supposed to be level. I could tell from 50 feet away and a glance that it wasn't, so we checked. It was off by literally 1 degree.

Degrees are bigger than we think, but also our eyes are incredible instruments.

[-] theneverfox@pawb.social 10 points 2 weeks ago

I remember we once installed something on a beam 40' feet up. While waking through an inspection of many such things, the engineer stops, cocks his head for a second, and says "that's not quite straight"

And then it wasn't. Like a cast of manual breathing, the thing I had been frequently walking past for weeks was suddenly wrong, ever so slightly

[-] prole@lemmy.blahaj.zone 9 points 2 weeks ago

Leave it up to a civil engineer to ruin your day.

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[-] Geometrinen_Gepardi@sopuli.xyz 99 points 2 weeks ago

When sharpening knives, with practice you can tell when you are done by sliding your fingertips along (not across) the sharpened bevel. It's possible to feel imperfections measured in micrometers this way.

If the earth were shrank down to the size of a golf ball, you could feel houses.

[-] SpaceNoodle@lemmy.world 149 points 2 weeks ago

That seems wildly unnecessary. I can already feel houses.

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[-] southsamurai@sh.itjust.works 25 points 2 weeks ago

I mean, most people do it across, rather than along the blade, what with the necessity of detecting a burr, which can't usually be felt length wise. You slide along the blade, and it is sharp, if you screw up you get cut.

That doesn't take away from what you're saying, it's very true, no matter which direction you're feeling. Just normal, average fingertips can pick up stuff like that, that you'd need a microscope to see. It's a trip!

[-] Geometrinen_Gepardi@sopuli.xyz 11 points 2 weeks ago

The burr is also detectable lengthwise. When starting with a dull blade it feels smooth while sliding fingers lenghtwise. When the burr is formed, it starts to feel rough. When it feels like it's digging into skin, it's sharp. It's a very subjective thing though, everybody has different fingers.

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[-] danekrae@lemmy.world 21 points 2 weeks ago

We have equipment to measure down to microns, and my students often test how fine details they can feel.

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[-] can@sh.itjust.works 77 points 2 weeks ago* (last edited 2 weeks ago)

Our bodies n brains are so cool. Think about what goes into locating a sound in space.

Edit: there's more to it but at the most basic level your brain calculates the fraction of a second difference between when one ear picks up a sound and when the other does creating a reference point based on that.

[-] bleistift2@sopuli.xyz 31 points 2 weeks ago

That’s boring. Two ears only allow you to put the sound somewhere on a plane (the vertical one that cuts your body in half lengthwise). How do you know the ‘height’ of the sound on that plane? By utilizing the different distortions the sound goes through while being funneled through your auricle.

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[-] rocketpoweredredneck@sh.itjust.works 27 points 2 weeks ago* (last edited 2 weeks ago)

My hearing is pretty severely damaged in my left ear, and for several months I thought everything was to my right. but my ability to locate sounds has come back. My hearings not any better, my brain just figured out that my left ears fucked and compensated.

[-] qupada@fedia.io 25 points 2 weeks ago

I got into an argument with someone once about this, when they told me (paraphrasing) "it's safe to drive listening to music through headphones, because they let outside sound in".

Yes they indeed might, but - even ignoring delay introduced from digital electronics - you've now lost all sense of where that sound is coming from, because you're listening to the sound of one microphone being played through one speaker.

The human ear really is an incredible thing.

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[-] Zink@programming.dev 17 points 2 weeks ago* (last edited 2 weeks ago)

I think the “more to it” might be significantly crazier than the timing thing.

Or ears have unique complex shapes that attenuate certain frequencies and bounce sound around in complex ways depending on the direction they are coming from. And our brains instantly process all that stuff too. It’s why our sense of hearing isn’t just on a flat plane around our head.

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[-] dukatos@lemm.ee 13 points 2 weeks ago

You can also detect is the source up or down thanks to ear shape which delays sound for couple of ms.

[-] GraniteM@lemmy.world 13 points 2 weeks ago

Put on some halfway decent headphones and try out the virtual barbershop.

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[-] abbadon420@lemm.ee 57 points 2 weeks ago

If you're about to walk into a bar with you head, or like the top of a doorpost or smt. You'll instinctively pull back and avoid the obstacle, inches before it hurts, because your brain notice the hairs on your head moved. That's why men who have recently gone bald, often have bumps and bruises on their head. My bald colleague told me that for him, that was the hardest thing about going bald.

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[-] milicent_bystandr@lemm.ee 53 points 2 weeks ago

Not advanced maths per se; neural networks are amazing! Fuzzy matching based on experience - taken to an incredible level. And, tuneable by internal simulation (imagination).

[-] HereIAm@lemmy.world 22 points 2 weeks ago

Don't be fooled to think computer neural networks is how the brain is structured. Through out history we've always compared the brain to the most advanced technology at the time. From clocks, to computers with short and long term memory, and now to neural networks.

[-] milicent_bystandr@lemm.ee 10 points 2 weeks ago

That is a good point, though the architecture of computer neutral networks is inspired by how we think the brain works, and if I understand correctly there is some definite similarity in the architecture.

Lots of difference though, still!

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[-] Kolanaki@yiffit.net 52 points 2 weeks ago

The second thing about microslippage is why I, even though I would say I'm transhumanist, would only ever go full cyborg if the robot parts had a sense of touch.

I don't wanna pet my dog and not only not feel their fur, but also end up crushing them with my super strength.

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[-] iAmTheTot@sh.itjust.works 50 points 2 weeks ago* (last edited 2 weeks ago)

Throwing and catching always amaze me. And it's not something that everyone is always great at, for sure, but anyone can try to toss a wad of paper into the waste basket. Whether or not you make it, the calculations under the hood, happening so quickly, always astound me to think about.

