Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking. Pay there and welcome to Forward Thinking, the
Speaker 1: podcast that looks at the future and says, but my
Speaker 1: words like silent raindrops fell and echoed in the wells
Speaker 1: of silence. I'm Jonathan Strickland and I'm Joe McCormick. And today, Yes, Joe,
Speaker 1: we're going to be zooming in and enhancing the topic
Speaker 1: we've talked about before. Yeah. We we talked about zoom
Speaker 1: and Enhanced a while ago, right, we did one way
Speaker 1: back in Uh, you know, I haven't gone back and
Speaker 1: listened to any of our episodes from in a while,
Speaker 1: but I don't know. I feel like I'd be embarrassed
Speaker 1: to hear myself. Then we have learned a lot about podcasting.
Speaker 1: I've forgotten more than I've ever learned. Wait what No, anyway, So, yeah,
Speaker 1: we we recorded one about zoom and Enhanced with image
Speaker 1: imagery back in August two thousand teen. We're recording this
Speaker 1: at the beginning of September two thousand fifteen, so it's
Speaker 1: been more than two years. So clearly, first of all,
Speaker 1: we finally solve that zoom and enhanced for video and
Speaker 1: pictures right, That's that's done. Now you can take like
Speaker 1: a highly pixelated JPEG and turn it into a full
Speaker 1: motion three D video and it doesn't matter if that
Speaker 1: image was taken seventy years ago. You can still do it,
Speaker 1: you know. I came across just recently. Uh, my wife
Speaker 1: Rachel and I have been going back through The X
Speaker 1: Files because it's up on Netflix, and and and uh Christian,
Speaker 1: our our colleague Christian who's also on Stuff to Blow
Speaker 1: your mind with me and Lauren, there have been like,
Speaker 1: you've got to watch the X Files, so we have,
Speaker 1: and we came across an episode that has probably the
Speaker 1: most egregious and ridiculous case of zoom and enhanced I
Speaker 1: have ever seen in any show. It's an episode where
Speaker 1: there is a character who does psychic photography, so he
Speaker 1: like gets near a camera and whatever is going on
Speaker 1: in his head ends up on the film, and it's
Speaker 1: this polaroid of somebody's vision of some hellish nightmare escape
Speaker 1: with these ghosts called howlers screaming around a woman's face,
Speaker 1: and then in the background there's this little blur and
Speaker 1: and Moulder goes to the lab where they zoom and
Speaker 1: enhance the little blur and then they get this perfectly
Speaker 1: resolved picture of a guy's face from a polaroid. Yeah,
Speaker 1: seems like that might be a little far fetched. Um. Yeah,
Speaker 1: as it turns out, we do not have this magical capability.
Speaker 1: Things have improved since two thousand thirteen. You know, the
Speaker 1: basic premise of zoom and enhances all about you take
Speaker 1: you take an existing video or image, you concentrate your
Speaker 1: view on one particular sector of that image, and then
Speaker 1: you zoom that in and you are in and swing
Speaker 1: the pictures so that it is more uh, that you
Speaker 1: can see what it is. And for one thing, we've
Speaker 1: got super high resolution cameras now, so there's some that
Speaker 1: are so high resolution that a normal view you'd be
Speaker 1: looking at you know, like a like a YouTube video,
Speaker 1: something along that size. And then it turns out that
Speaker 1: the resolution is so high you could digitally punch into
Speaker 1: parts of that video and not lose a lot of resolutions.
Speaker 1: So it gives you the effect of zoom and enhanced.
Speaker 1: But really it's not enhancing. It's just that information is
Speaker 1: already there. Yeah, and that's the key. The information is
Speaker 1: already there. We have never gotten and we will never
Speaker 1: get to a point where there can be information retrieved
Speaker 1: from an image that was not recorded in the image.
Speaker 1: Now we can have it simulated. Right. That's exactly what
Speaker 1: we're going to talk about today, is finding ways to
Speaker 1: use what information is recorded in the image and do
Speaker 1: very smart things with it with computer programs. Right. And
Speaker 1: the really cool thing is that we're not talking about
Speaker 1: actual like images as the end result in this case, right,
Speaker 1: we are talking about using images to reconstruct sound. Yeah.
