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Speaker 1: Get in touch with technology with tech Stuff from how

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Speaker 1: stuff works dot com. Hello everyone, and welcome to tech stuff.

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Speaker 1: My name is Chris Poulette and I am an editor

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Speaker 1: at how stuff works dot com. Sitting across from me,

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Speaker 1: as he typically does on these days, is senior writer

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Speaker 1: Jonathan Strickland. He there. Yeah, so we were we were

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Speaker 1: going to share some twisted logic with you today. Yes,

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Speaker 1: we wanted to talk about dioxy ribonucleic acid computers. DONA

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Speaker 1: is the DONA No, no no, the DONA NA d n

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Speaker 1: A computers And what is a DNA computer? What would

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Speaker 1: it be? Because we're really in the very early stages

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Speaker 1: of using DNA for the reasons of uh purposes of

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Speaker 1: a computer. But what would a DNA computer be? Why

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Speaker 1: would we even use DNA? And what the heck is

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Speaker 1: this DNA stuff? Anyway, Well, you know, I've got a

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Speaker 1: USB port in the back of my head. So yeah.

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Speaker 1: He also woke up one day and he was in

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Speaker 1: a giant battery and he had to get down. Turns

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Speaker 1: out Chris is the one, and definitely we got but this,

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Speaker 1: you know, we got agents Smith showing up every other

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Speaker 1: day at the office and we're like, he's not here,

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Speaker 1: today's teleworking and us just irritating. But anyways, in the

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Speaker 1: matrix DNA, so DNA is is is important stuff. I mean,

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Speaker 1: this is a molecule that contains information that you know, collectively,

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Speaker 1: this information makes makes organisms what they are. Yes, and

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Speaker 1: uh and so biologically DNA is used to store information

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Speaker 1: and that is really the key there, you know, saying,

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Speaker 1: wait a minute, if DNA stores information for organisms, could

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Speaker 1: we use DNA to store information for other purposes? But

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Speaker 1: to to really explain this, DNA, it's this, it's it's

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Speaker 1: that double helix molecule. You're probcing, Uh, you know, illustrations

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Speaker 1: of it. You may have built a model of it.

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Speaker 1: If you are in school, you may be studying this

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Speaker 1: so much that the terms I'm going to use you're thinking, wow,

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Speaker 1: he's really glossing over this. But it's because this is

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Speaker 1: tech stuff, not stuff to blow your mind. So we're

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Speaker 1: not going to go too deep into the cellular biology

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Speaker 1: aspect of DNA. Yes, And if you're looking for your

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Speaker 1: mind being blown, I'm sorry you've come to the wrong place.

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Speaker 1: Right now, DNA has a has a lot of instructions

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Speaker 1: in it. Yes, As it turns out, it's a very

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Speaker 1: tiny molecule with UH, with a very large capacity for

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Speaker 1: for carrying information. Yeah, if you were to actually stretch

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Speaker 1: out a DNA molecule and lay it lengthwise, it would

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Speaker 1: end up taking much more space than it typically does

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Speaker 1: because it has this twisted three dimensional uh uh structure.

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Speaker 1: Hence my earlier dumb joke. Right, So this twisted structure

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Speaker 1: actually allows this this very dense UH storage medium to

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Speaker 1: exist in a relatively small volume of space. Yeah, because

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Speaker 1: you've twisted it. And you know, it's the whole thing

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Speaker 1: about UH conserving surface area and all that great stuff

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Speaker 1: that all my biologist friends go on and on and

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Speaker 1: on about and then I end up wandering away. Um.

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Speaker 1: But DNA has UH among many other attributes. There are

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Speaker 1: pairs of bases that that pair up in DNA, and

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Speaker 1: this is you know, the the structure of those The

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Speaker 1: sequence of those determines what information is stored in that

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Speaker 1: strand of DNA. Okay, So those four bases you have

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Speaker 1: at Anne, Citazine, Guani, and thyming and usually we just

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Speaker 1: call those A, C, G and T. And the way

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Speaker 1: that those are sequenced, like I said, within a strand

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Speaker 1: of DNA determines the type of information that that DNA holds.

