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Speaker 1: Technology with tech Stuff from stuff dot Com. Hey there,

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Speaker 1: and welcome to Tech Stuff. I'm your host, Jonathan Strickland,

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Speaker 1: podcaster extraordinaire with how stuff works. And as you guys know,

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Speaker 1: I loves me some technologies and that's what I'd like

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Speaker 1: to cover on this show. And in the past I've

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Speaker 1: covered concepts like Moore's law, and that can tend to

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Speaker 1: lead people into thinking that, because computer processing power effectively

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Speaker 1: doubles every two years or so, that the entire world

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Speaker 1: is going to be transformed into a crazy techno wizard

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Speaker 1: world that you'd see in an imaginative science fiction film.

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Speaker 1: It's gonna happen any day now, and we're all headed

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Speaker 1: that way. It's a foregone conclusion. However, from a day

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Speaker 1: to day perspective, it doesn't seem like we're going all

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Speaker 1: that quickly, despite that amazing progress and computer process using power.

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Speaker 1: And one of the reasons there are many, but one

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Speaker 1: of the reasons for this is that while computer processing

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Speaker 1: power tends to follow that pathway that Gordon Moore observed

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Speaker 1: several decades ago, other aspects of technology aren't on quite

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Speaker 1: as predictable a path, nor do they advance at such

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Speaker 1: a reliable accelerated rate. And because of that, because some

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Speaker 1: aspects of technology lag behind the development of processing power,

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Speaker 1: we don't get that crazy future that we've been promised

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Speaker 1: since say the nineteen fifties. Now, one of those aspects,

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Speaker 1: one of the things that does not evolve as quickly

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Speaker 1: as processing power, would be user interfaces. Now, these are

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Speaker 1: the ways that we interact with our devices, such as

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Speaker 1: our computers. So the typical computer user, they're usually relying

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Speaker 1: upon your basic keyboard and mouse combination. It's the same

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Speaker 1: thing that's been in place, say the nineteen eighties and

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Speaker 1: personal computers. Xerox Park was introducing things like the mouse

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Speaker 1: and the graphic user interface much earlier than that, but

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Speaker 1: it was really the Apple Macintosh that brought the graphic

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Speaker 1: user interface and the mouse along with the keyboard to

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Speaker 1: the personal computing space. The keyboard, of course, had already existed. Uh,

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Speaker 1: there's a problem with this type of interface. There's actually

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Speaker 1: a couple. But one is that it requires users to

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Speaker 1: be both able to manipulate the input devices, which would

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Speaker 1: be the keyboard and mouse. You have to actually be

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Speaker 1: able to move them in order to interact with your computer.

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Speaker 1: And the other problem is that there's a learning curve.

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Speaker 1: You actually have to learn how to use those devices

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Speaker 1: in order to interact with your computer properly. It's not

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Speaker 1: a natural way to interact with a machine, or with

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Speaker 1: anything else. It's not the way we tend to interact

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Speaker 1: with the stuff in our everyday world. We don't have

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Speaker 1: to type out codes or move a random part of

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Speaker 1: an object in order to make something else move. We

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Speaker 1: are much more direct with our input whenever we are

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Speaker 1: interacting with our environment. So in order to learn how

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Speaker 1: to use a computer, we actually have to go through

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Speaker 1: this process of learning how keyboards and computer mices work.

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Speaker 1: Otherwise nothing much gets done. Now that's not to say

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Speaker 1: that once the keyboard and mouse combo came out we

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Speaker 1: stopped trying to find ways to interact with technology, because

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Speaker 1: engineers have been working on everything from light pens to

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Speaker 1: touch screens, to gesture controls to voice commands all the

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Speaker 1: way back to when the keyboard and mouse started to

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Speaker 1: become a thing. And this is all in an effort

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Speaker 1: to broaden the way we control computers and electronics. And

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Speaker 1: I've covered some of those technologies in earlier episodes of

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Speaker 1: Tech Stuff, and I've explained that many of them, like

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Speaker 1: voice recognition do not follow a path that's nearly as

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Speaker 1: accelerated as processing power. We've gotten really good with voice

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Speaker 1: recognition over the last say, five or six years, but

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Speaker 1: for many years it was lagging behind other technologies. And

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Speaker 1: this is the problem with making those big promises about

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Speaker 1: what the future is going to be like. Often that

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Speaker 1: is based on an assumption that everything is moving forward

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Speaker 1: at the same speed, and that's just not true. Well,

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Speaker 1: today I wanted to cover a specific type of technology

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Speaker 1: that can be used in user interfaces, although that's only

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Speaker 1: one application of this technology, and that is eye tracking technology.

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Speaker 1: A bit later in this episode, I'm going to play

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Speaker 1: an interview I had with Oscar Werner of Toby Tech,

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Speaker 1: and Toby Tech is a business unit of a company,

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Speaker 1: Toby that is pioneering eye tracking technology for all sorts

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Speaker 1: of applications, both on the business to business side and

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Speaker 1: the business to consumer side. But before I get to

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Speaker 1: that interview, I thought it might be interesting to talk

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Speaker 1: about the evolution of eye tracking in general, because it's

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Speaker 1: actually a really cool story, and you I learned stuff

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Speaker 1: I just didn't know, including stuff that schemed me out

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Speaker 1: a little bit. So I want to share my skiviness

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Speaker 1: with you. Wait, no, that's not right. I want to

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Speaker 1: share the stuff that schemed me out with you. My

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Speaker 1: skiviness is a matter for my own personal life. Back

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Speaker 1: off alright, To begin with, eye tracking technology is the

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Speaker 1: product of a few different disciplines, and they originate from

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Speaker 1: different perspectives. You've got philosophical approaches, you have technical approaches,

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Speaker 1: you have biological approaches, and you also have human behavior

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Speaker 1: along with psychology and physiology. So in the eighteenth century,

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Speaker 1: which I feel I need to point out, was an

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Speaker 1: era that had very few personal computers in it because

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Speaker 1: they had not yet been invented. There was a guy

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Speaker 1: named William Porterfield, who should not be confused with professional

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Speaker 1: cricket player from Ireland, totally different person. This was William

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Speaker 1: Porterfield in the eighteenth century, an Englishman who made some

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Speaker 1: general notes about oculomotor behavior and reading, in other words,

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Speaker 1: how our eyes behave as we read text. Now, Porterfield's

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Speaker 1: work was not based off empirical evidence, but rather casual

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Speaker 1: observations and some hypotheses. But later scientists would study this

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Speaker 1: behavior in greater detail and with more rigorous scientific approaches.

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Speaker 1: So some of them looked at it from a physiological standpoint,

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Speaker 1: some looked at it from a philosophical standpoint. Some of

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Speaker 1: them combined the two, and a man named Louis Emil

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Speaker 1: Javal conducted a study of how our eyes behave when

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Speaker 1: we read text. He was working in the late nineteenth century,

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Speaker 1: around the eighteen sixties and eighteen seventies. He published his

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Speaker 1: work about the US in eighteen seventy eight, and he

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Speaker 1: made his observations by directly watching people's eyes as they

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Speaker 1: read lines of text. And he saw that when you

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Speaker 1: do that, your eyes don't just glide seamlessly across a page. Instead,

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Speaker 1: your eyes have lots of stops and starts. Those motions

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Speaker 1: he gave names, so he called every time you stopped,

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Speaker 1: when you would your eyes would pause as they went across,

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Speaker 1: he called those fixations. And he would call all the

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Speaker 1: bits where your eyes would move across rapidly Saccadays, those

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Speaker 1: would be the starts. Now, saccad comes from a French

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Speaker 1: word that was originally used to describe horse movements, and

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Speaker 1: a rough translation into English might be jerk, as in

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Speaker 1: the motion, not as in some jerk face who's giving

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Speaker 1: you a hard time. So Javal's work was interesting in that,

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Speaker 1: for the most part. The only studies in oculu motor

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Speaker 1: function up to that time were limited to diagnos sing

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Speaker 1: and perhaps treating dysfunction, so the work wasn't all about

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Speaker 1: learning more of what typical behavior is like. In other words,

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Speaker 1: doctors normally didn't think to look into the way our

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Speaker 1: eyes move unless something atypical was going on with the patient.

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Speaker 1: Javal started a movement in medicine and biology that, pardon

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Speaker 1: the pun, shifted the focus. Other scientists observed similar similar

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Speaker 1: oculomotor behavior, so this was all emerging around the same time.

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Speaker 1: There are actually quite a few people who were looking

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Speaker 1: into it, so to speak. Javal just became the most

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Speaker 1: famous of all those people. So I don't mean to

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Speaker 1: suggest he was the only one, but rather he's the

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Speaker 1: one that gets most of the credit, and that is

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Speaker 1: because of another person named Edmund Huey, who was a

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Speaker 1: clever fellow from the late nineteenth and early twenty centuries.

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Speaker 1: He made more progress in this study by creating an

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Speaker 1: invention that sounds like it came straight out of a

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Speaker 1: clockwork orange. It consisted of a plaster I cup that

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Speaker 1: would fit over a subject's I so it would go

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Speaker 1: right up against the person's eye, and the cup had

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Speaker 1: a lever attached to it that went off to the side.

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Speaker 1: At the other end of the lever there was a pen,

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Speaker 1: and the pen could move across a rotating smoked drum,

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Speaker 1: and thus the pen would make marks across the smoked

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Speaker 1: surface of this drum that rotated around. And the idea

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Speaker 1: was that this would allow you to look at those

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Speaker 1: marks and map that to I've movements that are happening

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Speaker 1: while you're actually giving the subject a test. So as

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Speaker 1: the subject's eyes would scan text, the movements of those

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Speaker 1: eyes would make the plaster cup move, which would transfer

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Speaker 1: that motion to the lever and ultimately to the pen

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Speaker 1: that was resting against the rotating drum. And this sounds

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Speaker 1: absolutely ghastly to me, but it gave valuable information to

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Speaker 1: Hueie about how people's eyes move when they're reading. Now,

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Speaker 1: in his papers on the subject, hue would refer back

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Speaker 1: to Javal's work and his research on the physiology of reading.

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Speaker 1: There were other scientists who are looking into this subject

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Speaker 1: as well, but Huey's work and the citation of Javel

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Speaker 1: have led many to simplify history and just say they're

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Speaker 1: the ones responsible for the research. On i've movements in

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Speaker 1: the early days. Later on, another scientist, George Malcolm Stratton,

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Speaker 1: would start to study how we move our eyes as

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Speaker 1: we perceive illusions. Now, this is really interesting. Optical illusions

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Speaker 1: depend upon our eyes perceiving something that is either not

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Speaker 1: there or is there in a way that is different

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Speaker 1: from the actual physical thing that we are perceiving, and

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Speaker 1: therefore the way our eyes behave is very important to

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Speaker 1: how those illusions work. What is it that's going on

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Speaker 1: physiologically with our eyes, how much of that is dependent

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Speaker 1: upon my behavior versus what's going on in our brains.

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Speaker 1: This would slowly lead scientists to the conclusion that our

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Speaker 1: eyes are really an extension of our brains, and that

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Speaker 1: the process of thinking is very closely, if not synonymously,

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Speaker 1: connected with the process of seeing. And I think that's

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Speaker 1: pretty cool too. Stratton's work would publish in the early

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Speaker 1: twentieth century and also help inform scientists and others about

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Speaker 1: the nature of our eyes. All of this is to say,

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Speaker 1: these early studies began to coalesce around that concept of

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Speaker 1: not just how our eyes move as we perceive, but

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Speaker 1: also where our focus tends to be directed. Knowing about

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Speaker 1: focus is important for lots of different fields, some of

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Speaker 1: which appear to be completely independent of technology and user interfaces.

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Speaker 1: For example, let's say that you are a graphics designer

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Speaker 1: and you have a job. You're given a contract, and

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Speaker 1: your job is to create a sign that will warn

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Speaker 1: people to potential danger. Maybe it's a warning sign for

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Speaker 1: let's say radioactive material, and you want to make sure

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Speaker 1: you get across to people that anything beyond that sign

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Speaker 1: could pose as a threat to that person's health. There

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Speaker 1: are many things you would have to consider before you

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Speaker 1: start making that sign. For example, which colors should you use.

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Speaker 1: You're gonna want something that's going to have a good

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Speaker 1: level of contrast, so that whatever the message is that

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Speaker 1: you're trying to convey will be easy for people to perceive,

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Speaker 1: even if people might have some form of color blindness.

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Speaker 1: Then you have to ask, all right, well, if there

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Speaker 1: are any words on there, what typeface should you use?

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Speaker 1: I mean, it needs to be easily legible, and where

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Speaker 1: do you draw the focus on this sign so that

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Speaker 1: the message you are sending gets to your audience and

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Speaker 1: they actually get the point. Being able to track eye

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Speaker 1: movement gives us more information about how we humans work,

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Speaker 1: not just how we can interact with stuff. As for

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Speaker 1: eye tracking technology, it thankfully evolved beyond the need for

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Speaker 1: eye cups and mechanical levers. Otherwise I would just be

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Speaker 1: running around screaming inside of the studio because I have

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Speaker 1: a thing about eyes. But one methodology still relied on

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Speaker 1: the subject wearing special equipment, and it was a system

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Speaker 1: consisting of a pair of contact lenses with a sort

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Speaker 1: of special feature, which is dependent upon the actual implementation

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Speaker 1: of the technology. Some versions would use contact lenses that

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Speaker 1: had a magnetic field sensor connected to them, or they

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Speaker 1: might have an embedded mirror that would reflect light, and

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Speaker 1: then you would have an external system that has partnered

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Speaker 1: at any given time, assuming that the contact lens fits

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Speaker 1: of the eye. Obviously, if that happens, then it's messing

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Speaker 1: the contact lens, not necessarily the movement of the eye itself.

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Speaker 1: But for something like a computer or a mobile device

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Speaker 1: for that, you probably don't want to deal with putting

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Speaker 1: in special contacts. So the interfaces that we're finding with

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Speaker 1: personal electronics and computers typically rely upon optical tracking. And

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Speaker 1: that means exactly what you think. It means. You're using

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Speaker 1: some form of camera to monitor where you are looking.