Speaker 1: And this all comes to us because we watched a
Speaker 1: TED talk in which a computer scientist named Aid Davis
Speaker 1: talked about a really interesting project that involved cameras and
Speaker 1: uh not necessarily well, I guess inanimate objects really and
Speaker 1: being able to reconstruct sound that took place near that
Speaker 1: inanimate object as if that inanimate object itself were a microphone.
Speaker 1: Say that all again? All right, so, um, there's this
Speaker 1: guy named Aimed Davis. No no, no, no, no. The
Speaker 1: relevant part it does what sound? So yeah, it acts
Speaker 1: as if any object itself is a microphone, not in
Speaker 1: the sense of amplifying what was said, but in the
Speaker 1: sense of of being being a record of what was said,
Speaker 1: Like the vibrations of the material itself are able to
Speaker 1: inform us enough that we can we can replicate the
Speaker 1: sound that was created. Yeah, he's he's part of this
Speaker 1: team that includes other researchers at m I t he's
Speaker 1: a he's a grad student or possibly a graduate of
Speaker 1: m I t UH and also scientists over at Microsoft
Speaker 1: and Adobe. And this is so cool. Yes, this, So
Speaker 1: this is a synesthesia machine. It sees sound. This it's
Speaker 1: like it took a bunch of LSD and began to
Speaker 1: see the music. Except that's what literally that they can do. Now. Yeah,
Speaker 1: it's and and when you start to break down what's
Speaker 1: going on, it starts to be less magical, but no
Speaker 1: less amazing. All right, So let's let's take some of
Speaker 1: the mysticism and magic out first. And to do that,
Speaker 1: we have to talk about what sound is, which we've
Speaker 1: done on this show before, but I'm going to give
Speaker 1: a quick rundown. So sound is really the energy of vibration, right,
Speaker 1: So when something vibrates, that's when it's creating a sound.
Speaker 1: And as long as there is some sort of medium
Speaker 1: for that sound to travel through, such as air exactly,
Speaker 1: water or the wood of a table that you've put
Speaker 1: your head down on, right, any of these things. Metal
Speaker 1: mask around your head hatchet. Now you're just giving Aaron
Speaker 1: Cooper father for the next next image. Alright, So but yes,
Speaker 1: as long as there's a medium through which sound can travel,
Speaker 1: it will travel as far as it possibly can before
Speaker 1: the energy has essentially dissipated. And this is why sound
Speaker 1: does not really does not travel in space because space
Speaker 1: is effectively a vacuum. So there are no particles, there's
Speaker 1: no medium through which the sound can travel. But here
Speaker 1: on Earth we've got air, thank goodness, because this is
Speaker 1: where I keep all my stuff, and air can act
Speaker 1: as a medium through which sound can travel. So what
Speaker 1: happens is when something vibrates, h, it begins to pull
Speaker 1: and push uh, the air around it. So if you
Speaker 1: imagine a vibration, some of those vibrations are going to
Speaker 1: move inward based on your perspective, that's gonna pull air
Speaker 1: toward it. Sometimes it's going to be moving outward, pushing
Speaker 1: air away from it. So think of like a a
Speaker 1: vibrating string on a guitar or a vibrating drumhead. Uh,
Speaker 1: that's going to be pushing and pulling air. Now that air,
Speaker 1: in turn, is going to be pushing and pulling the
Speaker 1: air molecules around it, and so on and so forth.