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Speaker 1: Uh and uh, it's it's it's that that forms the

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Speaker 1: basis of the idea of using a DNA computer because

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Speaker 1: in our of course, in our our classic computer model,

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Speaker 1: we've got computers thinking quote unquote thinking in binary right,

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Speaker 1: zeros and ones and so uh. With using DNA. UH,

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Speaker 1: the approach right now is to associate certain of those

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Speaker 1: bases with zeros and the others with ones, and the

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Speaker 1: idea being that way you could sequence a DNA down

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Speaker 1: the length of a strand of DNA with these zeros

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Speaker 1: and ones. You encode a strand of DNA that way,

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Speaker 1: and then you would decode it. You would read back

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Speaker 1: those those base pairings and that would determine whether each

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Speaker 1: pair was a zero or a one, and then you

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Speaker 1: would decode that into binary language, and thus you would

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Speaker 1: get back to whatever information you originally stored onto the DNA. UM.

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Speaker 1: This is it makes it sound pretty simple, but this

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Speaker 1: is high tech science stuff right now. Now. Granted, it's

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Speaker 1: high tech science stuff that we have made huge advances

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Speaker 1: in over the last two decades. Really, so things that

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Speaker 1: were seen as practically impossible two decades ago are things

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Speaker 1: that we do almost not quite routinely, but with a

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Speaker 1: greater ease than we could have expected. Yeah, but over

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Speaker 1: the course of of the last few decades. Um, it's

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Speaker 1: the kind of thing that when people see the double helix,

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Speaker 1: it's familiar. Um, you know, it's it's it's it's high

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Speaker 1: tech science. But it's in our public consciousness too, it's

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Speaker 1: in our DNA. There you go the fact that that

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Speaker 1: that's a a uh slang term, you know, for something.

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Speaker 1: When you say it's, it's basically you're saying it's deeply

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Speaker 1: ingrained in your personality or whatever you're saying that about. Um,

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Speaker 1: you know, it's it's certainly something that that we're all

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Speaker 1: familiar with now, but only a few decades ago, you know,

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Speaker 1: it was completely foreign to us. Yeah. So yeah, let's

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Speaker 1: we'll do a quick, quick rundown of the history of

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Speaker 1: our knowledge about DNA, because clearly DNA has existed for

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Speaker 1: millions of years, but we've only really been aware of

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Speaker 1: it since about well, we knew something about it back

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Speaker 1: in eighteen sixty. Yes, when Freedrich Meischer, who was thank

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Speaker 1: you was he was a biologist from Switzerland and he

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Speaker 1: was looking at something pretty darn gross. He was looking

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Speaker 1: at bandages that had pus on them, and he isolated

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Speaker 1: DNA from the pus on the bandages, and he thought

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Speaker 1: that perhaps the this stuff that these nucleic acids, which

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Speaker 1: is DNA, is a nucleic acid. He thought that perhaps

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Speaker 1: this stuff might contain information in it that would determine

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Speaker 1: why stuff is the way it is so genetic information.

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Speaker 1: He thought that that probably did contain that information, but

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Speaker 1: there was no way for him to be able to

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Speaker 1: confirm it. He could not point to anything and say, see,

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Speaker 1: I'm right, So that had to wait for future scientists

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Speaker 1: to uh, to really dive into it, not not the

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Speaker 1: pus that big gross, but to really dive into the

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Speaker 1: information and study it and and figure out more details.

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Speaker 1: So Intree, some scientists at Rockefeller University, including Oswald Avery,

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Speaker 1: showed that DNA taken from a bacterium could make a

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Speaker 1: non infectious type of bacteria become infectious bacteria. So the

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Speaker 1: thought was that there must be some information from this

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Speaker 1: nucleic acid taken from one type of bacteria that could

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Speaker 1: transfer properties to a different bacteria that otherwise would not

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Speaker 1: have that infectious property. But what does it? Yes, that's

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Speaker 1: kind of what everyone was saying. Well, there's some sort

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Speaker 1: of information holding material here. We don't really understand the

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Speaker 1: mechanism by which it stores information, nor how does it

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Speaker 1: impart that information or or replicated. We didn't know that

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Speaker 1: at the time. Uh. And then in nineteen fifty two,

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Speaker 1: Alfred Hershey and Martha Chase showed that to make new

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Speaker 1: viruses bacteria fage virus injected DNA into the host cell,

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Speaker 1: which was important because previously it was thought that perhaps

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Speaker 1: it was through protein exchange, but instead of protein exchange,

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Speaker 1: it was DNA exchange. So that showed, yes, there's something

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Speaker 1: in this. This d N A is what is important.

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Speaker 1: And then came along Watson and Crick, Yes, James D.