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Speaker 1: The device uses cameras that can detect your eyes using

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Speaker 1: it's looking for different aspects of eyes that are common

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Speaker 1: across many people. And once it identifies, all right, that's

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Speaker 1: an eye, then it starts to try and track where

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Speaker 1: using a system to set a baseline for this. You

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Speaker 1: can't just turn it on and start looking. You have

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Speaker 1: to calibrate it. So you calibrate the system so it

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Speaker 1: knows where you're looking. It might guide you into looking

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Speaker 1: at specific regions of a screen, whether it's a mobile

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Speaker 1: device or a computer or whatever it might be. And

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Speaker 1: that way, once it knows quote unquote that you are

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Speaker 1: looking where you're supposed to, it can then uh interpret

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Speaker 1: where your eye is looking from that point forward, because

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Speaker 1: it's calibrated from a known set of standards. And from

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Speaker 1: that point forward, assuming that everything is working properly, every

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Speaker 1: time you look at some other part of the screen,

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Speaker 1: the eye tracking software can track your gaze and know

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Speaker 1: exactly where you are looking. That's the basic idea behind it. Now,

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Speaker 1: when we listen to in on an interview in just

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Speaker 1: a few minutes, Mr Werner will explain how Toby's technology

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Speaker 1: accomplishes this. In particular, they have a specific kind of

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Speaker 1: approach to using cameras to track eye movements. It's not

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Speaker 1: that different from the way motion sensors like the Microsoft

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Speaker 1: Connect work, only obviously, eye tracking technology is more precisely

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Speaker 1: tuned to look at the movement of your eyeballs, not

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Speaker 1: your overall body. Now, this technology allows for all sorts

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Speaker 1: of potential applications, and some of them are passive, which

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Speaker 1: means that people can use the eye tracking data to

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Speaker 1: get an idea of where people direct their focus for

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Speaker 1: any given situation. So that might be when someone is

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Speaker 1: looking at an advertisement, or looking at a web page,

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Speaker 1: or playing a game. It can be more active. It

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Speaker 1: doesn't have to be a passive implementation, it can allow

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Speaker 1: people the chance to send input into a computer by

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Speaker 1: staring at specific parts of a screen. This is useful

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Speaker 1: for those people who may otherwise be unable to move.

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Speaker 1: They can use these kind of interfaces in order to communicate.

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Speaker 1: And there are countless other applications that exist now and

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Speaker 1: even more that we haven't even thought of yet. To

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Speaker 1: get a better idea of what this tech is all

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Speaker 1: about and how it might be used in the future,

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Speaker 1: I talked with Oscar Warner. He's the business unit president

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Speaker 1: of Toby Tech, and we'll hear that interview right after

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Speaker 1: we take this quick break to thank our sponsor. Let's

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Speaker 1: serve by you introducing yourself and your title and the company.

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Speaker 1: So my name is Oscar Warner. I'm president of Toby Tech,

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Speaker 1: and Toby Tech is basically one of three business units

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Speaker 1: in Toby U in Toby Group, so um Toby there

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Speaker 1: are three business units. Toby Dinox is providing solutions for

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Speaker 1: people with disabilities. Someone with a S who cannot move,

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Speaker 1: any who cannot move at all can basically communicate via

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Speaker 1: looking at a computer or send emails via just looking

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Speaker 1: at the computer, or somebody with CP who is pastic

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Speaker 1: can type emails and write on a thesis or or

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Speaker 1: or or write on a computer and use a computer

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Speaker 1: just with the rice. And then it's Toby Toby Pro

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Speaker 1: which is focusing on selling research people's solutions to to

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Speaker 1: universities and to companies like Proper and gaming the U

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Speaker 1: in the level to understand human behavior. And then it's

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Speaker 1: Toby Tech who is the developer of all the core

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Speaker 1: eye tracking technology and is selling this to the consumer markets,

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Speaker 1: which may be PIEC, gaming, the PC industry, smartphone industry,

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Speaker 1: v R, a R industry, so selling to the big

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Speaker 1: big o emsum of which you know pretty much all

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Speaker 1: the names. Right, So let's start just by kind of

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Speaker 1: explaining what I track tracking technology does in general, so

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Speaker 1: without getting into the mechanics of it, what exactly is

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Speaker 1: its purpose as far as as a technology goes. So,

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Speaker 1: eye tracking does two things, um um. It basically makes

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Speaker 1: technology understand you as a human being, and it does

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Speaker 1: that in two different ways. You know. The first one

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Speaker 1: is what we in already call insight. It makes devices

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Speaker 1: know what you're paying attention to, and when you think

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Speaker 1: about it, what you're paying attention to is your interest

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Speaker 1: or your intent at that given point in time. So

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Speaker 1: a computer with eye tracking know what your intention is

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Speaker 1: and when you think about it is if you think

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Speaker 1: on your in front of computer, you're looking at an

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Speaker 1: icon that you want to click on. The first thing

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Speaker 1: you do is you look at it. The second thing

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Speaker 1: you do is you take your mouse and drag the

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Speaker 1: mouse and throw over it. And the third thing you

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Speaker 1: do is you click on your mouth or in your

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Speaker 1: touchpad or in your control or whatever. But a computer

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Speaker 1: with an eye tracker already know that you're looking at something,

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Speaker 1: so that it knows what you want to click on

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Speaker 1: before you touch your mouth. So that could come in

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Speaker 1: really handy for anyone who's designing something to have a

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Speaker 1: process where you run the test and you have eye

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Speaker 1: tracking technology, you can see what elements of your design

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Speaker 1: are actually working or maybe are distracting to your to

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Speaker 1: your potential user. Yes, that is exactly what to be

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Speaker 1: pro that their entire business models is centered around that.

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Speaker 1: For example, you know they're creating glasses eye tracking, a

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Speaker 1: set of glasses and they send a test group through

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Speaker 1: a store, a retail store, and then big retail companies

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Speaker 1: such as Propering annulal unit level that would test the

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Speaker 1: store layout and see what package did I look at?

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Speaker 1: What package did I not see? And how do I

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Speaker 1: reconfigure the store layout. It can also be done on

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Speaker 1: websites or pack research, etcetera. But US excellent and it

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Speaker 1: can also be used not just to see where our

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Speaker 1: attention is, but it can go a step further and

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Speaker 1: become a direct interface with some other technology. For example,

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Speaker 1: you can use it so that you are creating an action,

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Speaker 1: you're removing that need to move and click correct. Yes.

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Speaker 1: So the first thing, the first category is just it

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Speaker 1: gives computers or it gives devices insight of what you're

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Speaker 1: looking at. If you're in front of the computer, are

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Speaker 1: you're focusing on the screen, or you're leaving the screen,

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Speaker 1: what you saw, what you did not see. It can

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Speaker 1: be presence and identity in all these things. It gives

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Speaker 1: you that it gives you another knowledge about the human.

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Speaker 1: And the second thing is you can use it for

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Speaker 1: interaction like taking an example from VR. For example, if

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Speaker 1: you imagine you pick up something in something in your

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Speaker 1: hand and you want to throw it, and if you

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Speaker 1: do this, you throw it aim at the a's in

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Speaker 1: your room. You want to throw it. When you as

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Speaker 1: a human aim at that place, you are looking at

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Speaker 1: the place with your eyes and then you give the

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Speaker 1: command to your body to throw the thing with your hand.

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Speaker 1: But the VR headset in order to tell where you

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Speaker 1: want to throw the object, you either need to point

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Speaker 1: at the area you want to throw it it with

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Speaker 1: your forehead or you need to point at the area

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Speaker 1: you want to throw at it with your hand or

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Speaker 1: do a gesture, and that's very very hard to get

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Speaker 1: exact basically, So this is kind of replicating the human

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Speaker 1: behavior when you pick up pick up something and you

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Speaker 1: want to throw at something, you look at the point

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Speaker 1: you want to throw at and that's how you do

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Speaker 1: your aim. And headsets with eye tracking would suddenly understand

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Speaker 1: your intention. They would understand what you are trying to

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Speaker 1: hit because you're looking at that point. So those devices

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Speaker 1: are much smarter, and we give developers the freedom to

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Speaker 1: use that and it removes that barrier from a user

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Speaker 1: perspect active that any time you have any kind of

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Speaker 1: interface with a machine, the more levels of of abstraction

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Speaker 1: that there are between you and what you're trying to do,

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Speaker 1: the more there's a learning curve, right that you have

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Speaker 1: to actually train yourself how to use that device, so

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Speaker 1: that the device does what you wanted to do, whereas

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Speaker 1: this is kind of stripping that away quite a bit.

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Speaker 1: We're trying to make it. We're trying to make it natural.

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Speaker 1: That is exactly how you behave in the real world.

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Speaker 1: You want to throw an object at something, you pick

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Speaker 1: it up, you look, that's how you aim and then

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Speaker 1: you throw, while in VR you would have to do

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Speaker 1: something else. So so we're trying to make it as natural. Yeah,

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Speaker 1: So what we think when you think about what devices

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Speaker 1: are as of today, devices have and I'm talking about

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Speaker 1: devices a community or a or smartphones or computers. But

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Speaker 1: they they they know if you push the buttons or

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Speaker 1: push them right. They listened to you because they have

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Speaker 1: cortona or they have different types of voice input and microphones.

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Speaker 1: They know where you are because they may have a GPS.

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Speaker 1: They know if you turn them around because they have

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Speaker 1: a gyro, etcetera. They know all these things, but they

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Speaker 1: have no concept, no idea of of the human in

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Speaker 1: front of them. They don't know if there's there's anyone

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Speaker 1: in front of them. So we typically say that devices

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Speaker 1: as of today are blind. They can listen, they can feel,

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Speaker 1: they know where they are, they know in what direction

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Speaker 1: they are, but they are blind. They have no concept

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Speaker 1: of who is in front of them, and what is

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Speaker 1: that person doing, and and where is that person looking

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Speaker 1: what is that person's intention? We think that's in the

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Speaker 1: in the world of AI, you know, trying to create

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Speaker 1: machines that understands use humans. We think that's kind of

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Speaker 1: actually crazy. Um, it is I would I would probably

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Speaker 1: argue pretty strongly for that. It is it really or

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Speaker 1: more important to know what is your what is my

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Speaker 1: user's intention? What are they interested in at every given

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Speaker 1: point in time, and knowing if they are in front

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Speaker 1: of the computer, as knowing where they are or in

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Speaker 1: what direction the laptop or smartphone is turned interesting. So

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Speaker 1: with this, this philosophy, this and this general approach, this

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Speaker 1: idea of teaching machines how we humans pay attention, you know,

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Speaker 1: looking for the signs that show that we are in

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Speaker 1: fact focusing upon any given aspect. What is the actual

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Speaker 1: technological component that allows these machines to do that. I

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Speaker 1: imagine that we're talking about a hardware side with a

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Speaker 1: camera and then obviously a software side that's processing that

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Speaker 1: information and making meaning out of it. Yeah, I mean

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Speaker 1: the core components of a of an eye tracking system.

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Speaker 1: It's it's a it's a camera in near infrared camera

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Speaker 1: and it's a set of illuminators that can that protected

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Speaker 1: light pattern or your eyes, and then this camera takes

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Speaker 1: the pictures with this light pattern. Then you send these

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Speaker 1: pictures the picture stream onto sometimes formal processing units where

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Speaker 1: there is a set of algorithms that can calculate um

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Speaker 1: either where you're looking, or you can do face idea

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Speaker 1: on the same camera, so who you are, or it

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Speaker 1: can calculate what direction your head is. It can detect

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Speaker 1: your facial pictures. Are you happy, are you sad? It

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Speaker 1: can take the drowsiness, are you awake or sleeping, So

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Speaker 1: you can do a lot of different things with those pictures.

434
00:26:36,800 --> 00:26:39,760
Speaker 1: And then the third component, it's kind of the camera,

435
00:26:40,160 --> 00:26:42,720
Speaker 1: the algorithms, and then it's the use case. So what

436
00:26:42,840 --> 00:26:45,960
Speaker 1: do you do with the knowledge of that you're looking here?

437
00:26:46,119 --> 00:26:48,760
Speaker 1: That's kind of built into the use case, and what

438
00:26:48,840 --> 00:26:50,560
Speaker 1: do you do with the knowledge that you know the

439
00:26:50,640 --> 00:26:54,399
Speaker 1: identity of this person? So it might be something in

440
00:26:54,480 --> 00:26:58,000
Speaker 1: the case of authentication where you're looking at a person's idea,

441
00:26:58,040 --> 00:27:00,920
Speaker 1: their their facial structure. Similar to what we saw with

442
00:27:01,280 --> 00:27:05,239
Speaker 1: the the reveal of the new iPhone handsets that are

443
00:27:05,280 --> 00:27:08,480
Speaker 1: coming out, they're using a face i D technology for

444
00:27:08,640 --> 00:27:11,640
Speaker 1: that sort of thing authentication, but it could it could

445
00:27:11,640 --> 00:27:14,280
Speaker 1: also be control systems, whether it's in a game or

446
00:27:14,359 --> 00:27:19,080
Speaker 1: as you had mentioned earlier, for people who have mobility

447
00:27:19,200 --> 00:27:21,840
Speaker 1: disabilities that they aren't able to move, they're able to

448
00:27:22,160 --> 00:27:25,200
Speaker 1: perhaps use their eyes to focus on specific icons and

449
00:27:25,320 --> 00:27:29,360
Speaker 1: thus communicate using eye tracking software to indicate what they're

450
00:27:29,400 --> 00:27:33,840
Speaker 1: intent is. Yeah, so you see big trend in consumer

451
00:27:33,880 --> 00:27:37,159
Speaker 1: actronics right now. If I mean the iPhone is is

452
00:27:37,440 --> 00:27:41,720
Speaker 1: just one of them. They're entering because they want to

453
00:27:41,920 --> 00:27:46,760
Speaker 1: make their devices smarter and understand the users better. They

454
00:27:47,040 --> 00:27:51,800
Speaker 1: enter special use of facing cameras, nearing for red cameras

455
00:27:51,960 --> 00:27:56,000
Speaker 1: which can understand their users more. And that is exactly

456
00:27:56,080 --> 00:27:58,840
Speaker 1: what iPhone did, I mean iPhones quote in one of

457
00:27:58,920 --> 00:28:02,000
Speaker 1: the newspapers or articles I read was what can be

458
00:28:02,119 --> 00:28:06,440
Speaker 1: more natural than touch? Well just a look. So iPhone

459
00:28:06,520 --> 00:28:09,720
Speaker 1: Is or Apple is recognizing that, hey, yeah, we're using

460
00:28:09,760 --> 00:28:12,320
Speaker 1: the touch interface today. But if I really won't understand

461
00:28:12,359 --> 00:28:15,000
Speaker 1: my user, I need to understand what the user is,

462
00:28:15,560 --> 00:28:18,360
Speaker 1: what the user is doing in front of advice. That's

463
00:28:18,400 --> 00:28:22,959
Speaker 1: why they implemented face i D sure in the phone um,

464
00:28:23,440 --> 00:28:26,120
Speaker 1: And that's why I mean Huawei. We did the phone

465
00:28:26,160 --> 00:28:28,440
Speaker 1: with Huawei Run about a year ago which had a

466
00:28:28,520 --> 00:28:31,520
Speaker 1: similar type of similar type of camera which could do

467
00:28:32,000 --> 00:28:34,399
Speaker 1: various features as well and understand you as a user.