Speaker 1: It's this great, big chain reaction because our atmosphere is
Speaker 1: a giant fluid, right, It's it's a gas, but it's
Speaker 1: it's a It acts as a fluid. So these various
Speaker 1: molecules will continue to push and pull, and then eventually
Speaker 1: that motion will make it into the air inside of
Speaker 1: your ears. So it's not that the air molecules that
Speaker 1: were next to the strumming string on the guitar have
Speaker 1: magically made their way to your ear. It's rather that
Speaker 1: that motion has continued to move up at the speed
Speaker 1: of push to your to the air inside your ears. Sure,
Speaker 1: now at that point it ends up vibrating your ear drum,
Speaker 1: which then goes through this whole complicated series of maneuvers
Speaker 1: where you're talking about tiny bones and the cochlea and
Speaker 1: fluid and we're not going to get into this to
Speaker 1: how hearing works. You can actually read an amazing article
Speaker 1: at how stuff works dot com on how hearing works
Speaker 1: that explains it. But our brains ultimately interpret this motion
Speaker 1: as sound. Now, of course, the key fact here is
Speaker 1: that sound is vibration, and that vibration is something that
Speaker 1: you could in theory. See, yeah, if you could see
Speaker 1: fast enough, and if you could tell what you were
Speaker 1: looking at. Yeah, if you could see with the ability
Speaker 1: to really notice minute changes. I said fast enough, I
Speaker 1: should have said I guess fast enough enough frames per
Speaker 1: second and with enough resolution ship Yeah right. So, uh,
Speaker 1: you know this is like there's certain videos where if
Speaker 1: you do you know, high speed photography, high speed film,
Speaker 1: you can see how how something like a tuning fork,
Speaker 1: when you strike it and it's vibrating, you can actually
Speaker 1: see how it's moving in and out of its normal alignment,
Speaker 1: and it looks really freaky because when you just look
Speaker 1: at it with our normal eyes are normal ability to perceive,
Speaker 1: it doesn't really have that, you know, you don't see
Speaker 1: it distorting like it does in that high speed video.
Speaker 1: But uh, if we could see it, and if we
Speaker 1: could then interpret those vibrations, if we if we knew,
Speaker 1: all right, it's vibrating at this speed and this amplitude,
Speaker 1: that would tell us the pitch and volume of the
Speaker 1: sound that was affecting it, if we knew enough of
Speaker 1: the properties of the material itself. So that's the basis
Speaker 1: of the experiment that these folks from in my Tea
Speaker 1: were following, and it was all about kind of pointing
Speaker 1: a camera at an object, a camera that was capable
Speaker 1: of detecting these minute changes, these these movements of that object,
Speaker 1: and then feeding that through a computer that had an
Speaker 1: algorithm that could interpret those changes as sound and then
Speaker 1: reconstruct the sound that must have happened to produce those changes.
Speaker 1: And the results are pretty amazing. Yeah, I have to
Speaker 1: say I was really impressed. I am astonished. Yeah. Yeah,
Speaker 1: it was one of those things where well, first of all, uh,
Speaker 1: they decided to use Mary had a Little Lamb as
Speaker 1: a lot of their their you know what they would
Speaker 1: try to record, right, which is a throwback to experiments
Speaker 1: that Edison was doing way back when. Yeah. The first,
Speaker 1: the earliest recording that we know of that tom as
Speaker 1: and made dates to eighteen seventy eight. It was on
Speaker 1: a device that recorded messages onto tinfoil. Interestingly, the scholarship
Speaker 1: suggests that it wasn't Edison himself that provided the voice.
Speaker 1: It was probably someone else, but the voice says he made.
Speaker 1: The voice says Mary had a little Lamb, And it's
Speaker 1: very loud and very deliberate because the technology was brand
Speaker 1: new and it was not high fidelity by any stretch
Speaker 1: of the imagination. So this is kind of a a
Speaker 1: sort of genuflecting to history, saying, well, that this was
Speaker 1: a significant moment in history. We're going to use that same, uh,
Speaker 1: that same idea when we're trying this new experiment. And
Speaker 1: it worked like that. They did both tones of the
Speaker 1: song Mary had a Little Lamb, and they also did
Speaker 1: spoken variations of Mary had a Little Lamp, which in
Speaker 1: the Ted talk I highly recommend you watch it. It's
Speaker 1: very entertaining. Abe Davis is actually very entertaining presented. He
Speaker 1: talks about how he he shot a you know, one
Speaker 1: of the videos. He shows the video of him shouting
Speaker 1: at an empty bag of potato chips. Yeah. Yeah, it
Speaker 1: is a very technical experiment that definitely involves M. I. T.
Speaker 1: Grad students yelling the lyrics to Marry had a Little
Speaker 1: lamb at empty bags of potato chips. Right. He even
Speaker 1: talks about how, you know, originally they wanted to have
Speaker 1: the best possible um a chance to be able to
Speaker 1: pick up these vibrations. They knew that these uh, these
Speaker 1: vibrations were going to be tiny like a micrometer, like
Speaker 1: like a tenth of a micrometer. Yeah, that's super tiny.