[-] merc@sh.itjust.works 25 points 2 weeks ago

What's amazing is our ability to calculate the path of something in the air.

There's a test they did with Cristiano Ronaldo where someone kicked a ball to him so he could head it. They shut off the lights before the ball was in the air and somehow from the body shape of the person kicking it, he was able to know how to make contact with it without being able to see it.

https://youtu.be/0k2ey_okQ4E?t=1255

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[-] Valmond@lemmy.world 19 points 2 weeks ago

Read somewhere that catching is actually dead simple, just "move towards the image of the incoming target" (I'm not talking about the arm kinematics).

There were a robot paper bin that zoomed under stuff you threw up in the air using no complicated algorithms for example.

Funnily many algos are calked on physical and chemical effects in the real workld, like splines for example were made with a thin metal bar and lead weight bending it to get the lines used in boat hull construction.

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[-] remotedev@lemmy.ca 16 points 2 weeks ago

I remember when I was younger and would lay on my back throwing a baseball up in the air and catching it, that I could watch it go up and not follow it with my eyes as it goes down and still have my hand in the right spot to catch it

[-] bitwolf@lemmy.one 48 points 2 weeks ago

I was always amazed at how we can catch objects in flight.

Compared to how long it takes me to calculate projectile momentum in Physics 1

[-] buttfarts@lemy.lol 36 points 2 weeks ago

Or tiny birds that can expertly navigate wind currents with an almond sized brain using real-time force feedback. The computational power at their disposal is very well optimized for what they do.

[-] PlantDadManGuy@lemmy.world 21 points 2 weeks ago

Hummingbirds are fucking incredible. They can literally hover, fly backwards, fly inverted, fly silently, or flap their wings loud enough to generate sound waves as a mating ritual. They're like miniature f-18s dog fighting constantly.

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[-] iAvicenna@lemmy.world 35 points 2 weeks ago* (last edited 2 weeks ago)

I always imagine it more like neural networks. simply based on a lot of training and experience. As an example think of times when you step onto a non moving escalator. Your mind definitely knows its not moving but you still can't defeat the trained expectation of jerk.

[-] JackbyDev@programming.dev 22 points 2 weeks ago* (last edited 2 weeks ago)

My brain is like a neural network? No way...

[-] iAvicenna@lemmy.world 9 points 2 weeks ago

more like neural networks are maybe like your brain? dunno not an expert, just a feeling

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[-] thedeadwalking4242@lemmy.world 26 points 2 weeks ago

A lot of it is less math and more just approximations using old data, just fitting a complex statistical model neural nets suck ass at math

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[-] tigeruppercut@lemmy.zip 22 points 2 weeks ago

Most people who've been juggling for awhile don't need too much additional practice to be able to do at least a few blindfolded catches just because of how consistent your throws get after awhile.

The other thing that's interesting is how pattern recognition in flying things people aren't generally used to seeing develops. I used to play ultimate, and when people start learning how a frisbee flies they might be susceptible to chasing it down by following along the path of the disc rather than moving directly to where it's going to end up. This is sometimes called dogging the disc because (many) dogs do the same thing. But then you learn to "read" the disc and you can tell by the flight path and angle of the disc where it's going to land.

[-] TheReturnOfPEB@reddthat.com 17 points 2 weeks ago* (last edited 2 weeks ago)

microslippages: some of us just call it what it is ... masturbation

[-] Emerald@lemmy.world 13 points 2 weeks ago* (last edited 2 weeks ago)

I always thought about how interesting it is that handing things to people is so reliable. We just kind of know exactly when the other person has grabbed something enough for us to let go.

[-] NikkiDimes@lemmy.world 17 points 2 weeks ago

And then there's the rare moment when you think they have it so you let go and it falls to the floor 😭

[-] Tarquinn2049@lemmy.world 12 points 2 weeks ago* (last edited 2 weeks ago)

A lot of it is the difference between learning practically and learning theoretically. You don't have to understand the underlying mechanics in practice to know how to keep getting the same result. Your brain doesn't have to be doing any math, it just has to have shaken a bottle enough times to have a good comparative basis formed.

Learning to calculate the current remaining volume in a container when observing someone else shake it.... that would use all that theoretical knowledge and math.

It's like knowing how hard you have to throw an egg at a wall for it to break instead of bounce off. You do it 100 times, you just get a good feel for it. Doing all the math, and then trying to learn it practically is barely gonna affect how quickly you learn it in practice. But if you wanted to make a robot that throws it exactly hard enough without wasting any energy, practical knowledge will have almost no value, and theory and math will be incredibly valuable.

This is coming from someone who does indeed have the whole "passive trajectory analysis of every moving object around me" thing. I can't do crowds or drive at busy times. But, for moving through a minor crowd while reading a book, or pulling into a tight parking space while other cars are moving around near me, it's very helpful. I have good spatial awareness in general, like parking in my garage with only an inch of clearance on the far side of my car has never been an issue in 14 years so far. Or when doing it with someone else's borrowed car every now and then too. When I shrug off the difficulty of doing something like that, people seem to be amazed. Otherwise, I would have assumed it was normal, feels normal to me.

[-] pancake@lemmygrad.ml 12 points 2 weeks ago

The overwhelming majority of all neurons in our body are just for controlling movement. Ironically, things like language or creativity require very little of our computing power and might be replicated by machine learning and a sufficiently beefy computer. But complex motor tasks? We're way ahead of our current tech on that.

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this post was submitted on 15 Nov 2024
1271 points (99.5% liked)

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