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Speaker 1: Watson and Francis Crick. Yeah. They it was clear that, uh,

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Speaker 1: that people were already onto something. Hershey and Chase had

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Speaker 1: something there. And it was only a year later when

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Speaker 1: Watson and Crick, uh you know, made their announcement they

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Speaker 1: had discovered the structure of DNA, right, and so this

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Speaker 1: is when we started to really learn what how DNA

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Speaker 1: you know, forums and what shape it takes and why

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Speaker 1: that's important. And um so once all of that was taken,

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Speaker 1: once we learned all that, we began to see that

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Speaker 1: these base pairings I was talking about, we learned that

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Speaker 1: they pair in very specific ways. You know, I mentioned

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Speaker 1: there are the four different bases. There's A, the A, C, G, T. Well,

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Speaker 1: half of those A and G are called purines. Uh,

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Speaker 1: C and T are uh perimidines. I'm glad you took

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Speaker 1: that part. Yeah me too, Uh, you know, way back

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Speaker 1: when I was actually really good at biology. But man,

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Speaker 1: that was a few decades ago. So anyway of perings

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Speaker 1: and peri peri pyrimidines. Look, I can't even do it now,

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Speaker 1: periings of paramidines. Still glad you took that bond together, right, So, uh,

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Speaker 1: you don't get too purines bonding together, and don't get

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Speaker 1: two pyramidines bonding together. And to be even more specific,

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Speaker 1: A and T will bond together, and C and G

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Speaker 1: will bond together. All right, So that that means that

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Speaker 1: you know, you can't you're not going to get a

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Speaker 1: strand of DNA where A and C or A and

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Speaker 1: G are paired together. It does not happen. They structurally,

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Speaker 1: that doesn't happen. So uh that also dictates the rationale

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Speaker 1: behind using uh these pairings as zeros and ones because

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Speaker 1: you can either have UH. You can either have the

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Speaker 1: A T pairing or the C G pairing, right, so

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Speaker 1: that that lets you say, okay, well that's binary. It's

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Speaker 1: either you you just designate that one means one, pairing

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Speaker 1: means zero, the other pairing means one. Um, if it

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Speaker 1: weren't that case, if we could have multiple pairing, multiple uh,

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Speaker 1: like like if A could pair with G instead of

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Speaker 1: just A and T, then you would say, all right, well,

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Speaker 1: now we've got system that goes beyond binary, which in theory,

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Speaker 1: if you completely change the way computers work, would mean

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Speaker 1: that you could dramatically increase parallel processing because you could

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Speaker 1: designate things. It would almost be like the cubits of

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Speaker 1: a quantum computer, where you know, the basic explanation is

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Speaker 1: a cubit represents both a zero and a one and

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Speaker 1: all values in between in superposition of one another, and

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Speaker 1: that if you have enough cubits you can perform a

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Speaker 1: massive parallel processing problem all at the same time because

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Speaker 1: those that that one group of cubits is behaving as

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Speaker 1: if it's uh, you know a huge number of traditional bits.

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Speaker 1: I think it's important to remember too that no matter

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Speaker 1: how many bases DNA has they all belong to us.

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Speaker 1: I knew it. I knew it. I was like, oh,

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Speaker 1: I was going to do an all your base I

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Speaker 1: belonged to us. If someone set us up the bomb

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Speaker 1: so well, it could be Actually, if you if you

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Speaker 1: were trying to if those pairs become corrupted, they will

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Speaker 1: not work and uh and a cell can die. Actually,

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Speaker 1: we're getting a lot of this information to from our

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Speaker 1: our excellent article on how stuff works dot com about

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Speaker 1: how DNA works. It gets into a whole lot more detailed, right, Yeah,

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Speaker 1: if you want to learn more about and and it's

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Speaker 1: very accessible. It's a very accessible article. So if you're

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Speaker 1: curious about you know, you've always heard about d N

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Speaker 1: A and you've heard about DNA testing, and you know

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Speaker 1: about chromosomes and genes, but you're not really you know,

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Speaker 1: beyond that, you're kind of confused. I highly recommend you

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Speaker 1: read how DNA works at how stuff works dot com.

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Speaker 1: We also have an article on how DNA computers work,

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Speaker 1: which is pretty interesting because it's talking about an earlier

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Speaker 1: era of DNA computers, but recent developments have really brought

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Speaker 1: it brought to lights some interesting uh, new technologies and

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Speaker 1: new use cases for d N a and we'll get

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Speaker 1: into those in a second. It's it's funny that you

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Speaker 1: say that, because I'm sure that people this is futuristic

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Speaker 1: enough where people are saying, what are you talking about

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Speaker 1: new developments? We haven't heard of a d N A

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Speaker 1: computer before? But yeah, that's that's not really surprising. This

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Speaker 1: is the kind of thing, like like quantum computing, where

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Speaker 1: they've been working on it for some time, but it's

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Speaker 1: not at a point where they can really you know,

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Speaker 1: put something on a shelf and go look at this. Yeah,

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Speaker 1: where people really take notice of it. In general, this

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Speaker 1: is all stuff that's taking place in universities and research facilities,

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Speaker 1: and it's you know, most of these machines that are

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Speaker 1: being made now or or these implementations of using DNA

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Speaker 1: for information digital information are really in the prototype stage.