Speaker 1: So they wanted to be able to get that with
Speaker 1: a pretty high resolution high speed camera, and they had
Speaker 1: to use a lot of light because these high speed
Speaker 1: cameras that you know, the shutter speed is so fast
Speaker 1: that you need a lot of light to light your
Speaker 1: scene in order to get an image of what you're
Speaker 1: you're pointing the camera at. And he even talked about
Speaker 1: how the lights were so hot that on a previous
Speaker 1: experiment they melted the bag, the empty bag of potato
Speaker 1: chips as a result of this. So it was a
Speaker 1: lot of trial and error early on, but it worked. Yeah. So,
Speaker 1: so they were using objects like like bags of potato chips,
Speaker 1: empty bags of potato chips, and potted plants. And the
Speaker 1: camera that they were using for these first experiments was
Speaker 1: was a high speed camera could capture at two thousand
Speaker 1: to six thousand frames per second, which is a higher
Speaker 1: frequency than the audio signal. But it certainly isn't like
Speaker 1: like the highest possible end high speed camera on the market,
Speaker 1: Phantom or anything. Yeah. Yeah, yeah, the the highest speed
Speaker 1: cameras run something like a thousand a hundred thousand frames
Speaker 1: per second. Sorry, And the software could could pick up
Speaker 1: these tiny, these tiny, tiny movements. Um a tenth of
Speaker 1: a micrometer is something like five thousands of a pixel,
Speaker 1: and it could do that thanks to very subtle changes
Speaker 1: and in each pixels color values at the edges of
Speaker 1: the objects that were being studied. So yeah, and it's
Speaker 1: also that he pointed out in the TED talk that
Speaker 1: it's not like the camera was pointed at one particular,
Speaker 1: tiny little edge of one of these objects. It could
Speaker 1: actually take into account all of the different vibrations happening
Speaker 1: across the object, and that collectively that provided the data
Speaker 1: necessary for them to be able to reconstruct the audio. Right.
Speaker 1: It's rooted in research from from m I t S
Speaker 1: Computer Science and Artificial Intelligence Laboratory, and the software that
Speaker 1: that team was developing was originally intended to amplify color
Speaker 1: changes in video, but then they realized that that it
Speaker 1: could thereby amplify motion, and so they bent it to
Speaker 1: to UH tasks like monitoring blood flow unobtrusively and then
Speaker 1: show that in the video right that they show the
Speaker 1: pulse of someone's arm. Because of these minute changes, they're
Speaker 1: able to amplif by that to the point where you
Speaker 1: can actually see the pulse, which is, by the way,
Speaker 1: a little freaky sure, but also pretty cool. And and
Speaker 1: so this this new team, this this acoustic team in
Speaker 1: built on top of that software, adding the algorithms that
Speaker 1: would identify the whole object and monitor its overall movements
Speaker 1: in order to create the the sound goodness. And it
Speaker 1: was interesting because once they determined that they could capture
Speaker 1: the motion under those quote unquote ideal circumstances with the
Speaker 1: bright lighting and the high speed camera, they started to
Speaker 1: test how far outside of those ideal circumstances they could
Speaker 1: still capture meaningful information and be able to replicate the
Speaker 1: sound that occurred next to that physical object. And you know,
Speaker 1: the idea being that you would be able to replicate
Speaker 1: sound even if there were no microphones, no official microphones working.
Speaker 1: So they it up testing it with normal daylight, providing
Speaker 1: the lighting and shooting through a soundproofed window. So the
Speaker 1: camera was on one side of the window, the object
Speaker 1: was on the other side of the window, another empty
Speaker 1: back of chips, yep, and and that's where the sound
Speaker 1: was generator was on the other side of the soundproof windows.
Speaker 1: So uh, in theory, there shouldn't have been any sound
Speaker 1: bleed over into the camera and they could still pick
Speaker 1: up sound that way clearly. Yeah. Um, and with normal
Speaker 1: indoor light. They filmed a pair of earbuds like normal plastic,
Speaker 1: cheap out earbuds, and then reconstructed the music that they
Speaker 1: were playing well enough that they successfully shazammed the music
Speaker 1: and it was under pressure, which I realized now that
Speaker 1: I should have used a lyric from that from the
Speaker 1: beginning of the show, but never mind that. Uh They
Speaker 1: also furthermore found that they could use a standard camera,
Speaker 1: not a high faluten camera. And we're talking standard like
Speaker 1: like sixty frames per second smartphone camera or you know something.