468
00:28:34,720 --> 00:28:37,960
Speaker 1: Are you in front of it? Then the screen didn't live, etcetera, etcetera.

469
00:28:38,760 --> 00:28:40,960
Speaker 1: It's the same thing that is happening with eye tracking.

470
00:28:41,720 --> 00:28:43,440
Speaker 1: It is the same thing which is happening in the

471
00:28:43,440 --> 00:28:45,920
Speaker 1: automotive industry where you have used of facing cameras to

472
00:28:46,200 --> 00:28:49,680
Speaker 1: detected drowsiness. Except it's the same thing that is happening

473
00:28:49,720 --> 00:28:51,440
Speaker 1: in in v R where a lot of people are

474
00:28:51,440 --> 00:28:54,840
Speaker 1: are looking into eye tracking cameras or user facing cameras

475
00:28:54,880 --> 00:28:56,959
Speaker 1: in in in, in the in the in the headset.

476
00:28:57,000 --> 00:29:00,480
Speaker 1: So it's a it's a general trend basically. And I

477
00:29:00,560 --> 00:29:04,120
Speaker 1: had a chance to experience this and many years ago.

478
00:29:04,400 --> 00:29:06,200
Speaker 1: In fact, I think it was a booth at c

479
00:29:06,400 --> 00:29:08,760
Speaker 1: E S and I think it was a Toby booth

480
00:29:08,800 --> 00:29:12,160
Speaker 1: if I'm not mistaken, where I sat down and got

481
00:29:12,240 --> 00:29:16,240
Speaker 1: a general demo of the eye tracking technology. At the time,

482
00:29:16,360 --> 00:29:19,200
Speaker 1: there was an application. It was a game essentially sort

483
00:29:19,200 --> 00:29:22,280
Speaker 1: of like the old game of Asteroids, where you would

484
00:29:22,320 --> 00:29:26,400
Speaker 1: focus on items on the screen, and wherever your focus was,

485
00:29:26,520 --> 00:29:32,400
Speaker 1: that's where the quote unquote firing of the the asteroid

486
00:29:32,520 --> 00:29:35,920
Speaker 1: destroying laser or whatever it was would focus. And it

487
00:29:36,080 --> 00:29:38,800
Speaker 1: was a great little demo showing the promise of it.

488
00:29:38,960 --> 00:29:43,880
Speaker 1: I imagine that as all technologies do, this has evolved

489
00:29:43,920 --> 00:29:48,200
Speaker 1: to become much more accurate and precise over time. Yes,

490
00:29:48,720 --> 00:29:53,360
Speaker 1: so that's obviously and one of our core challenges and

491
00:29:53,440 --> 00:29:57,239
Speaker 1: tusks is to improve the accuracy and precision. But it's

492
00:29:57,280 --> 00:30:01,440
Speaker 1: also to make it work consistent live for the entire

493
00:30:01,520 --> 00:30:04,760
Speaker 1: population in all different conditions. That is what it is hard.

494
00:30:04,840 --> 00:30:06,800
Speaker 1: With an eye track there, making an eye track of

495
00:30:06,840 --> 00:30:08,520
Speaker 1: the work for one person is prettycy, but making it

496
00:30:08,680 --> 00:30:11,520
Speaker 1: one an eye tracker the works the same way for

497
00:30:11,720 --> 00:30:16,800
Speaker 1: everyone is pretty hard. You can compare that with voice recognition.

498
00:30:16,920 --> 00:30:20,720
Speaker 1: I mean, making a voice recognition system that that recognizes

499
00:30:20,760 --> 00:30:24,400
Speaker 1: your voice is pretty okay, pretty easy, But making to

500
00:30:24,520 --> 00:30:27,239
Speaker 1: do with it for the entire human race in all

501
00:30:27,240 --> 00:30:30,920
Speaker 1: different conditions, with all different background sounds, that's pretty hard. Um.

502
00:30:31,680 --> 00:30:34,880
Speaker 1: So that's that's the challenge, and that's that's what we

503
00:30:35,040 --> 00:30:39,440
Speaker 1: are ultimately they're leading the world on. So you're you're

504
00:30:39,560 --> 00:30:43,479
Speaker 1: looking at the separating all the signal from the noise

505
00:30:44,120 --> 00:30:47,840
Speaker 1: making sure that on any I mean, I sit there

506
00:30:47,840 --> 00:30:49,640
Speaker 1: and I just think about all the different cases where

507
00:30:49,680 --> 00:30:52,160
Speaker 1: I'm using my computer. I mean, even if it were

508
00:30:52,240 --> 00:30:57,360
Speaker 1: just a laptop implementation, keeping all the others aside just

509
00:30:57,640 --> 00:31:00,520
Speaker 1: the laptop alone. There are times where I'm at my desk,

510
00:31:00,640 --> 00:31:02,920
Speaker 1: there are times where I'm sitting at a couch or

511
00:31:03,120 --> 00:31:07,480
Speaker 1: in another environment. They're different lighting conditions, they're different angles. Um.

512
00:31:07,640 --> 00:31:10,480
Speaker 1: I imagine that that for most of these there's probably

513
00:31:10,640 --> 00:31:16,240
Speaker 1: some sort of UH training or orientation UH segment where

514
00:31:16,320 --> 00:31:19,440
Speaker 1: it allows you to to at least set that baseline

515
00:31:19,680 --> 00:31:22,440
Speaker 1: for eye tracking, for to make sure that you know

516
00:31:22,520 --> 00:31:26,000
Speaker 1: you're getting a good response early on. But yes, as

517
00:31:26,040 --> 00:31:29,280
Speaker 1: you point out, if you're rolling out of technology that's

518
00:31:29,280 --> 00:31:33,240
Speaker 1: going to go to a wide consumer market, then that

519
00:31:33,440 --> 00:31:37,520
Speaker 1: challenges is non trivial. You have something that needs to

520
00:31:37,640 --> 00:31:42,400
Speaker 1: work out of the box for UH an enormous really

521
00:31:42,440 --> 00:31:45,800
Speaker 1: an endless variety of people in and an almost equally

522
00:31:46,000 --> 00:31:51,680
Speaker 1: endless variety of situations. So um, these days you've mentioned

523
00:31:51,760 --> 00:31:53,920
Speaker 1: some of the tools. One of the things I was

524
00:31:54,000 --> 00:31:58,560
Speaker 1: really interested in was this user interface with computers specifically.

525
00:31:58,640 --> 00:32:01,400
Speaker 1: But I mean, obviously all the differ friend. Uses of

526
00:32:01,560 --> 00:32:05,160
Speaker 1: eye tracking are are fascinating to me. Um. One of

527
00:32:05,200 --> 00:32:08,600
Speaker 1: the things I was really kind of interested in is

528
00:32:08,800 --> 00:32:13,960
Speaker 1: the implementation in the sense of how it works for

529
00:32:14,560 --> 00:32:18,880
Speaker 1: uh in the pro gaming industry. We've been looking at

530
00:32:19,000 --> 00:32:23,160
Speaker 1: that recently, and UM, I think it's really cool to

531
00:32:23,280 --> 00:32:27,800
Speaker 1: have a new tool to analyze the way people who

532
00:32:27,880 --> 00:32:31,080
Speaker 1: can play at a professional level. How you know where

533
00:32:31,120 --> 00:32:33,760
Speaker 1: their attention is and is it different from people who

534
00:32:33,880 --> 00:32:38,560
Speaker 1: play at a regular gaming level, like someone like me.

535
00:32:39,680 --> 00:32:43,760
Speaker 1: I consider myself a bullet sponge when it comes to games.

536
00:32:43,840 --> 00:32:48,280
Speaker 1: I'm I'm the one that people practice on. Yeah, no,

537
00:32:48,400 --> 00:32:50,600
Speaker 1: I'm great at doing that. I'm I'm if you have

538
00:32:51,000 --> 00:32:53,720
Speaker 1: if you have a healer on your team who needs practice,

539
00:32:54,440 --> 00:32:56,960
Speaker 1: I'm the guy who's gonna be giving that guy lots

540
00:32:57,000 --> 00:33:01,600
Speaker 1: of work. But uh, I'm sarious. How have you seen

541
00:33:01,680 --> 00:33:04,280
Speaker 1: this rolled out and implemented? Have Have there been any

542
00:33:05,400 --> 00:33:08,800
Speaker 1: things in that implementation that have surprised you or any

543
00:33:08,920 --> 00:33:14,360
Speaker 1: interesting stories through that process? I mean this, this entire

544
00:33:14,440 --> 00:33:16,560
Speaker 1: story is based on what we do in in in

545
00:33:17,320 --> 00:33:20,000
Speaker 1: what we have done many many years in various business units,

546
00:33:20,080 --> 00:33:22,840
Speaker 1: and it's based on the notion that what you look

547
00:33:22,920 --> 00:33:25,640
Speaker 1: at is a good approximation of what you think because

548
00:33:25,680 --> 00:33:31,160
Speaker 1: that is your intention. So the entire concept is pretty

549
00:33:31,200 --> 00:33:33,520
Speaker 1: straightforward in that. And when you when you think about that,

550
00:33:33,720 --> 00:33:38,720
Speaker 1: you can if I mean a pro gamer, where that

551
00:33:38,960 --> 00:33:44,240
Speaker 1: person spends his or her attention is extremely precious. I mean,

552
00:33:44,480 --> 00:33:47,479
Speaker 1: they have so many different impressions coming at them at

553
00:33:47,520 --> 00:33:49,400
Speaker 1: the same time, and they need to select and need

554
00:33:49,440 --> 00:33:53,840
Speaker 1: to be very good at making sure they perceived the

555
00:33:54,000 --> 00:33:56,520
Speaker 1: right things, making sure they spend their time on the

556
00:33:56,600 --> 00:33:59,840
Speaker 1: right things, otherwise they they will get killed. Um so,

557
00:34:01,040 --> 00:34:03,560
Speaker 1: and the concept is pretty much going to link to that. So,

558
00:34:03,720 --> 00:34:07,719
Speaker 1: for example, a pro gamer may know that they need

559
00:34:07,800 --> 00:34:11,040
Speaker 1: to regularly check check the minima. You know, how many

560
00:34:11,080 --> 00:34:13,239
Speaker 1: how many times a minute does a pro game or

561
00:34:13,320 --> 00:34:15,640
Speaker 1: check the minimap. You're going to see them continuously going

562
00:34:15,680 --> 00:34:19,080
Speaker 1: down there and checking what's happening, while a less you know,

563
00:34:19,400 --> 00:34:21,640
Speaker 1: a less good gamer may focus too much on the game.

564
00:34:22,400 --> 00:34:26,200
Speaker 1: You can you can you can check that out and

565
00:34:26,320 --> 00:34:29,360
Speaker 1: see how many times are you're actually checking minima or

566
00:34:29,480 --> 00:34:32,400
Speaker 1: you can see pro gamers are also before he's attacking,

567
00:34:32,760 --> 00:34:35,120
Speaker 1: checking the enemy items. You know, you know, what type

568
00:34:35,160 --> 00:34:36,959
Speaker 1: of skills or what type of weapons or what type

569
00:34:36,960 --> 00:34:40,160
Speaker 1: of skills does does the opponent have right now, you

570
00:34:40,239 --> 00:34:42,719
Speaker 1: can see that a less less good game it may

571
00:34:42,800 --> 00:34:46,520
Speaker 1: not do that. Yeah, you can also go into different

572
00:34:46,560 --> 00:34:49,360
Speaker 1: players player styles. You know, when you are a certain

573
00:34:49,400 --> 00:34:51,920
Speaker 1: player style, you may have a different games pattern than

574
00:34:52,040 --> 00:34:56,120
Speaker 1: you are another player style because you need you need

575
00:34:56,280 --> 00:34:59,080
Speaker 1: to do that differently. Or you can see things like

576
00:35:00,200 --> 00:35:02,480
Speaker 1: keyboard combination. I mean, you know, as as a really

577
00:35:02,520 --> 00:35:04,359
Speaker 1: good game and you know you need to learn all

578
00:35:04,440 --> 00:35:08,319
Speaker 1: your keyboard combinations by heart. You need to do that, um,

579
00:35:09,040 --> 00:35:12,520
Speaker 1: and that's gonna be and by doing that, you can

580
00:35:12,560 --> 00:35:15,520
Speaker 1: spend all your time focusing on the focusing on the screen. Well,

581
00:35:15,600 --> 00:35:17,759
Speaker 1: less good gamers they will not be they will not

582
00:35:17,920 --> 00:35:20,200
Speaker 1: know all the keyboard combinations. They will be focusing off

583
00:35:20,280 --> 00:35:22,839
Speaker 1: screen for a certain percentage of the time. You can

584
00:35:22,920 --> 00:35:25,880
Speaker 1: notice that. So you can kind of say, hey, you

585
00:35:25,960 --> 00:35:28,120
Speaker 1: need to practice your keyboard combinations because your off screen

586
00:35:28,239 --> 00:35:30,040
Speaker 1: thirty example of time or trying to perstand the temperation

587
00:35:30,040 --> 00:35:32,839
Speaker 1: on whatever it is you know. Um, so it's it's

588
00:35:33,280 --> 00:35:38,120
Speaker 1: it's things like that that you can notice that can

589
00:35:38,239 --> 00:35:41,239
Speaker 1: make you become a better gamer. If you study this

590
00:35:41,400 --> 00:35:44,239
Speaker 1: is my favorite gamer, this is how they behave I

591
00:35:44,440 --> 00:35:48,040
Speaker 1: see how they are playing and what they're intent is,

592
00:35:48,800 --> 00:35:51,520
Speaker 1: then you can learn from that. You may not have

593
00:35:51,600 --> 00:35:53,040
Speaker 1: the same players toty hole, but you can learn from

594
00:35:53,120 --> 00:35:55,920
Speaker 1: that and practice on certain certain events. Yeah, it might

595
00:35:56,000 --> 00:35:58,719
Speaker 1: even just teach you what parts of the game you

596
00:35:58,800 --> 00:36:03,279
Speaker 1: don't need to worry about because those are purely environmental