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Speaker 1: But we're getting the technology that allows us to create

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Speaker 1: these machines is becoming more and more sophisticated and less expensive,

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Speaker 1: which of course is key. It's huge any new Gordon

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Speaker 1: Moore explained that back in and when he did his

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Speaker 1: his paper about cramming more components onto an integrated circuit.

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Speaker 1: His point was not just that technology was advancing to

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Speaker 1: a point where we could shrink stuff down and fit

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Speaker 1: twice as many components onto a square inch of silicon

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Speaker 1: as we could a year ago. It was also that

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Speaker 1: the manufacturing process was becoming efficient enough and cheap enough

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Speaker 1: where that made sense. So same sort of thing here. Well,

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Speaker 1: all right, so we've we've determined that DNA contains information.

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Speaker 1: It because of its very structure, it can contain a

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Speaker 1: lot of information in a small volume. Uh. And then

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Speaker 1: it wasn't until about nine four, and I remember it

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Speaker 1: was the it was the fifties, the early fifties when

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Speaker 1: we started to really understand what DNA was and how

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Speaker 1: how it formed and how and its structured and everything

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Speaker 1: like that. In ninety four, a man named Leonard Edelman

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Speaker 1: came up with this idea. He sort of, uh introduced

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Speaker 1: the idea of using DNA to solve math problems. And

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Speaker 1: it was essentially this idea of coding DNA as if

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Speaker 1: it were a strip of binary code. And so he

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Speaker 1: took this idea and he sort of ran with it.

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Speaker 1: He began to formulate an idea about how to how

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Speaker 1: to create an experiment that could show that this would work.

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Speaker 1: And it's funny because it's talking about a DNA computer.

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Speaker 1: But if you read about the experiment, it sounds more

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Speaker 1: like someone in a chemistry lab mixing various chemical compositions

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Speaker 1: together and then coming up with a solution at the

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Speaker 1: end of it. And that's it turns out that this

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Speaker 1: is a computational solution, not just a chemical solution. I

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Speaker 1: see what you did there, little word play there. Yeah,

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Speaker 1: it's a little a little incredible. So he yeah, he um,

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Speaker 1: dissolved my objections. So wait, let me read. I'll read

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Speaker 1: the steps from our article on DNA computers, because I

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Speaker 1: want to explain how this early early early implementation of

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Speaker 1: a DNA computer, how it how it played out, and

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Speaker 1: it's kind of amazing. All right. Here are the steps.

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Speaker 1: Number one strands of DNA represent the seven cities. Now

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Speaker 1: when it says seven cities in here, what he was

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Speaker 1: doing was he was trying to solve something called the

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Speaker 1: traveling salesman problem, also the directed Hamilton's path problem. The

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Speaker 1: idea being that you're supposed to find the shortest route

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Speaker 1: between a group of cities, and and it could be

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Speaker 1: any number really of cities, but you have to only

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Speaker 1: go through each city one time. Um, and it becomes

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Speaker 1: more complex. This is this is why this is such

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Speaker 1: a fascinating problem. Uh As Jonathan pointed out to me

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Speaker 1: right before, he reminded me that this is something that

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Speaker 1: quantum computing is fascinated with because this is such a

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Speaker 1: I don't know what you call it, thorny, a thorny problem.

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Speaker 1: So it was that problem that they were were that

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Speaker 1: he wanted to work on, and he chose, I believe

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Speaker 1: seven in cities, he said that as his benchmark I

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Speaker 1: wanted to do. And see, this is this is an

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Speaker 1: interesting problem for h in computers because think about it,

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Speaker 1: You've got seven cities. You can only travel through each

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Speaker 1: city once. You have to find the most efficient pathway

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Speaker 1: to go. Well, the way a computer would do this,

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Speaker 1: generally speaking, is to start going through every single possible

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Speaker 1: um permutation of that trip, going from city to city,

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Speaker 1: and determining which of those is the most efficient by

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Speaker 1: the end of it by comparing them all, which can

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Speaker 1: take ages and as as of course, as you add

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Speaker 1: more cities, as you add complexity to the problem, it

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Speaker 1: creates an exponentially more difficult problem for the computer to solve.