Speaker 1: You could run out and buy a target. And this
Speaker 1: is thanks to a quirk and how standard digital cameras
Speaker 1: handle fast moving objects. It would be more accurate for
Speaker 1: for them to read measurements off of your whole array
Speaker 1: of photo detectors at the same time, but that is
Speaker 1: kind of expensive, so uh so cameras that are less
Speaker 1: expensive than than super high speed cameras instead read off
Speaker 1: of their photo detectors one row at a time, sort
Speaker 1: of like scan line televisions. And it does this very
Speaker 1: quickly but not instantaneously sure, and it can lead to
Speaker 1: that weird lag that you might have noticed in some
Speaker 1: videos of high speed objects, like sort of jagged edges
Speaker 1: or extra pixelation when the object is moving faster than
Speaker 1: the software can can handle. Yeah. I think in the
Speaker 1: m I T article we read, they use the example
Speaker 1: of a rotor blade of a helicopter. Right. Sure, sure,
Speaker 1: it might be spinning so fast that it's not going
Speaker 1: to capture it the same way your eye would see it,
Speaker 1: but it's going to scan the blade in a different
Speaker 1: position each line, right, and uh on, on a much
Speaker 1: smaller level, invisible to the naked eye. This flaw in
Speaker 1: in normal cameras creates visual artifacts that the researchers found
Speaker 1: out that they could use in order to measure subtle vibrations.
Speaker 1: So the audio reconstructions that they got out of this
Speaker 1: experiment weren't as close to the original audio, but the
Speaker 1: researchers did report that they could probably still identify like
Speaker 1: the number of speakers in a room, or the identity
Speaker 1: of a speaker, given that you have an audio profile
Speaker 1: of the person's voice to begin with. Yeah, so, uh
Speaker 1: definitely a little more like um muted and a little
Speaker 1: more distorted, to the point where if you had not
Speaker 1: already heard what was being said, you might not be
Speaker 1: able to necessarily reconstruct it. Um. Our brains are interesting, right,
Speaker 1: Like if we hear what we're supposed to hear, and
Speaker 1: then we hear the sound played, were more likely to
Speaker 1: pick it out. Uh. This is something that you find
Speaker 1: and people who claim for for like you know, hidden
Speaker 1: messages and backmasking and that kind of stuff. Yeah, if
Speaker 1: you if you listen to the raw sound file without
Speaker 1: any prompting, you may end up saying I didn't make
Speaker 1: anything out and then someone says, oh, you need to
Speaker 1: listen for the phrase, um help me, Jonathan has me
Speaker 1: trapped in the basement. You might end up hearing it.
Speaker 1: I try very hard to make sure don't hear it,
Speaker 1: but you might hear it. Okay. So anyway, that's when
Speaker 1: you play under pressure backwards. Oh vo vovo oh, Freddie Mercury.
Speaker 1: Other methods that you can use to pick up sound
Speaker 1: from a distance. Uh. Some of them use a similar method,
Speaker 1: Like there's one that uses lasers, and in fact, at
Speaker 1: the TED talk, Davis actually says this particular approach, a
Speaker 1: lot of people might immediately spring to the conclusion that
Speaker 1: you would use it to spy on someone, you would
Speaker 1: aim a camera in at something that would be kind
Speaker 1: of unobtrusive, like a potted plant that happens to be
Speaker 1: near a person's desk, and then you could end up
Speaker 1: replicating conversations that went on inside that room by just
Speaker 1: measuring the vibrations of that plant and then running it
Speaker 1: through this algorithm to recreate the sound that happened. Most
Speaker 1: evil plots take place in a room with a potted plant. Yeah,
Speaker 1: you know. Uh, yeah, that's why I only use cacti now,
Speaker 1: But even they have have been deceptive. So the the
Speaker 1: point that Davis makes is that this is pretty low fidelity.