597
00:36:03,440 --> 00:36:07,400
Speaker 1: and have no no direct impact on whether or not

598
00:36:07,680 --> 00:36:11,640
Speaker 1: there's an opponent, and therefore you don't waste time looking

599
00:36:11,719 --> 00:36:16,320
Speaker 1: at something that is not a threat exactly. And you

600
00:36:16,400 --> 00:36:18,799
Speaker 1: can see that just in the in the game where

601
00:36:18,880 --> 00:36:20,960
Speaker 1: somebody is playing without tracking, they can turn on what

602
00:36:21,080 --> 00:36:24,000
Speaker 1: we call a gaze overlay, and then where they're looking

603
00:36:24,080 --> 00:36:28,200
Speaker 1: you will get the kind of transparent blob. If the

604
00:36:28,280 --> 00:36:30,839
Speaker 1: streamer wants you to see that, so they can turn

605
00:36:30,920 --> 00:36:34,000
Speaker 1: it on, and then you, as as a viewer, get

606
00:36:34,080 --> 00:36:37,480
Speaker 1: the much richer experience because you can suddenly understand that,

607
00:36:37,600 --> 00:36:41,120
Speaker 1: all right, I know not only where the party, where

608
00:36:41,320 --> 00:36:43,080
Speaker 1: the where the pro is clicking, but I also know

609
00:36:43,160 --> 00:36:45,719
Speaker 1: where he's spending his attention, so I kind of can

610
00:36:45,800 --> 00:36:49,120
Speaker 1: anticipate his next move because I can see a little

611
00:36:49,160 --> 00:36:53,200
Speaker 1: bit how he thinks interested that, and that will make

612
00:36:53,320 --> 00:36:57,400
Speaker 1: you anticipate his next move and make you understand his

613
00:36:57,560 --> 00:37:01,000
Speaker 1: gameplay better and therefore you can always game and therefore

614
00:37:01,080 --> 00:37:04,680
Speaker 1: learn more. So just by looking how they scan off

615
00:37:04,719 --> 00:37:07,320
Speaker 1: the environment, you can kind of follow how the pro is,

616
00:37:07,400 --> 00:37:10,000
Speaker 1: how the pro is perceiving and playing the game, which

617
00:37:10,080 --> 00:37:12,719
Speaker 1: is incredibly useful for us as a as a as

618
00:37:12,800 --> 00:37:15,759
Speaker 1: a as a game that want improved. Yeah, this kind

619
00:37:15,800 --> 00:37:19,440
Speaker 1: of as a parallel. This reminds me a lot actually

620
00:37:19,920 --> 00:37:22,880
Speaker 1: of poker tournaments that are televised, where you get a

621
00:37:23,000 --> 00:37:26,360
Speaker 1: chance to see what the cards are of any particular player,

622
00:37:26,880 --> 00:37:30,640
Speaker 1: which then lets you understand more about the decisions the

623
00:37:30,760 --> 00:37:34,000
Speaker 1: players are making as the game unfolds. This is kind

624
00:37:34,040 --> 00:37:36,719
Speaker 1: of the equivalent to that you're not just watching the

625
00:37:36,840 --> 00:37:40,719
Speaker 1: game happen. You're actually seeing how the person playing it is.

626
00:37:41,239 --> 00:37:43,279
Speaker 1: You know what what they are perceiving and what is

627
00:37:43,680 --> 00:37:46,800
Speaker 1: important to them, and that's why they make the decisions

628
00:37:46,840 --> 00:37:49,000
Speaker 1: they make. So now you're not just seeing their decisions,

629
00:37:49,080 --> 00:37:52,440
Speaker 1: but you see why those decisions are happening exactly. I mean,

630
00:37:52,480 --> 00:37:54,640
Speaker 1: you you can take it to the to the you know,

631
00:37:55,040 --> 00:37:57,680
Speaker 1: real world poker world. If you're sitting around the you know,

632
00:37:57,719 --> 00:38:01,879
Speaker 1: really fiscal table, then you really good poker players well

633
00:38:02,040 --> 00:38:03,840
Speaker 1: will of course be looking at their cards, but they

634
00:38:03,880 --> 00:38:06,399
Speaker 1: would probably spend a very large portion of the time

635
00:38:06,520 --> 00:38:09,640
Speaker 1: watching their opponents. If you had eye tracking on them,

636
00:38:09,680 --> 00:38:13,640
Speaker 1: you could actually see what are they focusing on, what

637
00:38:13,960 --> 00:38:16,719
Speaker 1: parts of the player are they focusing on, and when

638
00:38:17,400 --> 00:38:20,359
Speaker 1: you know and how do they know? So you can

639
00:38:20,440 --> 00:38:22,440
Speaker 1: see what is it that they're focusing on, and what

640
00:38:22,520 --> 00:38:25,200
Speaker 1: are the interesting areas. As a non pro gamer, you

641
00:38:25,200 --> 00:38:28,359
Speaker 1: would probably learn immensely by knowing, all right, I should

642
00:38:28,400 --> 00:38:30,880
Speaker 1: not focus so much on my own cards, I should

643
00:38:30,880 --> 00:38:33,920
Speaker 1: focus on new opponents x percent at the time. And

644
00:38:34,040 --> 00:38:36,400
Speaker 1: then this is what the pros are actually looking at.

645
00:38:36,880 --> 00:38:40,920
Speaker 1: He look, he's lick, he's looking at if player he

646
00:38:41,160 --> 00:38:43,439
Speaker 1: is looking at player B and seeing if plays these

647
00:38:43,520 --> 00:38:48,279
Speaker 1: blinking and if he's blinking, he's kind of folding or doubling. Yeah,

648
00:38:48,520 --> 00:38:52,319
Speaker 1: so because because because that is the queue. Yeah, that's

649
00:38:52,440 --> 00:38:56,520
Speaker 1: and it's you know, that's incredible. It's it's blowing my

650
00:38:56,640 --> 00:38:59,000
Speaker 1: mind to even think about that possibility. Because we know

651
00:38:59,360 --> 00:39:03,560
Speaker 1: that people who or form at that at that professional level,

652
00:39:03,600 --> 00:39:07,480
Speaker 1: at that level that is above like sometimes a huge

653
00:39:07,640 --> 00:39:11,040
Speaker 1: leap above what we would consider a good player. There

654
00:39:11,080 --> 00:39:13,760
Speaker 1: are these these components and people always talk about tells

655
00:39:13,920 --> 00:39:16,160
Speaker 1: and they talk about the psychology of the game. But

656
00:39:16,280 --> 00:39:18,680
Speaker 1: that's stuff that is really difficult to learn unless you

657
00:39:18,760 --> 00:39:22,320
Speaker 1: are pouring hundreds of hours of experience in to be

658
00:39:22,440 --> 00:39:26,480
Speaker 1: able to see something like this, where you can get

659
00:39:26,560 --> 00:39:32,360
Speaker 1: that direct feedback of oh, well, I understand conceptually what

660
00:39:32,480 --> 00:39:35,000
Speaker 1: they're doing. Now I can actually see how they are

661
00:39:35,120 --> 00:39:37,839
Speaker 1: doing it. Even though I would argue it would still

662
00:39:37,880 --> 00:39:40,680
Speaker 1: take you many hours to to get a level of

663
00:39:40,719 --> 00:39:45,560
Speaker 1: proficiency there, you would at least have a place to start. Yeah, exactly.

664
00:39:47,480 --> 00:39:48,880
Speaker 1: But you can take this also too, I mean, can

665
00:39:48,920 --> 00:39:51,719
Speaker 1: take this to the real sports world. We have race

666
00:39:51,920 --> 00:39:55,719
Speaker 1: Formula one race car drivers were NASCAR drivers who are

667
00:39:55,800 --> 00:39:59,200
Speaker 1: using eye tracking in their helmets in order to see

668
00:39:59,760 --> 00:40:02,440
Speaker 1: rick chord where they are in practice now, where they

669
00:40:02,520 --> 00:40:04,799
Speaker 1: are looking and when they take the turns, because one

670
00:40:04,840 --> 00:40:06,520
Speaker 1: of the most important things going to take a turn

671
00:40:06,640 --> 00:40:09,719
Speaker 1: is to have the right kind of direction of your right,

672
00:40:09,840 --> 00:40:12,440
Speaker 1: right kind of focus points. And they're kind of learning

673
00:40:12,960 --> 00:40:15,680
Speaker 1: from the really good drivers to the less good drivers.

674
00:40:16,000 --> 00:40:19,360
Speaker 1: Where is the focused point in the term. So because

675
00:40:19,440 --> 00:40:21,560
Speaker 1: they can see right the good drivers are behaving like this,

676
00:40:21,920 --> 00:40:24,879
Speaker 1: this is their focused point. You know you should change.

677
00:40:24,920 --> 00:40:27,279
Speaker 1: You're focusing on their own directions. So it's kind of

678
00:40:27,680 --> 00:40:31,279
Speaker 1: it's it's in the physical world as well. Two. I

679
00:40:31,320 --> 00:40:33,279
Speaker 1: mean you can see the poker examples very easy, and

680
00:40:33,360 --> 00:40:35,759
Speaker 1: then you can obviously see the the the the the

681
00:40:36,320 --> 00:40:39,279
Speaker 1: the the computer game example as well. So this is

682
00:40:39,320 --> 00:40:41,960
Speaker 1: a two way street, right, We're talking about in one

683
00:40:42,320 --> 00:40:47,480
Speaker 1: side of things having a new approach, relatively new, I mean,

684
00:40:47,640 --> 00:40:49,400
Speaker 1: eye tracking has been around for a while, but to

685
00:40:49,480 --> 00:40:52,600
Speaker 1: see the technology mature to a point where it's rolling

686
00:40:52,640 --> 00:40:59,160
Speaker 1: out more more consistently. In consumer market stuff, we see

687
00:40:59,560 --> 00:41:03,279
Speaker 1: a new user interface approach. But on the other side,

688
00:41:03,360 --> 00:41:06,719
Speaker 1: we're seeing a way of learning more about ourselves. And

689
00:41:06,920 --> 00:41:10,440
Speaker 1: so it's really cool. It's technology that you can take

690
00:41:10,480 --> 00:41:13,080
Speaker 1: advantage of as a developer to create a new way

691
00:41:13,160 --> 00:41:16,920
Speaker 1: to interact with a product or whether it's hardware or software.

692
00:41:17,239 --> 00:41:21,520
Speaker 1: And then on the flip side, from a psychology standpoint,

693
00:41:21,640 --> 00:41:24,440
Speaker 1: you can learn more about human behavior. You can learn

694
00:41:24,440 --> 00:41:27,560
Speaker 1: more about human behavior and extremes such as the extreme

695
00:41:27,680 --> 00:41:31,440
Speaker 1: level of performance with professional gamers and that kind of thing. Um. So,

696
00:41:31,600 --> 00:41:34,840
Speaker 1: to me, this is an amazing technology, not just for

697
00:41:34,920 --> 00:41:36,880
Speaker 1: the potential of what I can do with it, but

698
00:41:37,080 --> 00:41:41,480
Speaker 1: what ultimately we can learn about ourselves and thus design

699
00:41:41,680 --> 00:41:46,919
Speaker 1: even better stuff another generation or two generations down the line, Yeah,

700
00:41:46,920 --> 00:41:49,439
Speaker 1: I'm out in just a computer developer, if they could see,

701
00:41:49,840 --> 00:41:52,400
Speaker 1: if they take a sample of a thousand gamers and

702
00:41:52,560 --> 00:41:56,240
Speaker 1: users of the game, and they would know on what objects,

703
00:41:56,760 --> 00:41:59,840
Speaker 1: what what are these guys are in girls seeing in

704
00:42:00,000 --> 00:42:03,080
Speaker 1: the user interface? And what are they not seeing? Alright,

705
00:42:03,120 --> 00:42:05,239
Speaker 1: they're not noticing I mean, they're not clicking on this thing.

706
00:42:05,320 --> 00:42:07,799
Speaker 1: They see it, but they turn away because because they're

707
00:42:07,800 --> 00:42:10,759
Speaker 1: not interested in it, or they're just missing this thing.

708
00:42:11,320 --> 00:42:14,160
Speaker 1: You know, how what what cues can you give it

709
00:42:14,200 --> 00:42:16,440
Speaker 1: to you? So if you know what they have, what

710
00:42:16,560 --> 00:42:19,680
Speaker 1: they have seen, you don't need to have a second

711
00:42:19,719 --> 00:42:22,399
Speaker 1: reminder of some of something that somebody has seen, seen,

712
00:42:22,480 --> 00:42:26,640
Speaker 1: seen already. So you can improve the user interface immensely

713
00:42:26,760 --> 00:42:29,800
Speaker 1: obviously by the stuff of right. And of course today

714
00:42:30,200 --> 00:42:32,640
Speaker 1: now that we're in a world where people have persistent

715
00:42:32,719 --> 00:42:37,680
Speaker 1: Internet connections, it allows you to roll out uh tweaks.

716
00:42:37,760 --> 00:42:40,640
Speaker 1: You can roll out versions and patches on a very

717
00:42:40,719 --> 00:42:45,319
Speaker 1: frequent basis. This allows for incredible flexibility if you are

718
00:42:46,040 --> 00:42:49,840
Speaker 1: trying to create something that is software based and you

719
00:42:50,120 --> 00:42:53,040
Speaker 1: are getting real time feedback due to the eye tracking

720
00:42:53,160 --> 00:42:56,719
Speaker 1: data about what is and isn't working, or what is

721
00:42:56,920 --> 00:43:02,320
Speaker 1: or isn't necessarily considered were the a focus and either

722
00:43:03,080 --> 00:43:05,920
Speaker 1: redesign it so that something that you think is important

723
00:43:06,040 --> 00:43:09,439
Speaker 1: can have a better sense of prominence in the eyes

724
00:43:09,520 --> 00:43:12,040
Speaker 1: of the people using it, or you just eliminate it.