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Speaker 1: You know, I don't think it's that unlike trying to

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Speaker 1: crack a password. In the in the you know, other

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Speaker 1: references we've made to these again, parallel processing. That's another

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Speaker 1: reason why quantum computers are very scary for anyone who's

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Speaker 1: in cryptography who wants to create good encryption, because they're

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Speaker 1: about using parallel processing to attack, you know, do a

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Speaker 1: brute force attack on a password. You can really reduce

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Speaker 1: the amount of time it would take you to crack

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Speaker 1: a password, like a password that would probably take you

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Speaker 1: thousands of years in classic computer time might only take

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Speaker 1: an hour in using a quantum computer because it's using

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Speaker 1: that parallel approach. So just remember, quantum computing is the

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Speaker 1: cure for the common code. Man, what is it with

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Speaker 1: you today? Chris is in a mood folks anyway, Alright,

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Speaker 1: so like getting back to getting back to this thing,

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Speaker 1: this this set of steps, all right. So Aedelman creates

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Speaker 1: strands of DNA that represent the seven cities. Uh, and

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Speaker 1: so it's these A, T, and CG pairings and then um,

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Speaker 1: these various sequences represent each city and possible flight path.

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Speaker 1: He then took the molecules that these strands of DNA

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Speaker 1: A and mixed them in a test tube, and some

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Speaker 1: of the strands of DNA stuck together in a chain

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Speaker 1: of those strands represented a potential answer to that question,

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Speaker 1: which of these you know, which route is the most efficient.

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Speaker 1: Within a few seconds, all of the possible combinations of

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Speaker 1: DNA strands were created in the test tube, and then

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Speaker 1: Edelman eliminated the wrong molecules through chemical reactions, which left

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Speaker 1: behind only the flight paths that connect all seven cities.

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Speaker 1: So here he was doing chemistry and looking at molecules

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Speaker 1: by uh it was and it was biological chemistry because

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Speaker 1: he was using organic DNA um and and trying to

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Speaker 1: come up with the answer that way, which is pretty

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Speaker 1: interesting to me. I mean, it looks that sounds so

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Speaker 1: different from the way we think of computing today, where

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Speaker 1: you're using microprocessors and you know, a user interface looking

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Speaker 1: at screen. This guy is using test tubes and molecules

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Speaker 1: um and he was actually thinking at the time that

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Speaker 1: this would be DNA computing is going to be the

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Speaker 1: future because it packs so much information in such a

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Speaker 1: small form factor and it's plentiful because there's a lot

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Speaker 1: of life out there, and organic life relies on DNA heavily.

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Speaker 1: There's some that rely on RNA, but we're not going

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Speaker 1: to go into that. But Anyway, a great amount of

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Speaker 1: organic life out there has lots and lots of DNA,

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Speaker 1: so that we've got plenty of materials to work from. Uh.

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Speaker 1: What's interesting is that since that time where his first

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Speaker 1: experiments were showing the viability of a DNA computer, our

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Speaker 1: ability to sequence synthetic DNA has improved to the point

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Speaker 1: where organic DNA is not really what we care about anymore.

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Speaker 1: We can synthesize DNA in the lab and just make

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Speaker 1: it ourselves so we don't have to um harvest it.

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Speaker 1: As Chris was saying in the pre show, you know,

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Speaker 1: it would be a totally different world if you realize

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Speaker 1: that your computer was running out a memory, so you

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Speaker 1: chucked another hamster into your machine so that you could

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Speaker 1: finish whatever it was you were doing. That was a

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Speaker 1: particularly gory idea. Well we didn't, but yeah, I left

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Speaker 1: out the part about the grinding noises, you know, and

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Speaker 1: for flying out the back you yeah, yeah, And I

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Speaker 1: thought that was my contribution. Um yeah. They University of Rochester.

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Speaker 1: There were some researchers that found ways to use DNA

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Speaker 1: to create logic gates. Again in the n it looks

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Speaker 1: like um so uh, and that's we've touched on on

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Speaker 1: several occasions, but that those logic gates are basically key

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Speaker 1: to classic computing. Yeah, this is what, uh, this is.

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Speaker 1: This is what allows the computer to dictate how information

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Speaker 1: moves through it so that it has any meaning. You know.

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Speaker 1: The logic gates essentially dictate whether the zero or one

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Speaker 1: that goes into the gate comes out at zero or

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Speaker 1: one on the other side or something. Usually it's a pair.