Speaker 1: If you want to do something like that, and if
Speaker 1: you really want to do that, there are alternatives that
Speaker 1: provide much higher quality recordings, uh, mainly using laser microphones. Now,
Speaker 1: you guys heard of laser microphones before we started looking
Speaker 1: into this, No, I don't think I had. It was
Speaker 1: one of those things that I had heard about only
Speaker 1: because I was looking through the Spy Museum in Washington,
Speaker 1: d C. And And read about them. So they work
Speaker 1: on a very similar principle, except instead of detecting the
Speaker 1: vibrations optically, what they're doing is they're using it's still optical,
Speaker 1: but it's not you know, like a visual approach. Um
Speaker 1: you're shooting a laser out at an object and as
Speaker 1: that object vibrates when it is exposed to sound the
Speaker 1: returning laser light. Because you know, it's all based on
Speaker 1: shooting a laser out and then detecting when it comes back,
Speaker 1: the returning laser light will have slightly different arrival times
Speaker 1: than when it was sent out based on those vibrations
Speaker 1: of it's vibrating out, it's going to be a little
Speaker 1: shorter than if it's vibrating in. And while that sounds
Speaker 1: incredibly minute, and it is, it's enough to be able
Speaker 1: to take that data, feed it back through and create
Speaker 1: a sound file based on it, so you could replicate
Speaker 1: things that are being said or other sounds that are
Speaker 1: going on. And in fact, there are a lot of
Speaker 1: places that that due to their classified nature, due to
Speaker 1: the secrecy of stuff that goes on inside, they take
Speaker 1: great pains to try and obvious skate any view into
Speaker 1: the place, whether that's creating sort of a double glazing
Speaker 1: on the window so it disperses the laser beam and
Speaker 1: thus the laser beam can't get a good read um
Speaker 1: or other elements as well. So that's super spy stuff
Speaker 1: that most of us don't have to worry about. But
Speaker 1: as Davis would say, that is a more relevant fear
Speaker 1: than someone using a camera to look in Um, that's
Speaker 1: not as likely. I mean, why would you do. It's expensive,
Speaker 1: but you do have to get your access to the
Speaker 1: algorithm though. That's true, that's true. No, I've got another
Speaker 1: technology in mind. That's where you just grab somebody from
Speaker 1: the room and throw them in a van and demand
Speaker 1: to know what was said. That's not so much a
Speaker 1: technology as it is a valid strategy. Hey, vans are
Speaker 1: a technology. You could just as easily throw them in
Speaker 1: the back of a horse drawn carriage. I mean, it's
Speaker 1: just which are also a technology? Options are list uh
Speaker 1: there of course also long range microphones. You probably have
Speaker 1: seen these advertise in the back of a comic book.
Speaker 1: Parabolic mic. Yeah, that's that's the really popular one. Like
Speaker 1: that's if you ever see, like the spy kits that
Speaker 1: are made for kids who are interested in this kind
Speaker 1: of stuff, there's usually some sort of parabolic mic and
Speaker 1: involved in that. Parabolic mics are meant to be sensitive
Speaker 1: and directional. They're not terribly good at being directional, but
Speaker 1: the really high powered ones are fairly sensitive. Uh. So
Speaker 1: the idea is that you're you're concentrating on a specific
Speaker 1: area to try and pick up sound from that area
Speaker 1: while trying to block sound from as other from all
Speaker 1: the other directions as much as possible. Right, Because as
Speaker 1: as you keep turning up sensitivity in any kind of recorder,
Speaker 1: you're going to increase your noise. Yeah, it's it's like
Speaker 1: turning up the gain on a microphone. If you crank
Speaker 1: that way up, you're gonna get a lot of noise,
Speaker 1: and and it's gonna be harder for you to concentrate
Speaker 1: on the signal. Uh. There are a lot of different
Speaker 1: models of long range microphones, and they all have varying
Speaker 1: degrees of directionality and sensitivity and and uh, but they
Speaker 1: all work on basically the same principle, the idea of
Speaker 1: boosting an acoustic signal to the point where you can
Speaker 1: hear it where normally you would not be able to.