725
00:43:12,160 --> 00:43:16,280
Speaker 1: If no one's looking there and it's taking up landscape,

726
00:43:16,320 --> 00:43:18,480
Speaker 1: you might just get rid of that entirely, if no

727
00:43:18,560 --> 00:43:22,279
Speaker 1: one really is using it. It's to me, it's like

728
00:43:22,719 --> 00:43:29,000
Speaker 1: another leap forward where we saw advertising go once the

729
00:43:29,120 --> 00:43:32,640
Speaker 1: Internet became a real entity. Because of course, in the

730
00:43:32,719 --> 00:43:38,160
Speaker 1: old days, advertising was limited to print and radio and

731
00:43:38,239 --> 00:43:43,359
Speaker 1: television uh campaigns, and you had a sense of how

732
00:43:43,480 --> 00:43:46,600
Speaker 1: well your ad campaign was going based upon sales, but

733
00:43:46,680 --> 00:43:51,080
Speaker 1: it was really hard to nail down whether or not

734
00:43:51,280 --> 00:43:55,520
Speaker 1: that was actual causation, right, because maybe it was because

735
00:43:55,600 --> 00:43:59,600
Speaker 1: the ad campaign, or maybe there was some incredible sale

736
00:43:59,760 --> 00:44:03,680
Speaker 1: that really help boost sales. But then the Internet comes

737
00:44:03,719 --> 00:44:07,160
Speaker 1: along and that gives a much more direct feedback loop

738
00:44:07,400 --> 00:44:11,439
Speaker 1: of what ads are are encouraging people to click through

739
00:44:11,680 --> 00:44:14,600
Speaker 1: and therefore experience it on a deeper level. This is

740
00:44:14,719 --> 00:44:18,879
Speaker 1: like that, except it can apply to everything, not just advertising,

741
00:44:18,960 --> 00:44:23,960
Speaker 1: but everything. So that's that's what I mean when when

742
00:44:24,000 --> 00:44:28,279
Speaker 1: I say eye tracking gives understanding of your intent and

743
00:44:28,520 --> 00:44:33,520
Speaker 1: how important is attempt to any any any computing device.

744
00:44:33,800 --> 00:44:37,360
Speaker 1: Intent is is probably the most important courage in that

745
00:44:37,440 --> 00:44:41,680
Speaker 1: you have. You know, you're you're you're kind of intent

746
00:44:41,840 --> 00:44:44,320
Speaker 1: and you're interesting. Your attention, I mean that is the

747
00:44:44,440 --> 00:44:48,839
Speaker 1: most the attention of the of humans is the most

748
00:44:48,920 --> 00:44:52,400
Speaker 1: pressured pressure pressures, pressure resource you have. Right, but then

749
00:44:52,440 --> 00:44:55,040
Speaker 1: it jumps down that, right, you can never share eye

750
00:44:55,080 --> 00:44:57,239
Speaker 1: tracking data the user doesn't want it show. I mean,

751
00:44:57,400 --> 00:45:01,600
Speaker 1: it's it's the user that controls it, so so there's

752
00:45:01,640 --> 00:45:05,279
Speaker 1: no kind of possibilities to spy. It's like you as

753
00:45:05,320 --> 00:45:07,520
Speaker 1: a user, you control if you want to give this

754
00:45:07,600 --> 00:45:10,080
Speaker 1: to a corporation or if you don't basically like anything else.

755
00:45:10,560 --> 00:45:15,000
Speaker 1: That's super super important. Obviously, absolutely yes you wouldn't if

756
00:45:15,040 --> 00:45:17,880
Speaker 1: you're volunteering it, that's one thing. But if you just

757
00:45:18,080 --> 00:45:22,319
Speaker 1: found out, oh gosh, Facebook implemented this technology and now

758
00:45:22,880 --> 00:45:26,040
Speaker 1: they know everywhere I look, and now my feed is

759
00:45:26,080 --> 00:45:28,480
Speaker 1: being filled with puppies, and I like puppies, but I

760
00:45:28,560 --> 00:45:31,440
Speaker 1: really would like other things besides puppies. Uh. I mean,

761
00:45:31,520 --> 00:45:35,480
Speaker 1: obviously we see that sort of analysis in all areas

762
00:45:35,760 --> 00:45:38,839
Speaker 1: of technology that are going on, just based upon our

763
00:45:38,920 --> 00:45:42,440
Speaker 1: actual physical behaviors. Are choices made, like whether we're following

764
00:45:42,560 --> 00:45:45,480
Speaker 1: one link versus another link. But I think a lot

765
00:45:45,560 --> 00:45:48,800
Speaker 1: of people would really uh, if it weren't something that

766
00:45:48,880 --> 00:45:51,680
Speaker 1: they were volunteering, they would really have a negative reaction

767
00:45:51,760 --> 00:45:53,680
Speaker 1: to that, to think, oh, well, now it's gone beyond

768
00:45:53,800 --> 00:45:56,200
Speaker 1: what I'm choosing to do. Now it's going to what

769
00:45:56,400 --> 00:45:59,000
Speaker 1: I'm I'm actually looking at. And uh, I think a

770
00:45:59,080 --> 00:46:01,760
Speaker 1: lot of people would find that creepy if it weren't

771
00:46:01,800 --> 00:46:04,720
Speaker 1: a volunteer, voluntary thing. So I agree with you entirely

772
00:46:04,840 --> 00:46:08,160
Speaker 1: that that that's an important step for this to be

773
00:46:08,360 --> 00:46:13,839
Speaker 1: a technology that people embrace as opposed to reject. Yeah,

774
00:46:14,280 --> 00:46:16,600
Speaker 1: and that's going we put hard viruses with the guardians

775
00:46:16,600 --> 00:46:18,640
Speaker 1: of the end users privacy or when you can only

776
00:46:18,680 --> 00:46:21,600
Speaker 1: read it if you're if you're loving right. So what

777
00:46:21,960 --> 00:46:26,240
Speaker 1: I want to ask you what your personal favorite implementation

778
00:46:26,640 --> 00:46:30,080
Speaker 1: of eye tracking technology has been up to this point.

779
00:46:33,440 --> 00:46:36,520
Speaker 1: It's it's a very good question. It's also very hard

780
00:46:36,640 --> 00:46:40,160
Speaker 1: question because as we have discussed, his knowing the intent

781
00:46:40,560 --> 00:46:44,120
Speaker 1: of humans is so powerful, So you can you can

782
00:46:44,200 --> 00:46:51,800
Speaker 1: drew up so many different example and implementations. But if I,

783
00:46:51,800 --> 00:46:55,680
Speaker 1: if I, if I take a few, um we have

784
00:46:55,800 --> 00:46:58,480
Speaker 1: in our business unit Tobo Dona woks. We have so

785
00:46:58,680 --> 00:47:01,839
Speaker 1: many users. So when their mothers and fathers who come

786
00:47:01,920 --> 00:47:05,759
Speaker 1: to us and say, hey, my my son or my

787
00:47:05,880 --> 00:47:09,960
Speaker 1: daughter has for the first time ever communicated to me, mom,

788
00:47:10,040 --> 00:47:13,360
Speaker 1: I love you, or has for the first time drawn

789
00:47:13,640 --> 00:47:16,400
Speaker 1: a drawing on on on anything, but this time on

790
00:47:16,480 --> 00:47:19,759
Speaker 1: the computer with with his or her eyes, I mean

791
00:47:19,880 --> 00:47:24,360
Speaker 1: that that goes beyond anything when you get that type

792
00:47:24,400 --> 00:47:29,520
Speaker 1: of really really kind of strong value, because because a

793
00:47:29,640 --> 00:47:32,640
Speaker 1: person who has previously not been able to communicate can

794
00:47:32,760 --> 00:47:37,000
Speaker 1: now communicate, I mean that that's kind of that's outside anything. Yeah,

795
00:47:37,040 --> 00:47:40,160
Speaker 1: that's transformative. I mean that's that's the sort of story

796
00:47:40,320 --> 00:47:44,040
Speaker 1: that is incredibly inspiring, and it does show that this

797
00:47:44,200 --> 00:47:51,640
Speaker 1: technology has an incredible power, and it can not only

798
00:47:51,680 --> 00:47:56,040
Speaker 1: does have incredible power, it has incredible power to empower

799
00:47:56,600 --> 00:48:01,640
Speaker 1: people who previously had very little chance of having that

800
00:48:01,719 --> 00:48:05,680
Speaker 1: sort of human connection. And until you hear those stories,

801
00:48:06,080 --> 00:48:10,560
Speaker 1: you don't even realize how incredibly valuable that can be

802
00:48:10,840 --> 00:48:13,640
Speaker 1: and how much those of us who haven't had to

803
00:48:14,239 --> 00:48:17,279
Speaker 1: experience that take it for granted. But then you start

804
00:48:17,360 --> 00:48:20,160
Speaker 1: thinking about it and you realize this sort of connection

805
00:48:20,440 --> 00:48:24,800
Speaker 1: that is possible due to technology like this and you really,

806
00:48:25,360 --> 00:48:28,120
Speaker 1: I mean, it really does open up your eyes on

807
00:48:29,239 --> 00:48:31,440
Speaker 1: didn't mean to go with that particular metaphor, but that

808
00:48:31,840 --> 00:48:36,440
Speaker 1: it really it really does does hammer home how how

809
00:48:36,880 --> 00:48:41,719
Speaker 1: incredibly impactful this sort of technology can be. The other

810
00:48:41,960 --> 00:48:43,960
Speaker 1: the other if I take one more example, more from

811
00:48:44,000 --> 00:48:46,480
Speaker 1: the consumer world. You know, I don't think it's hard

812
00:48:46,520 --> 00:48:49,279
Speaker 1: to tromp that type of but take it from the

813
00:48:49,320 --> 00:48:53,160
Speaker 1: consumer world. If I think about a VR headset or

814
00:48:53,360 --> 00:48:55,520
Speaker 1: or an a R or a R air headset, it's

815
00:48:56,239 --> 00:48:59,200
Speaker 1: what what is happening is we are actually seeing that

816
00:48:59,360 --> 00:49:03,640
Speaker 1: we can take a three step interaction and make it

817
00:49:03,719 --> 00:49:06,960
Speaker 1: into two step interaction and take away one entire step

818
00:49:07,080 --> 00:49:10,759
Speaker 1: into every single interaction. So interview had set us of

819
00:49:10,840 --> 00:49:15,200
Speaker 1: today the method to interact with something is one, you

820
00:49:15,320 --> 00:49:17,640
Speaker 1: look at it too, you turn your head or you

821
00:49:17,719 --> 00:49:20,800
Speaker 1: point your hand controller to it. Three, you push a

822
00:49:20,880 --> 00:49:22,800
Speaker 1: button to pick it up or you know, whatever you

823
00:49:22,840 --> 00:49:25,080
Speaker 1: want to do with it. So it's kind of one

824
00:49:25,200 --> 00:49:28,240
Speaker 1: look to turn your head or move your hand control

825
00:49:28,280 --> 00:49:31,080
Speaker 1: to the point, three press a button. You know. Their

826
00:49:31,160 --> 00:49:33,719
Speaker 1: variations could be my voice as well, but there so

827
00:49:33,960 --> 00:49:36,840
Speaker 1: that's a three step process. With eye tracking, you reduced

828
00:49:36,880 --> 00:49:39,920
Speaker 1: that to two step process, which is basically one you

829
00:49:40,080 --> 00:49:44,759
Speaker 1: look and an object to your press. That's fantastic, and

830
00:49:44,880 --> 00:49:47,840
Speaker 1: it creates a deeper sense of immersion because you're no

831
00:49:48,000 --> 00:49:51,680
Speaker 1: longer again you're removing another one of those layers that

832
00:49:51,840 --> 00:49:55,640
Speaker 1: the person using it had to go through previously. Every

833
00:49:55,680 --> 00:49:58,080
Speaker 1: time one of those layers gets removed, then you have

834
00:49:58,280 --> 00:50:02,120
Speaker 1: this this deeper immersing of the sense that creates a

835
00:50:02,200 --> 00:50:06,759
Speaker 1: more convincing experience overall. Yeah, and when you think about that,

836
00:50:07,040 --> 00:50:10,000
Speaker 1: what when you think about what the entire touch revolution,

837
00:50:10,080 --> 00:50:12,200
Speaker 1: what that really is? You know, you know I when

838
00:50:12,200 --> 00:50:13,799
Speaker 1: you've given a touch phone to you, you know, your

839
00:50:13,800 --> 00:50:17,400
Speaker 1: first experience with a touch phone with and and and

840
00:50:17,600 --> 00:50:22,160
Speaker 1: the you know the and the what that revolution is

841
00:50:22,360 --> 00:50:26,160
Speaker 1: is like one you look to your touch. That is

842
00:50:26,200 --> 00:50:27,560
Speaker 1: what you do on the touch phone. It's a two

843
00:50:27,560 --> 00:50:30,520
Speaker 1: step in the direction one too, just like it is

844
00:50:30,560 --> 00:50:33,200
Speaker 1: in the order with eye tracking, one to press about

845
00:50:33,239 --> 00:50:37,200
Speaker 1: them while it's coming from the PC world, where the

846
00:50:37,239 --> 00:50:39,920
Speaker 1: interaction is one look to drag with your mouth or

847
00:50:40,000 --> 00:50:44,399
Speaker 1: your touch pad three click. So the revolution you're going

848
00:50:44,520 --> 00:50:47,040
Speaker 1: through with eye tracking is is exactly the same in

849
00:50:47,200 --> 00:50:49,600
Speaker 1: terms of taking one step away and just having it

850
00:50:49,800 --> 00:50:53,279
Speaker 1: one look to action, one look to action. So it's

851
00:50:53,960 --> 00:50:57,600
Speaker 1: I would argue, it's just as powerful as that touch revolution.

852
00:50:58,640 --> 00:51:00,359
Speaker 1: And when you think, when you think about it further,

853
00:51:01,400 --> 00:51:06,920
Speaker 1: why is this so much more intuitive? It is because

854
00:51:07,000 --> 00:51:10,120
Speaker 1: that is how we have learned to interact, interact even

855
00:51:10,160 --> 00:51:13,000
Speaker 1: since we were a kid. You know, when you, as

856
00:51:13,040 --> 00:51:15,440
Speaker 1: a kid wanted to learn we can interact, to interact

857
00:51:15,480 --> 00:51:17,399
Speaker 1: with something. You have something on the table in front

858
00:51:17,480 --> 00:51:20,680
Speaker 1: of you, it's one look to pick up to explore.