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Speaker 1: If it's a zero and a one on the other

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Speaker 1: side of the gate, is that going to be a

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Speaker 1: one or zero? And it all depends on the type

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Speaker 1: of gate it is. UM And of course you you

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Speaker 1: can link a bunch of gates together to create all

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Speaker 1: sorts of different outcomes depending upon what the input is.

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Speaker 1: This is all very important from classical computing. So getting

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Speaker 1: to that step of being able to build logic gates

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Speaker 1: out of DNA it was pivotal if you want to

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Speaker 1: be able to eventually build a true DNA computer. And

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Speaker 1: again this is you know, you compare the components of

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Speaker 1: a DNA computer to those of a an inorganic computer. UM,

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Speaker 1: and we have, as a Jonathan pointed out, and Gordon

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Speaker 1: Moore's uh famous prediction that the transistors would double in

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Speaker 1: number per square inch of elicon. Back in the original prediction, UM,

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Speaker 1: you know every you know over a certain period of time,

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Speaker 1: which again has changed, you know, year, year and a half,

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Speaker 1: two years. The thing is, Um, we're talking about a

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Speaker 1: flat piece of silicon. And we've also talked about how

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Speaker 1: hard drives. The classical hard drive, UM, you know has

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Speaker 1: so much information on it. It's in a it's in

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Speaker 1: a flat plane. We've talked about electronic memory and how

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Speaker 1: you know this information is is getting stored, but we've

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Speaker 1: basically been talking two dimensional and and a long time

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Speaker 1: ago we talked about processors and how at some point,

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Speaker 1: due to the limitations of physics, like it's at some

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Speaker 1: point electrons will begin to tunnel through layers of the

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Speaker 1: material used to create transistors, basically making them ineffective. So

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Speaker 1: at some point, theoretically the traditional transistor chip is going

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Speaker 1: to be so full that you cannot fill it anymore

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Speaker 1: without having syria. It's electrical problems. So they were talking

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Speaker 1: about going into three D processors. Well, d n a

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Speaker 1: kind of goes around that problem or is a natural

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Speaker 1: if you will solution. Hey, for once, that wasn't a

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Speaker 1: pun intended UM, because DNA is volumetric. It isn't It

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Speaker 1: can fit because of its its natural characteristics. It doesn't

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Speaker 1: have to be in a two dimensional flat shape. You

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Speaker 1: don't have to stretch out the helix and stick it

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Speaker 1: on a piece of silicon or whatever to make it work. Um,

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Speaker 1: and that gives uh, that gives computing so much more

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Speaker 1: advantage to move to a DNA based existence, right. Yeah.

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Speaker 1: The the challenge is building eloquently. The challenge is building

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Speaker 1: the equipment that allows you to sequence and decode that information,

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Speaker 1: because you know that's where that's where the bottleneck is

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Speaker 1: right now, is that the It's not simple. Yeah, you

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Speaker 1: have to get there. Yeah. But once we get to

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Speaker 1: a point where we're able to construct the DNA and

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Speaker 1: lay it out in such a way we were able

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Speaker 1: to pack in all that information, and then we have

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Speaker 1: the companion devices that can decode that and make it

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Speaker 1: meaningful to a computer again, then you're talking about some

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Speaker 1: huge leaps in storage capacity. One gram of d N

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Speaker 1: a can store up to four hundred and fifty five

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Speaker 1: billion gigabytes of data, which is about a hundred billion

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Speaker 1: DVDs worth of information. Yea, yea. As a matter of fact,

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Speaker 1: this is the article that sort of uh turned me

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Speaker 1: onto this idea was something that my friends Kim and

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Speaker 1: Tim pointed out to me in the in the Guardian,

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Speaker 1: which really wasn't that long ago August two thousand twelve.

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Speaker 1: They started talking about how books had been encoded in

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Speaker 1: DNA um and that that got me to thinking and

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Speaker 1: to suggesting this to Jonathan is a potential topic because

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Speaker 1: it's it's fascinating that d N a, something so small,

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Speaker 1: can hold that much information. And it's funny because the

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Speaker 1: story goes it talks about how Professor George Church lead

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Speaker 1: this project and he belongs to UM. He well, he

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Speaker 1: teaches it. He teaches at Havid. But not just Harvard,

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Speaker 1: it's Harvard Medical School. This is this is one of

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Speaker 1: those weird things, uh that this this overlaps science, computer

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Speaker 1: science and h medicine. Yeah, and medicine. Yeah, so you've

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Speaker 1: got I'm sorry, physical science and medical science. Let's say