Speaker 1: There are not very many out there that are uh
Speaker 1: powerful enough and and effective enough to be able to
Speaker 1: listen to a conversation beyond like fifty meters away, unless
Speaker 1: people are shouting, in which case you probably go a
Speaker 1: little further, but um, you know that they have their limitations.
Speaker 1: Whereas the laser, I mean, as long as you have
Speaker 1: a line of sight, you could in theory be really
Speaker 1: far away from the actual conversation taking place and be
Speaker 1: able to replicate it. Also, depending on who the person
Speaker 1: spuying on you is, they could just listen to you
Speaker 1: through your cell phone. Yeah, there are a lot of
Speaker 1: other options right, um, but at any rate, so if
Speaker 1: this is not really good as a spy technology, what
Speaker 1: else could we use it for? Well, it could be
Speaker 1: used to reconstruct conversations for court cases and and forensics
Speaker 1: within the justice system. Yep. Of course it requires that
Speaker 1: you have had a camera in place of that area
Speaker 1: in the first place. But yes, but many places do
Speaker 1: be paranoid everyone. It could help out in hospitals that
Speaker 1: the kind of software could monitor vital signs like like
Speaker 1: breath and blood flow from a distance, like we were
Speaker 1: talking about earlier, which would be especially useful in cases
Speaker 1: where you want to disturb the patient as little as possible,
Speaker 1: which I would I would posit as everyone, but but
Speaker 1: especially like infants. Yeah, theah people who who might not
Speaker 1: be able to alert you in a change like especially
Speaker 1: a sudden change in their health. This would be very
Speaker 1: useful to monitor that type of stuff and get a
Speaker 1: very early look at it. Or hey, uh, laper scopy
Speaker 1: is pretty cool putting cameras where cameras don't usually go
Speaker 1: into human bodies, and you could use this to take
Speaker 1: more precise measurements of what's going on inside of a
Speaker 1: human body. Joe, have you ever wondered what your spleen
Speaker 1: sounds like? I don't need to wonder. It's voice whisper
Speaker 1: sweet nothings in my ear. That's better than my answer,
Speaker 1: which was I can show you, all right. So, going
Speaker 1: back to the Ted talk, Davis actually talked about how
Speaker 1: this could even tell us more about materials themselves and
Speaker 1: how they behave, which was really cool. The idea that
Speaker 1: it's kind of like reversing the the approach that they
Speaker 1: had been taking, where they were looking at the vibrations
Speaker 1: and determining what sound was being made to cause those vibrations. Instead,
Speaker 1: they end up measuring vibrations and then figuring out how
Speaker 1: that material would behave uh, depending upon the different types
Speaker 1: of stresses being put on that material. So the first
Speaker 1: example he shows was a it was a wire uh,
Speaker 1: like a wire sculpture of a of a human figure,
Speaker 1: and they had it on a on a surface like
Speaker 1: it's on a little pedestal and it was resting on
Speaker 1: like a shelf table or something. And you see a
Speaker 1: hand come into frame and bang on the surface quite
Speaker 1: a few times to create little vibrations in the wire frame.
Speaker 1: It was. It was to the tune of shaven a
Speaker 1: haircut two bits, And they ended up measuring this with
Speaker 1: their camera equipment, but instead of trying to recreate the
Speaker 1: shaven a haircut knock, they did it to find out
Speaker 1: how this material behaves when stresses are put on it,
Speaker 1: and their algorithm could then simulate that material's behavior and
Speaker 1: they could virtually drag any part of that material and
Speaker 1: then let go to see how it would snap back
Speaker 1: into place, uh, creating kind of this virtual model but
Speaker 1: using real imagery. It was really interesting. Yeah. Yeah, And
Speaker 1: the this little wire figure was not the only thing
Speaker 1: that he showed a test of, right, he showed a bush.
Speaker 1: They ended up shooting video of a bush as it
Speaker 1: was moving through because of I believe it was a
Speaker 1: breeze that was just blowing. Yeah, it was just a
Speaker 1: shrub outside of his apartment, I think, and then they
Speaker 1: were able to with getting enough of that information, they
Speaker 1: were able to then recreate that as well. And so
Speaker 1: you have this image of the bush and he could
Speaker 1: pick any point of it and virtually pull on it,
Speaker 1: and it would show how that bush would move, and
Speaker 1: it looks like it's just video that's been shot of
Speaker 1: this bush as someone has you know, kicked it or something.