859
00:51:21,520 --> 00:51:24,120
Speaker 1: You know, when you want to turn you on your dishwasher,

860
00:51:24,239 --> 00:51:27,040
Speaker 1: I mean one look at the knob to turn. When

861
00:51:27,080 --> 00:51:28,960
Speaker 1: you want to shake somebody hand, look at the one

862
00:51:29,040 --> 00:51:31,600
Speaker 1: look at the hand to shake the hand. You know,

863
00:51:32,160 --> 00:51:34,560
Speaker 1: it's it's a two step interaction. That is what you

864
00:51:34,760 --> 00:51:37,400
Speaker 1: have learned as a kid to explore, one look to

865
00:51:37,560 --> 00:51:42,759
Speaker 1: pick up and and we're replicating that. And that's why

866
00:51:42,840 --> 00:51:46,280
Speaker 1: it feels so intuitive. And I can tell you anybody

867
00:51:46,400 --> 00:51:49,560
Speaker 1: that we demo a VR or or are application to

868
00:51:49,680 --> 00:51:52,839
Speaker 1: they kind of they get it instantly, like, oh yeah,

869
00:51:53,040 --> 00:51:56,200
Speaker 1: this is more intuitive because it's simple as that we're

870
00:51:56,200 --> 00:51:58,399
Speaker 1: just replicating what you do in the red world, which

871
00:51:58,520 --> 00:52:00,759
Speaker 1: is which is kind of actually, if you wanted to

872
00:52:00,920 --> 00:52:05,759
Speaker 1: virtual reality, it's it's supposedly pretty important to replicate your

873
00:52:05,840 --> 00:52:09,080
Speaker 1: actress in the real world, right, yes, I mean if

874
00:52:09,120 --> 00:52:11,400
Speaker 1: it If it doesn't, then it takes you out of that.

875
00:52:11,600 --> 00:52:15,160
Speaker 1: You're aware that you are in an artificial experience. And

876
00:52:15,520 --> 00:52:19,040
Speaker 1: uh And obviously the goal is to reduce that awareness

877
00:52:19,080 --> 00:52:22,239
Speaker 1: as much as possible so that you can really have

878
00:52:22,520 --> 00:52:25,600
Speaker 1: that the experience of the developer intended when he or

879
00:52:25,680 --> 00:52:30,239
Speaker 1: she started to design it. Uh And and ideally, at

880
00:52:30,280 --> 00:52:34,440
Speaker 1: least for most VR experiences, that's to strip away all

881
00:52:34,560 --> 00:52:38,399
Speaker 1: the rest of the awareness in augmented reality. Obviously it's

882
00:52:38,400 --> 00:52:41,680
Speaker 1: meant to augment and experience in the real world, but

883
00:52:41,760 --> 00:52:45,560
Speaker 1: even then, you want to you want to reduce the

884
00:52:45,800 --> 00:52:49,120
Speaker 1: load on the user of having to think, oh, well,

885
00:52:49,239 --> 00:52:52,279
Speaker 1: if I want to accomplish goal X, I have to

886
00:52:52,360 --> 00:52:55,360
Speaker 1: go through these steps in order to actually do that.

887
00:52:55,680 --> 00:52:57,600
Speaker 1: Whereas in the real world, if you were looking at

888
00:52:57,640 --> 00:53:01,440
Speaker 1: an actual physical rep of what you were seeing in

889
00:53:01,480 --> 00:53:03,840
Speaker 1: the argumented world, you wouldn't have to go through that

890
00:53:03,960 --> 00:53:06,280
Speaker 1: because that's just not the way the real world world works.

891
00:53:07,320 --> 00:53:11,080
Speaker 1: Imagine imagine, imagine a fast paced VR game or a

892
00:53:11,239 --> 00:53:13,279
Speaker 1: R game, it doesn't matter. I mean, you would be

893
00:53:13,480 --> 00:53:15,960
Speaker 1: running down a pitch in a in a football match,

894
00:53:16,400 --> 00:53:18,280
Speaker 1: and you want to pass the ball to somebody who's

895
00:53:18,360 --> 00:53:22,400
Speaker 1: running full speed in the other direction, and then you

896
00:53:22,880 --> 00:53:25,640
Speaker 1: how do you do that with the current controls in

897
00:53:25,719 --> 00:53:28,600
Speaker 1: the R I mean you're running full speed your yourself,

898
00:53:28,719 --> 00:53:32,319
Speaker 1: and then you should either point your head to kind

899
00:53:32,320 --> 00:53:35,080
Speaker 1: of to to point to the other, to the other,

900
00:53:35,239 --> 00:53:37,719
Speaker 1: to your teammates running in the other direction, and do

901
00:53:37,840 --> 00:53:39,960
Speaker 1: that continuously to tell the computer where you want to

902
00:53:40,000 --> 00:53:41,759
Speaker 1: tell your head that way you want to pass the ball,

903
00:53:42,840 --> 00:53:46,000
Speaker 1: or you should running full speed one direction. You should

904
00:53:46,000 --> 00:53:48,080
Speaker 1: point your hand to tell the via heads that I

905
00:53:48,120 --> 00:53:51,640
Speaker 1: want to pass the ball to this guy. That's super hard.

906
00:53:51,920 --> 00:53:54,120
Speaker 1: I mean, that's just gonna It's just impossible. You can

907
00:53:54,160 --> 00:53:56,000
Speaker 1: try to do it yourself in your any room if

908
00:53:56,040 --> 00:53:59,600
Speaker 1: you want. But or you imagine the interaction. You're running down,

909
00:54:00,120 --> 00:54:01,920
Speaker 1: you know, in one direction, you look at the guy

910
00:54:02,080 --> 00:54:03,680
Speaker 1: running in the other direction. You can do that. You

911
00:54:03,719 --> 00:54:07,040
Speaker 1: can follow that person extremely easily with the rice and

912
00:54:07,120 --> 00:54:08,960
Speaker 1: then you just press a button then post that a guy.

913
00:54:10,000 --> 00:54:13,799
Speaker 1: That's that's just so much easier, and it takes down

914
00:54:14,040 --> 00:54:16,640
Speaker 1: this barrier. It takes away one step and it will

915
00:54:17,040 --> 00:54:20,120
Speaker 1: enable game developers to make Vio games more immersive and

916
00:54:20,160 --> 00:54:22,839
Speaker 1: also more frost pace, because otherwise you need to kind

917
00:54:22,880 --> 00:54:25,200
Speaker 1: of slow down the pace in order to make people

918
00:54:25,680 --> 00:54:27,799
Speaker 1: hit the right person. And not only that, I would

919
00:54:27,840 --> 00:54:30,919
Speaker 1: add that it adds in an element that you see

920
00:54:30,960 --> 00:54:33,440
Speaker 1: in the real world all the time, which is misdirection,

921
00:54:33,640 --> 00:54:36,600
Speaker 1: purposeful misdirection. If you're playing on a team and you

922
00:54:36,719 --> 00:54:39,800
Speaker 1: want to pass to a teammate, you don't want to

923
00:54:39,920 --> 00:54:44,160
Speaker 1: telegraph that to the other team. So so being able

924
00:54:44,200 --> 00:54:47,719
Speaker 1: to use your attention to direct the ball in the

925
00:54:47,920 --> 00:54:50,200
Speaker 1: in the right direction without having to turn your head

926
00:54:50,239 --> 00:54:52,800
Speaker 1: and make it obvious, oh well, he's about to pass

927
00:54:52,920 --> 00:54:55,680
Speaker 1: to his teammate on his left, then it makes it

928
00:54:55,760 --> 00:54:58,879
Speaker 1: more challenging for the opposing team to anticipate what your

929
00:54:58,920 --> 00:55:03,120
Speaker 1: move is. Yeah, or more I mean more like personal

930
00:55:03,280 --> 00:55:06,480
Speaker 1: connecting interaction. I mean you're sitting around the table, you're

931
00:55:06,520 --> 00:55:10,000
Speaker 1: talking to set up people. Imagine you have two people

932
00:55:10,040 --> 00:55:12,200
Speaker 1: in front of you now, and then you start talking

933
00:55:12,280 --> 00:55:15,719
Speaker 1: to one of them. You would be looking at that person, um,

934
00:55:16,360 --> 00:55:18,399
Speaker 1: but you would be looking at that person with your eyes.

935
00:55:18,680 --> 00:55:21,719
Speaker 1: You would not turn your forehead to that person. So

936
00:55:21,840 --> 00:55:23,560
Speaker 1: the v R A R head said would not know

937
00:55:24,320 --> 00:55:27,719
Speaker 1: that you're you weren't talking to person A. It may

938
00:55:28,120 --> 00:55:29,839
Speaker 1: you may have your head the point still the point

939
00:55:29,880 --> 00:55:32,719
Speaker 1: that that person be. So then the via head said,

940
00:55:32,719 --> 00:55:36,440
Speaker 1: would it would the wrong person would not or blink

941
00:55:36,680 --> 00:55:38,759
Speaker 1: or or or or smile at you when you when

942
00:55:38,800 --> 00:55:41,520
Speaker 1: you smile back at them, because they you don't know

943
00:55:42,560 --> 00:55:46,600
Speaker 1: what you're what, what you're interesting. You only know what

944
00:55:46,760 --> 00:55:49,320
Speaker 1: you're interested in, what you're interested in if you know

945
00:55:49,360 --> 00:55:52,440
Speaker 1: where you're looking, because your forehead is just an approximation

946
00:55:52,520 --> 00:55:54,520
Speaker 1: of your interest, and it's always it's going to be

947
00:55:54,840 --> 00:55:57,319
Speaker 1: wrong in in certain number of cases. Oh sure. Yeah.

948
00:55:57,560 --> 00:56:00,880
Speaker 1: So if you were in a game that wire's interaction

949
00:56:01,000 --> 00:56:06,719
Speaker 1: with uh PC controlled characters, and you're trying desperately to

950
00:56:07,400 --> 00:56:10,759
Speaker 1: uh to align yourself with one character, and there's a

951
00:56:10,880 --> 00:56:13,680
Speaker 1: secondary character there, and you accidentally swear fealty to the

952
00:56:13,760 --> 00:56:18,800
Speaker 1: bad guy, Suddenly the whole game has changed, yeah, or

953
00:56:18,960 --> 00:56:22,640
Speaker 1: just feels less immersive because the people you look at

954
00:56:22,680 --> 00:56:25,120
Speaker 1: their stone face, they don't want to spot at them

955
00:56:25,200 --> 00:56:28,160
Speaker 1: because they don't understand they're looking at them because you didn't.

956
00:56:28,600 --> 00:56:31,239
Speaker 1: You didn't do you didn't turn your forehead to them

957
00:56:31,280 --> 00:56:33,640
Speaker 1: to indicate that you actually want to speak to them,

958
00:56:33,880 --> 00:56:35,560
Speaker 1: which is I'm not sure you don't do that really

959
00:56:35,600 --> 00:56:38,000
Speaker 1: well and I could see this also just being useful

960
00:56:38,280 --> 00:56:41,600
Speaker 1: in a virtual meeting space where you're just having a

961
00:56:41,880 --> 00:56:44,200
Speaker 1: like just a not a game element at all, just

962
00:56:44,320 --> 00:56:48,480
Speaker 1: a literally a meeting where you have multiple people logging

963
00:56:48,560 --> 00:56:51,839
Speaker 1: in through various devices. Being able to see where anyone's

964
00:56:52,360 --> 00:56:56,640
Speaker 1: gaze is is incredibly useful because if you're addressing questions

965
00:56:56,719 --> 00:56:59,480
Speaker 1: to somebody, you don't have to It's it's kind of

966
00:56:59,520 --> 00:57:02,719
Speaker 1: like inter acting with a personal digital assistant that's voice

967
00:57:02,719 --> 00:57:06,520
Speaker 1: activated today where uh, you know you. You use a

968
00:57:06,840 --> 00:57:10,759
Speaker 1: typically a name that indicates this is the alert to

969
00:57:11,200 --> 00:57:13,920
Speaker 1: listen in and then to respond. But it's not the

970
00:57:13,960 --> 00:57:16,040
Speaker 1: way we humans tend to talk to one another. If

971
00:57:16,080 --> 00:57:18,280
Speaker 1: I were having a conversation with you, and I started

972
00:57:18,320 --> 00:57:21,960
Speaker 1: every sense with Oscar, what do you think about after

973
00:57:22,000 --> 00:57:24,720
Speaker 1: about after about five or six sentences, it feels weird.

974
00:57:26,280 --> 00:57:30,560
Speaker 1: So you've got it. You've got it. Can I hire you? No?

975
00:57:31,040 --> 00:57:33,320
Speaker 1: But that's that's it. You can I take one more

976
00:57:33,440 --> 00:57:37,320
Speaker 1: use case, just absolutely please do or another I mean

977
00:57:37,440 --> 00:57:40,080
Speaker 1: just to take it in a different direction or tangent.

978
00:57:40,640 --> 00:57:45,520
Speaker 1: It's it also can also affect the actual core rendering

979
00:57:45,680 --> 00:57:49,560
Speaker 1: of the graphics. So I mean today in VR or

980
00:57:49,600 --> 00:57:53,200
Speaker 1: in PC, I mean, we're all creating to create beautiful

981
00:57:53,240 --> 00:57:56,840
Speaker 1: games with with as high resolution as possible, but that

982
00:57:57,040 --> 00:57:58,960
Speaker 1: takes a high toll on on the on the GPU

983
00:57:59,600 --> 00:58:04,960
Speaker 1: mhm um. But actually the human eyes only perceiving what

984
00:58:05,120 --> 00:58:07,720
Speaker 1: you look at in high resolution where you look at it,

985
00:58:08,040 --> 00:58:11,720
Speaker 1: the rest is kind of blurring. So that means you

986
00:58:11,800 --> 00:58:14,000
Speaker 1: can do something called phobid rendering, that is that you

987
00:58:14,160 --> 00:58:18,040
Speaker 1: only render in high resolution in the area you look

988
00:58:18,920 --> 00:58:22,160
Speaker 1: and in low resolution in the prefery, and then you

989
00:58:22,280 --> 00:58:25,360
Speaker 1: look at a different point, and then it switches very

990
00:58:25,440 --> 00:58:27,600
Speaker 1: fast to render in high resolution where you look at

991
00:58:27,680 --> 00:58:31,760
Speaker 1: that point and in lower resolution and periphery. As a user,

992
00:58:31,960 --> 00:58:35,160
Speaker 1: you cannot notice because this is all happening too fast.