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00:27:42,480 --> 00:27:46,080
Speaker 1: that right. That that's that's fine. That's a computer science

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Speaker 1: and and medical science. It's it's multidisciplinary obviously, just like

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Speaker 1: nanobiology or nanotechnology is a multidisciplinary approach. So is this

430
00:27:57,359 --> 00:28:03,360
Speaker 1: DNA computer or DNA storage idea. So what what Professor

431
00:28:03,480 --> 00:28:08,560
Speaker 1: Church did was they decided to take a book that

432
00:28:09,480 --> 00:28:14,919
Speaker 1: was about five point to seven megabits of digital space

433
00:28:15,119 --> 00:28:20,600
Speaker 1: once you converted into digital information, and to encode that

434
00:28:21,119 --> 00:28:26,000
Speaker 1: as DNA. And um. They didn't do it just once.

435
00:28:27,440 --> 00:28:33,120
Speaker 1: They decided to duplicate it a few times, seven seventy

436
00:28:33,200 --> 00:28:39,440
Speaker 1: billion times, seventy billion copies of this book, which, according

437
00:28:39,560 --> 00:28:43,000
Speaker 1: to an article in Extreme Tech, prompted them to joke

438
00:28:43,120 --> 00:28:45,720
Speaker 1: that it made it the best selling book of all time, yes,

439
00:28:46,600 --> 00:28:50,080
Speaker 1: and that it was. The seventy billion copies totaled about

440
00:28:50,280 --> 00:28:55,960
Speaker 1: forty four peda bytes of data. Um, so that is

441
00:28:56,040 --> 00:28:58,960
Speaker 1: slightly larger than the n A S I have attached

442
00:28:59,040 --> 00:29:01,960
Speaker 1: at my network at home. Yeah. Yeah, forty four pedo bites.

443
00:29:02,080 --> 00:29:05,880
Speaker 1: That's an incredible amount of information. It's also quite a

444
00:29:05,960 --> 00:29:10,160
Speaker 1: bit smaller my NA s. Yeah. So so when you

445
00:29:10,240 --> 00:29:15,800
Speaker 1: think about it, the the promise of DNA is that

446
00:29:16,400 --> 00:29:21,200
Speaker 1: with a relatively small amount of DNA you could store

447
00:29:21,520 --> 00:29:25,240
Speaker 1: the sum total of all human knowledge in a very

448
00:29:26,000 --> 00:29:31,880
Speaker 1: tiny compartment, relatively speaking, a tiny compartment. And um, if

449
00:29:31,920 --> 00:29:36,280
Speaker 1: you're able to use that same sort of uh of

450
00:29:36,520 --> 00:29:41,560
Speaker 1: capacity in a processing way as opposed to just storage

451
00:29:41,600 --> 00:29:45,760
Speaker 1: storage is great. I mean, that's fantastic, The the the Uh,

452
00:29:46,040 --> 00:29:50,440
Speaker 1: this project was really showing how using DNA is great

453
00:29:50,480 --> 00:29:54,520
Speaker 1: for archival purposes if you want to store information for

454
00:29:54,720 --> 00:29:59,000
Speaker 1: longevity sake. And another point about that is that I

455
00:29:59,080 --> 00:30:01,760
Speaker 1: love this, Yeah, is that here's here's an issue that

456
00:30:01,880 --> 00:30:06,560
Speaker 1: we have with storing information. The way we access information

457
00:30:06,760 --> 00:30:11,200
Speaker 1: changes over time, and some of the they're they're multiple

458
00:30:11,240 --> 00:30:14,680
Speaker 1: problems here. Sometimes the way we store information, uh, we

459
00:30:14,800 --> 00:30:19,040
Speaker 1: store it on a medium that can decompose, which means

460
00:30:19,120 --> 00:30:23,800
Speaker 1: that as time passes, the likelihood that that data is

461
00:30:23,880 --> 00:30:28,920
Speaker 1: intact decreases. So let's say like a book. Okay, books

462
00:30:29,000 --> 00:30:33,320
Speaker 1: are susceptible to lots of different environmental factors that can

463
00:30:33,800 --> 00:30:37,560
Speaker 1: make them impossible to read. Right, So as time goes by,

464
00:30:38,160 --> 00:30:43,280
Speaker 1: a book's ability to preserve that information decreases, particularly depending

465
00:30:43,360 --> 00:30:46,040
Speaker 1: upon its environment. Yeah. And and one of the things

466
00:30:46,120 --> 00:30:49,800
Speaker 1: that's funny to me about this is and I'll keep