Speaker 1: And also showed a like a curtain or a tapestry
Speaker 1: hanging and how that would move based upon the same
Speaker 1: sort of thing, like based upon the source of stresses
Speaker 1: you could put on it, whether you're tugging at one
Speaker 1: corner or the center or whatever, how it would ripple
Speaker 1: back into place. And this was based on extremely small,
Speaker 1: like like invisible emotions to the eye. In the case
Speaker 1: of the curtain, it was just just tiny currents of
Speaker 1: air that we're moving through the room. And so it
Speaker 1: was really really striking getting to watch it, you know. Artistically,
Speaker 1: this kind of thing could let filmmakers adjust the motion
Speaker 1: of objects after a video has already been shot, like
Speaker 1: if if if hair was was blowing the wrong way
Speaker 1: in in in a shot, because you've because you've kind
Speaker 1: of you've kind of plastered a couple different a couple
Speaker 1: different frames together or something like that. Then you could
Speaker 1: move the hair in another direction. Do you remember that
Speaker 1: phase in the history of video games, video games when
Speaker 1: they were no when everyone was obsessed with hair blowing
Speaker 1: in the wind. I don't think we're over there. Remember
Speaker 1: it's happening today. I mean, that's like the thing that
Speaker 1: all graphics boasting referred to. Look at this character's hair.
Speaker 1: It's the hair and it's water. Doesn't like the water
Speaker 1: effects and the hair effects. But no, I was gonna say, like,
Speaker 1: this could create a new era of full motion video
Speaker 1: video games. Finally, finally, we've been waiting for it exactly.
Speaker 1: The reason we don't have that yet is that we
Speaker 1: don't know what to make these characters look like when
Speaker 1: they're supposed to jiggle. I am looking forward to the
Speaker 1: resurgence of the emotion video video game because I need
Speaker 1: to make sure that I have a transition plan for
Speaker 1: when I am finished doing my futurism. I need to
Speaker 1: have another career to move into, and I think FMV
Speaker 1: actor in low budget video games is my niche. You know,
Speaker 1: if Tim Curry can do it, you can do it too. Yeah,
Speaker 1: nowhere near the panache that Mr Curry had in things
Speaker 1: like that Frankenstein game. Well, work on it. Also, your
Speaker 1: listeners over tech stuff would be so happy. That's true.
Speaker 1: That's true. So we will see if that day arrives.
Speaker 1: But more practically, it could let engineers test structures for whear,
Speaker 1: like like predict damage from earthquakes, important things like that. Yeah,
Speaker 1: it's really kind of an interesting way of advancing our
Speaker 1: knowledge of material science in an indirect fashion. It's pretty amazing. Uh.
Speaker 1: Also could tell us things about like resonant frequencies, that
Speaker 1: sort of stuff, which again is very similar to making
Speaker 1: sure you're you're in engineering things properly in the case
Speaker 1: of earthquakes or you know, we've we've heard the horror
Speaker 1: stories about bridges and resonant frequencies. That kind of stuff
Speaker 1: really fascinating And uh, we're sitting in an audio studio
Speaker 1: right now. I wonder if it could have applications in
Speaker 1: trying to figure out how to best insulate how the
Speaker 1: best baffle sound studio, which we often find baffling. All right, Well,
Speaker 1: on that note, members of the audience, have you ever
Speaker 1: heard drilling in a forward thinking podcast? We tried to
Speaker 1: edit most to the drilling out, but sometimes some drilling
Speaker 1: might get through. Yeah, I blame Ben Bolan and his
Speaker 1: search for lost gold, but uh, you know. Anyway, Guys,
Speaker 1: if you have suggestions for future topics we can tackle
Speaker 1: here on Forward Thinking, whatever they may be, you should
Speaker 1: write us and let us know. The email address is
Speaker 1: FW thinking at how Stuff Works dot com, or you
Speaker 1: can drop us a line on Twitter or Google Plus.
Speaker 1: We are FW thinking at both of those places. Our
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Speaker 1: can leave us a message and we'll talk to you
Speaker 1: again really soon for more on this topic and the
Speaker 1: future of technology. This is forward sinking dot Com, brought
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