993
00:58:35,280 --> 00:58:39,200
Speaker 1: You you're not noticing that the entire world is rendered

994
00:58:39,240 --> 00:58:43,320
Speaker 1: in lower resolution in the prefery. But you save thirty

995
00:58:43,400 --> 00:58:46,880
Speaker 1: or two on the GP capacity excellent. So then that

996
00:58:47,000 --> 00:58:50,840
Speaker 1: also means that you're not overheating your machine. It means

997
00:58:50,920 --> 00:58:55,160
Speaker 1: that devices that have say the latest and greatest in

998
00:58:55,360 --> 00:59:00,120
Speaker 1: in graphics hardware, that's going to remain relevant longer that

999
00:59:00,200 --> 00:59:02,439
Speaker 1: it would be like the life cycle of these things

1000
00:59:02,560 --> 00:59:05,000
Speaker 1: is notoriously fairly short. If you want to be on

1001
00:59:05,160 --> 00:59:08,680
Speaker 1: the cutting edge of capability. But if you're using a

1002
00:59:08,760 --> 00:59:14,080
Speaker 1: strategy such as this that reduces that load, then you've

1003
00:59:14,160 --> 00:59:18,919
Speaker 1: extended the life, the useful lifespan of those uh, those

1004
00:59:19,080 --> 00:59:22,560
Speaker 1: those components by quite a bit because you don't you're

1005
00:59:22,600 --> 00:59:25,760
Speaker 1: not maxing out as quickly as you would in the

1006
00:59:26,960 --> 00:59:28,600
Speaker 1: in the real world. I mean I that was one

1007
00:59:28,640 --> 00:59:32,360
Speaker 1: of the reasons why back in the nineties gaming computers

1008
00:59:33,200 --> 00:59:35,680
Speaker 1: got to the first they became a thing, and then

1009
00:59:35,760 --> 00:59:37,800
Speaker 1: they became a thing that I just could not keep

1010
00:59:37,880 --> 00:59:40,320
Speaker 1: up with. And it was very frustrating for me to

1011
00:59:40,400 --> 00:59:43,520
Speaker 1: think that every six months my machine was out of

1012
00:59:43,600 --> 00:59:46,360
Speaker 1: date enough where if I went out and purchased a

1013
00:59:46,440 --> 00:59:48,920
Speaker 1: new game six months after I bought a machine, or

1014
00:59:49,000 --> 00:59:52,040
Speaker 1: I bought a graphics card, I could not run it

1015
00:59:52,640 --> 00:59:55,120
Speaker 1: at the settings I wanted to because it would be

1016
00:59:55,280 --> 00:59:58,520
Speaker 1: too strong, to too big a strain on my components.

1017
00:59:58,560 --> 01:00:01,720
Speaker 1: I would have to actually upgrade my hardware. So if

1018
01:00:01,720 --> 01:00:04,360
Speaker 1: you're able to solve that through software where you're you're

1019
01:00:04,360 --> 01:00:08,600
Speaker 1: able to reduce that load, to me, that's phenomenal because

1020
01:00:09,440 --> 01:00:13,800
Speaker 1: it takes me out of that massochistic relationship I had have.

1021
01:00:14,880 --> 01:00:16,880
Speaker 1: You can be also be a little bit less of

1022
01:00:16,880 --> 01:00:19,120
Speaker 1: a bullet sponsor. Right, Oh, yes, that would also, that

1023
01:00:19,120 --> 01:00:22,200
Speaker 1: would be lovely. I mean, let's not dream too big here, Oscar.

1024
01:00:22,360 --> 01:00:26,840
Speaker 1: Let's let's keep our expectations realistic. No, but you can.

1025
01:00:26,880 --> 01:00:29,920
Speaker 1: You can use it obviously to keep your hardware longer

1026
01:00:30,160 --> 01:00:32,760
Speaker 1: or to reduce your cost of your hardwork. Or you

1027
01:00:32,880 --> 01:00:35,800
Speaker 1: can use it to get a better immersion by being

1028
01:00:35,840 --> 01:00:40,080
Speaker 1: able to get your computer to handle high resolution graphics.

1029
01:00:41,240 --> 01:00:44,720
Speaker 1: Or you can get your computer to um to run

1030
01:00:44,760 --> 01:00:49,120
Speaker 1: at the higher refresh rate or higher FPS. So you

1031
01:00:49,200 --> 01:00:52,960
Speaker 1: can use it, you know, however you want either to

1032
01:00:53,000 --> 01:00:55,560
Speaker 1: save cost or prolong your prolong your lifetime, or or

1033
01:00:55,680 --> 01:00:58,800
Speaker 1: two to to to run the game in a in

1034
01:00:59,400 --> 01:01:04,240
Speaker 1: in higher solution and get more Marcy, that's fantastic, Oscar.

1035
01:01:04,480 --> 01:01:08,000
Speaker 1: Thank you so much for joining me on this podcast.

1036
01:01:08,120 --> 01:01:11,000
Speaker 1: This has been a fascinating conversation. I very much appreciate

1037
01:01:11,080 --> 01:01:15,360
Speaker 1: your time. Alright, when we come back, we'll talk a

1038
01:01:15,480 --> 01:01:18,320
Speaker 1: bit more about eye tracking technology and where it's going.

1039
01:01:18,480 --> 01:01:22,400
Speaker 1: But first let's take another quick break to thank our sponsor.

1040
01:01:29,200 --> 01:01:32,240
Speaker 1: As Mr Werner pointed out, the data we generate through

1041
01:01:32,440 --> 01:01:36,560
Speaker 1: our attention is valuable, and it also poses a clear

1042
01:01:36,680 --> 01:01:40,160
Speaker 1: threat to our privacy if it is handled poorly. Now,

1043
01:01:40,240 --> 01:01:44,320
Speaker 1: I appreciate that Toby's policy is to only use data

1044
01:01:44,440 --> 01:01:47,640
Speaker 1: with the permission of the user, because you can easily

1045
01:01:47,720 --> 01:01:51,120
Speaker 1: imagine scenarios which could be compromising if you did not

1046
01:01:51,400 --> 01:01:54,320
Speaker 1: realize your eye movements were being tracked. So, for example,

1047
01:01:55,480 --> 01:01:59,080
Speaker 1: let's say they're going in for a job interview for

1048
01:01:59,400 --> 01:02:02,760
Speaker 1: a big tech company, and you're qualified, and you are

1049
01:02:02,880 --> 01:02:06,840
Speaker 1: knowledgeable in your field. You are a hard worker and

1050
01:02:07,160 --> 01:02:11,840
Speaker 1: you really really want this job, but you're also a

1051
01:02:11,920 --> 01:02:16,120
Speaker 1: bit nervous about going in and interviewing. That's to be expected,

1052
01:02:16,400 --> 01:02:19,560
Speaker 1: and because you're nervous, you know, you're looking around a lot.

1053
01:02:19,680 --> 01:02:22,160
Speaker 1: You don't really want to hold anyone's eye contact for

1054
01:02:22,280 --> 01:02:24,600
Speaker 1: too long because you don't want to come across as

1055
01:02:24,840 --> 01:02:27,440
Speaker 1: too intense or anything. So you know, you're you're just

1056
01:02:27,560 --> 01:02:30,160
Speaker 1: trying to feel your way through this experience as best

1057
01:02:30,240 --> 01:02:34,000
Speaker 1: you can. And unbeknownst to you, but beknownst to us,

1058
01:02:34,720 --> 01:02:37,440
Speaker 1: the people meaning with you are also using a system

1059
01:02:37,560 --> 01:02:41,600
Speaker 1: with eye tracking technology to observe you throughout the interview process,

1060
01:02:42,160 --> 01:02:45,320
Speaker 1: and the system is analyzing you as you respond to

1061
01:02:45,440 --> 01:02:48,680
Speaker 1: questions and converse with others. It's watching your eye movements

1062
01:02:48,760 --> 01:02:53,240
Speaker 1: and tracking that against various behavior patterns and drawing some conclusions,

1063
01:02:53,760 --> 01:02:57,920
Speaker 1: and maybe some software is generating a report that assigns

1064
01:02:58,120 --> 01:03:03,360
Speaker 1: metrics to fuzzy categories just assertiveness or honesty, and maybe

1065
01:03:03,520 --> 01:03:06,680
Speaker 1: even though you really are the best candidate for the job,

1066
01:03:06,840 --> 01:03:09,360
Speaker 1: the system tells the hiring manager that you're nothing more

1067
01:03:09,440 --> 01:03:13,400
Speaker 1: than a shifty peat and they shouldn't hire you. Now

1068
01:03:13,480 --> 01:03:15,120
Speaker 1: that kind of sounds silly the way I'm putting it,

1069
01:03:15,240 --> 01:03:19,560
Speaker 1: but it's certainly something that could potentially happen, and the

1070
01:03:19,640 --> 01:03:23,400
Speaker 1: technology already exists. Really, it just means that you have

1071
01:03:23,520 --> 01:03:26,680
Speaker 1: to create the software, which largely would mean making sure

1072
01:03:26,760 --> 01:03:30,920
Speaker 1: that your software is at least on the surface, dependent

1073
01:03:31,120 --> 01:03:35,480
Speaker 1: upon reasonable psychology. Right. You can't just say I think

1074
01:03:35,600 --> 01:03:38,360
Speaker 1: that if you look up, you are lying. That's one

1075
01:03:38,440 --> 01:03:42,320
Speaker 1: of those little bits of folk wisdom that actually isn't true.

1076
01:03:43,000 --> 01:03:45,120
Speaker 1: So you would want to make sure that your software

1077
01:03:45,600 --> 01:03:47,960
Speaker 1: is based off of science, or at least appears to

1078
01:03:48,000 --> 01:03:49,600
Speaker 1: be based off of science. I mean, if you're not

1079
01:03:49,720 --> 01:03:52,480
Speaker 1: being very ethical, you could sell your software package no

1080
01:03:52,600 --> 01:03:55,880
Speaker 1: matter what. But it's easy to imagine that sort of

1081
01:03:55,960 --> 01:04:01,920
Speaker 1: scenario actually happening. That a company be that assertive or

1082
01:04:02,000 --> 01:04:06,400
Speaker 1: aggressive and its hiring strategies to incorporate that level of

1083
01:04:06,560 --> 01:04:09,880
Speaker 1: screening when they're looking at potential employees. But it's not

1084
01:04:10,080 --> 01:04:15,120
Speaker 1: really fair and it certainly seems invasive. Now that's the hypothetical.

1085
01:04:15,480 --> 01:04:18,240
Speaker 1: It's not something that I'm actually referring to that's happened

1086
01:04:18,240 --> 01:04:21,320
Speaker 1: in the real world to my knowledge, but it's the

1087
01:04:21,400 --> 01:04:23,520
Speaker 1: sort of stuff we don't want to see. It places

1088
01:04:23,560 --> 01:04:26,680
Speaker 1: people at a disadvantage, and it could also be used

1089
01:04:26,720 --> 01:04:30,439
Speaker 1: to create opportunities for abuse in many ways, which again

1090
01:04:30,600 --> 01:04:33,280
Speaker 1: is why that policy of only collecting information with the

1091
01:04:33,360 --> 01:04:37,080
Speaker 1: express permission of the user is important. You wouldn't want

1092
01:04:37,200 --> 01:04:41,640
Speaker 1: to come back at somebody and say, hey, I noticed

1093
01:04:41,720 --> 01:04:44,120
Speaker 1: that you were spending an awful lot of time looking

1094
01:04:44,240 --> 01:04:47,360
Speaker 1: at this one person in the room. Uh. It makes

1095
01:04:47,440 --> 01:04:50,880
Speaker 1: us uncomfortable because it appears that you have some sort

1096
01:04:51,200 --> 01:04:55,920
Speaker 1: of attraction to or maybe animosity towards this person. All

1097
01:04:56,000 --> 01:04:58,920
Speaker 1: of that seems like it could go south in a hurry,

1098
01:04:59,480 --> 01:05:03,919
Speaker 1: and it be reflective of something that is not actually real.

1099
01:05:04,560 --> 01:05:08,240
Speaker 1: Because while our eyes are an indicator of where our

1100
01:05:08,280 --> 01:05:11,920
Speaker 1: attention happens to be, it's not always the case that

1101
01:05:12,080 --> 01:05:14,960
Speaker 1: what our eyes are pointing at is what we're actually

1102
01:05:15,080 --> 01:05:18,480
Speaker 1: focusing on. It's most of the time that's the case,

1103
01:05:18,840 --> 01:05:22,280
Speaker 1: especially when we're being very active with our attention, but

1104
01:05:22,400 --> 01:05:25,640
Speaker 1: it's not always the case. So this is a complicated issue.

1105
01:05:26,920 --> 01:05:30,160
Speaker 1: I think eye tracking tech has far too much potential

1106
01:05:30,240 --> 01:05:33,560
Speaker 1: to do great things for us to be too wary

1107
01:05:33,640 --> 01:05:35,320
Speaker 1: of it. I don't think we need to back off

1108
01:05:35,400 --> 01:05:38,040
Speaker 1: of it. I don't think we need to abandon it.

1109
01:05:38,200 --> 01:05:41,360
Speaker 1: I don't think we need to label it as irresponsible

1110
01:05:41,480 --> 01:05:45,120
Speaker 1: or dangerous technology. We just have to make sure we

1111
01:05:45,320 --> 01:05:52,959
Speaker 1: hold organizations, companies, researchers accountable for responsible implementations of the tech.

1112
01:05:53,880 --> 01:05:57,840
Speaker 1: But these applications really could transform our world, particularly for

1113
01:05:57,960 --> 01:06:01,520
Speaker 1: people who have difficulty interacting with others or with their

1114
01:06:01,680 --> 01:06:04,960
Speaker 1: environment if they don't have that kind of technology at

1115
01:06:05,000 --> 01:06:08,200
Speaker 1: their disposal. So, like Mr Werner said, a technology that

1116
01:06:08,280 --> 01:06:12,320
Speaker 1: helps someone communicate after it appeared that all such ability

1117
01:06:12,440 --> 01:06:16,240
Speaker 1: had been lost is an incredibly powerful story, and it's

1118
01:06:16,280 --> 01:06:20,320
Speaker 1: hard to think of something more impactful than that. On

1119
01:06:20,440 --> 01:06:24,080
Speaker 1: the research side, scientists are using eye tracking to learn

1120
01:06:24,120 --> 01:06:28,480
Speaker 1: more about cognitive development. There's a researcher named Alex Willard

1121
01:06:28,760 --> 01:06:32,040
Speaker 1: who is working on her PhD and Maternal infant directed

1122
01:06:32,160 --> 01:06:36,000
Speaker 1: speech at the University of Newcastle and Hunter Medical Research

1123
01:06:36,080 --> 01:06:39,640
Speaker 1: Institute in New South Wales, and she's using eye tracking

1124
01:06:39,680 --> 01:06:44,040
Speaker 1: technology to study how babies develop cognitive skills. She's learning

1125
01:06:44,360 --> 01:06:48,919
Speaker 1: how babies recognize and solve problems. And I didn't even

1126
01:06:49,000 --> 01:06:53,919
Speaker 1: know babies could do that. I haven't seen Baby Boss though,

1127
01:06:53,960 --> 01:06:57,200
Speaker 1: so maybe it's all explained in that movie. Anyway. The

1128
01:06:57,240 --> 01:07:01,920
Speaker 1: study involves babies watching animations on greens and it tracks

1129
01:07:02,040 --> 01:07:05,240
Speaker 1: where their eyes go. So, for example, let's say you've

1130
01:07:05,240 --> 01:07:08,080
Speaker 1: got a cute cartoon bunny hopping around on the screen,

1131
01:07:08,160 --> 01:07:10,840
Speaker 1: and the baby notices the bunny and the baby's eyes

1132
01:07:10,840 --> 01:07:13,040
Speaker 1: are tracking where the bunny is going on the screen,

1133
01:07:13,480 --> 01:07:16,480
Speaker 1: and then the cartoon bunny hops behind a cartoon bush.

1134
01:07:17,040 --> 01:07:20,720
Speaker 1: Now at that point does the baby's focus continue along

1135
01:07:20,800 --> 01:07:23,120
Speaker 1: the bunny's pathway to the other side of the bush,

1136
01:07:23,400 --> 01:07:29,800
Speaker 1: anticipating the bunny's reappearance, And if not, why not? Now?

1137
01:07:29,880 --> 01:07:33,240
Speaker 1: Early results in the research project, and this project is

1138
01:07:33,280 --> 01:07:36,200
Speaker 1: scheduled to last for five years. It's a long term

1139
01:07:36,360 --> 01:07:40,480
Speaker 1: project to make sure that any findings are things that

1140
01:07:40,640 --> 01:07:45,400
Speaker 1: that can be backed up with replication. Some of the

1141
01:07:45,480 --> 01:07:48,960
Speaker 1: early research has suggested that babies who are less distractable

1142
01:07:49,360 --> 01:07:51,880
Speaker 1: when focusing on a subject tend to be better at

1143
01:07:51,960 --> 01:07:56,080
Speaker 1: problems solving later on, which makes sense intuitively, you would

1144
01:07:56,160 --> 01:07:58,600
Speaker 1: imagine that to be the case. But this approach could

1145
01:07:58,640 --> 01:08:02,480
Speaker 1: help parents detect potential challenges early on and address them

1146
01:08:02,800 --> 01:08:05,439
Speaker 1: and give their children the best chance of overcoming those

1147
01:08:05,520 --> 01:08:08,960
Speaker 1: challenges as they grow older. So you might see that

1148
01:08:09,080 --> 01:08:12,760
Speaker 1: certain cognitive development might be running a little bit behind

1149
01:08:12,960 --> 01:08:17,000
Speaker 1: average from you know, the mean, and you might say, well,

1150
01:08:17,439 --> 01:08:19,400
Speaker 1: what can we do to address that? Are there things

1151
01:08:19,479 --> 01:08:22,559
Speaker 1: we can do as parents to help encourage our child's

1152
01:08:22,640 --> 01:08:26,479
Speaker 1: cognitive development in these areas and thus give your kid

1153
01:08:26,640 --> 01:08:30,160
Speaker 1: the best chance for success. It's kind of cool, I think,

1154
01:08:30,479 --> 01:08:33,000
Speaker 1: and it gives a lot more information and power to parents,

1155
01:08:33,280 --> 01:08:37,240
Speaker 1: stuff that people didn't have at their disposal without tools

1156
01:08:37,320 --> 01:08:41,640
Speaker 1: like this eye tracking tech that can back up those observations. Now,

1157
01:08:41,720 --> 01:08:45,599
Speaker 1: another study sounds ominous upon first glance. I was reading

1158
01:08:45,640 --> 01:08:47,920
Speaker 1: headlines and this one jumped out at me and it

1159
01:08:48,080 --> 01:08:51,240
Speaker 1: made me pause. It was the National Institute of Health

1160
01:08:51,560 --> 01:08:55,920
Speaker 1: spending four thousand, two hundred twenty dollars on eye tracking

1161
01:08:55,960 --> 01:09:00,120
Speaker 1: technology to analyze the eye movements of Latino customers at

1162
01:09:00,160 --> 01:09:05,080
Speaker 1: grocery stores. That was essentially the headline which made me say,

1163
01:09:05,320 --> 01:09:11,000
Speaker 1: what is going on here that sounds minority report esque,

1164
01:09:11,680 --> 01:09:19,000
Speaker 1: but upon further observation further investigation, it's not nearly that scary.

1165
01:09:19,280 --> 01:09:23,000
Speaker 1: It's actually kind of interesting. In this case. This is

1166
01:09:23,080 --> 01:09:26,000
Speaker 1: a study at San Diego State University that has the

1167
01:09:26,080 --> 01:09:29,960
Speaker 1: goal of finding ways to fight obesity, and the system

1168
01:09:30,080 --> 01:09:33,439
Speaker 1: is meant to provide data about the decisions that overweight

1169
01:09:33,680 --> 01:09:36,840
Speaker 1: or obese people are making as they shop for groceries,

1170
01:09:37,360 --> 01:09:40,439
Speaker 1: and it's in an effort to get insight into what

1171
01:09:40,880 --> 01:09:44,639
Speaker 1: is causing them to make those decisions. Are there specific

1172
01:09:44,760 --> 01:09:48,560
Speaker 1: things in the grocery store environment that are triggering those decisions.

1173
01:09:49,400 --> 01:09:52,800
Speaker 1: Can adjustments to the environment help guide customers into making

1174
01:09:52,880 --> 01:09:56,080
Speaker 1: more healthy choices? And the reason the study is looking

1175
01:09:56,160 --> 01:09:59,760
Speaker 1: at the Latino population in particular is that, according to

1176
01:09:59,800 --> 01:10:05,280
Speaker 1: the researchers, as a demographic, Latinos are disproportionately affected by obesity.

1177
01:10:05,680 --> 01:10:09,479
Speaker 1: They also shop more frequently than other populations do, and

1178
01:10:09,600 --> 01:10:12,920
Speaker 1: they tend to go shopping with children more frequently than

1179
01:10:13,000 --> 01:10:17,439
Speaker 1: other demographics do. So the hope is that by using

1180
01:10:17,479 --> 01:10:20,680
Speaker 1: the information from this study, we can come up with

1181
01:10:20,920 --> 01:10:24,160
Speaker 1: strategies that help people make better choices and have a

1182
01:10:24,280 --> 01:10:27,960
Speaker 1: healthier life, and also provide a healthier life for their children.

1183
01:10:29,000 --> 01:10:32,360
Speaker 1: In the consumer world, companies like Toyota are using eye

1184
01:10:32,400 --> 01:10:35,479
Speaker 1: tracking technology to measure how effective their show rooms are

1185
01:10:35,680 --> 01:10:38,560
Speaker 1: drawing attention to the features that they want to communicate

1186
01:10:38,600 --> 01:10:42,000
Speaker 1: to potential buyers. There might be something on a new

1187
01:10:42,080 --> 01:10:45,519
Speaker 1: Toyota model that the company really wants people to pay

1188
01:10:45,560 --> 01:10:48,479
Speaker 1: attention to, and they use the eye tracking technology to

1189
01:10:48,520 --> 01:10:50,680
Speaker 1: see if it's working, and if it's not working, can

1190
01:10:50,760 --> 01:10:56,160
Speaker 1: they adjust their approach to make it more attractive. And

1191
01:10:56,400 --> 01:11:00,160
Speaker 1: inside vehicles, we're seeing more eye tracking technology, both as

1192
01:11:00,200 --> 01:11:03,080
Speaker 1: a safety measure in the case of systems that monitor

1193
01:11:03,160 --> 01:11:07,040
Speaker 1: a driver's wakefulness or attention, and as a user interface.

1194
01:11:07,320 --> 01:11:11,040
Speaker 1: There's a Canadian research team that's using eye tracking technology

1195
01:11:11,120 --> 01:11:15,040
Speaker 1: to look at the potential for driver distractions. So it's

1196
01:11:15,120 --> 01:11:19,360
Speaker 1: monitoring a driver so that if the driver takes his

1197
01:11:19,560 --> 01:11:21,760
Speaker 1: or her attention away from the road, Let's say they

1198
01:11:21,800 --> 01:11:26,599
Speaker 1: are checking the various instrumentation panels, or maybe they're looking

1199
01:11:26,680 --> 01:11:30,080
Speaker 1: at their phone trying to read a respond to a text.

1200
01:11:31,080 --> 01:11:34,960
Speaker 1: The system the car would actually become aware of this.

1201
01:11:35,760 --> 01:11:39,759
Speaker 1: Maybe it would start to engage some driver assist features,

1202
01:11:40,160 --> 01:11:43,360
Speaker 1: maybe even taking over control of the car briefly, or

1203
01:11:43,479 --> 01:11:45,960
Speaker 1: it might send an alert to the driver saying, Hey,

1204
01:11:46,240 --> 01:11:48,720
Speaker 1: your attention is wandering away from the road. You really

1205
01:11:48,800 --> 01:11:52,040
Speaker 1: need to pay more mind to the task at hand.

1206
01:11:53,040 --> 01:11:57,559
Speaker 1: On the user interface side, Porsche recently revealed an electric

1207
01:11:57,640 --> 01:12:01,240
Speaker 1: car concept called the Mission E. I should really get

1208
01:12:01,360 --> 01:12:04,040
Speaker 1: Scott Benjamin in here to talk about this concept car.

1209
01:12:04,040 --> 01:12:06,400
Speaker 1: It's kind of neat. It's an electronic card. It's supposed

1210
01:12:06,439 --> 01:12:09,640
Speaker 1: to be a sports car that could compete with the

1211
01:12:09,880 --> 01:12:15,679
Speaker 1: Tesla sports Car electronic sports car, and these would include

1212
01:12:17,000 --> 01:12:20,879
Speaker 1: eye tracking type control systems for the in dashboard systems

1213
01:12:20,920 --> 01:12:24,920
Speaker 1: as well as the the entertainment systems, the various instrumentation panels.

1214
01:12:25,000 --> 01:12:27,040
Speaker 1: It would be able to detect what you're looking at

1215
01:12:27,120 --> 01:12:30,360
Speaker 1: and give you information based upon that. And I imagine

1216
01:12:30,400 --> 01:12:33,040
Speaker 1: we'll see even more of this technology built into self

1217
01:12:33,160 --> 01:12:35,920
Speaker 1: driving vehicles in the future, when the cars we get

1218
01:12:35,960 --> 01:12:39,000
Speaker 1: into become interactive environments that allow us to do all

1219
01:12:39,040 --> 01:12:42,519
Speaker 1: sorts of things we couldn't do as human drivers. And again,

1220
01:12:43,360 --> 01:12:46,760
Speaker 1: this is just scratching the surface. There are so many

1221
01:12:46,920 --> 01:12:49,599
Speaker 1: more potential applications and I'm sure I'm going to visit

1222
01:12:49,680 --> 01:12:52,559
Speaker 1: this topic again in future episodes to explore some of them.

1223
01:12:52,920 --> 01:12:55,879
Speaker 1: If you can't tell I'm really interested in this subject

1224
01:12:55,920 --> 01:12:59,120
Speaker 1: because it opens up new possibilities to interact with technology,

1225
01:12:59,360 --> 01:13:02,959
Speaker 1: will similtaneously giving us the chance to learn more about ourselves,

1226
01:13:03,000 --> 01:13:05,800
Speaker 1: and I kind of dig that. Before I sign off,

1227
01:13:06,120 --> 01:13:08,640
Speaker 1: I have an exciting announcement to make. I have a

1228
01:13:08,800 --> 01:13:13,080
Speaker 1: new podcast launching. It's called tech Stuff Daily, and as

1229
01:13:13,200 --> 01:13:17,360
Speaker 1: the name applies, it will be all about technology and

1230
01:13:17,520 --> 01:13:19,680
Speaker 1: it's also going to publish every day. That's that's what

1231
01:13:19,800 --> 01:13:22,680
Speaker 1: the daily part means every day Monday through Friday, and

1232
01:13:22,760 --> 01:13:25,639
Speaker 1: each episode will be between four and six minutes long,

1233
01:13:26,320 --> 01:13:29,360
Speaker 1: give or take, and we'll explore a tech topic that's

1234
01:13:29,400 --> 01:13:32,519
Speaker 1: been rambling around in the news cycle. This is not

1235
01:13:32,760 --> 01:13:36,160
Speaker 1: replacing Text Stuff. That show is still going to be

1236
01:13:36,240 --> 01:13:39,240
Speaker 1: publishing twice a week as always. It's going to exist

1237
01:13:39,320 --> 01:13:41,760
Speaker 1: side by side, but now you'll get even more tech

1238
01:13:41,920 --> 01:13:45,760
Speaker 1: goodness by subscribing to tech Stuff Daily. Now, in my

1239
01:13:45,880 --> 01:13:48,720
Speaker 1: next episode, i'll chat a bit more about using eye

1240
01:13:48,800 --> 01:13:52,800
Speaker 1: tracking technology specifically in the realm of e sports, as

1241
01:13:52,880 --> 01:13:55,680
Speaker 1: well as a discussion about the sports in general. I

1242
01:13:55,800 --> 01:13:57,880
Speaker 1: look forward to chatting with you guys about it, and

1243
01:13:57,960 --> 01:14:00,519
Speaker 1: if you have suggestions for future episodes of Text Stuff,

1244
01:14:00,720 --> 01:14:03,240
Speaker 1: please let me know you can write me at tech

1245
01:14:03,320 --> 01:14:06,519
Speaker 1: Stuff at how stuff works dot com, or drop me

1246
01:14:06,600 --> 01:14:09,400
Speaker 1: a line on Facebook or Twitter. The show's handle is

1247
01:14:09,479 --> 01:14:13,719
Speaker 1: tech Stuff h SW. Remember I record new episodes every

1248
01:14:13,800 --> 01:14:16,559
Speaker 1: Wednesday and Friday, and you can watch me record them

1249
01:14:16,720 --> 01:14:20,719
Speaker 1: live at twitch dot tv slash tech Stuff. Just visit

1250
01:14:20,800 --> 01:14:23,200
Speaker 1: that you r L. You'll find the schedule there and

1251
01:14:23,280 --> 01:14:32,479
Speaker 1: I'll talk to you again really soon for more on

1252
01:14:32,560 --> 01:14:35,320
Speaker 1: this and thousands of other topics because it staff works

1253
01:14:35,360 --> 01:14:35,720
Speaker 1: dot com.