467
00:30:49,880 --> 00:30:52,120
Speaker 1: this short, but it's it's funny to me that in

468
00:30:52,240 --> 00:30:57,880
Speaker 1: a way, uh, the increase in technology um has only

469
00:30:58,600 --> 00:31:01,040
Speaker 1: increased the rate of data right as some people call it,

470
00:31:01,120 --> 00:31:04,240
Speaker 1: Because you think about something like the Rosetta stone and

471
00:31:04,360 --> 00:31:07,920
Speaker 1: how long ago that was chiseled but it's still there

472
00:31:08,040 --> 00:31:10,720
Speaker 1: because hey, you know it's stone. If now, if you

473
00:31:10,840 --> 00:31:13,560
Speaker 1: left it out in the elements, eventually the the writing

474
00:31:13,640 --> 00:31:16,440
Speaker 1: on it will wear away due to the effects of erosion.

475
00:31:16,560 --> 00:31:20,520
Speaker 1: But um, that's longer lived than say paper, which could

476
00:31:20,560 --> 00:31:24,640
Speaker 1: be eaten by weevils, or could be affected by mold

477
00:31:24,720 --> 00:31:28,440
Speaker 1: or mildew or or even water or fire. Um. You

478
00:31:28,520 --> 00:31:31,239
Speaker 1: know there there are many things acid in the paper. Um.

479
00:31:31,480 --> 00:31:34,280
Speaker 1: But but that would be longer lived than say, um,

480
00:31:34,760 --> 00:31:38,120
Speaker 1: a magnetic storage medium, which might may only live a

481
00:31:38,200 --> 00:31:42,920
Speaker 1: few decades because you've got with magnetic storage, Eventually that

482
00:31:43,360 --> 00:31:46,960
Speaker 1: magnetic properties starts to kind of and I have that

483
00:31:47,400 --> 00:31:50,960
Speaker 1: cop yeah, and I've had CDs and DVDs that I've

484
00:31:51,040 --> 00:31:54,400
Speaker 1: burned and a few years ago that are starting to

485
00:31:54,640 --> 00:31:59,160
Speaker 1: show signs of deterioration. And I'm thinking all this futuristic stuff,

486
00:31:59,160 --> 00:32:01,240
Speaker 1: it's kind of funny. This uff that's chiseled in stone

487
00:32:01,320 --> 00:32:03,200
Speaker 1: is still there. Well. And on top of all that,

488
00:32:03,880 --> 00:32:06,480
Speaker 1: besides the fact that you've got these media, these media

489
00:32:06,640 --> 00:32:11,960
Speaker 1: that will that can degrade over time. Um, magnetic definitely

490
00:32:12,280 --> 00:32:14,800
Speaker 1: is more susceptible that I would say, than optical storage.

491
00:32:14,880 --> 00:32:18,480
Speaker 1: But but both can can degree and both are susceptible

492
00:32:18,560 --> 00:32:21,280
Speaker 1: to damage. I mean, just about everything is. But but

493
00:32:22,200 --> 00:32:26,960
Speaker 1: the other problem is that we move away from those

494
00:32:27,400 --> 00:32:30,520
Speaker 1: older forms of media and eventually we get to a

495
00:32:30,560 --> 00:32:34,000
Speaker 1: point where nothing we have can read what we used

496
00:32:34,040 --> 00:32:37,840
Speaker 1: to use, or if you do have something that can

497
00:32:37,880 --> 00:32:41,360
Speaker 1: read it, it's a legacy system. So like keeping old

498
00:32:41,440 --> 00:32:44,520
Speaker 1: computers around simply to read those documents, right, Like, like

499
00:32:44,600 --> 00:32:46,680
Speaker 1: anything that's on an old five and a quarter inch

500
00:32:46,760 --> 00:32:51,280
Speaker 1: diskette from the early days of the personal computer, you know,

501
00:32:51,600 --> 00:32:54,560
Speaker 1: and I still have something. I would wager that most

502
00:32:54,640 --> 00:32:59,400
Speaker 1: people do not have easy access to such a disk drive. Um,

503
00:33:00,040 --> 00:33:02,160
Speaker 1: you know, especially if you're just kind of an average

504
00:33:02,240 --> 00:33:03,760
Speaker 1: user and you've gone out and you're like, oh, I

505
00:33:03,840 --> 00:33:05,719
Speaker 1: want a new laptop. You go again. If you buy

506
00:33:05,760 --> 00:33:07,560
Speaker 1: a new laptop today, you might not even have an

507
00:33:07,600 --> 00:33:11,120
Speaker 1: optical drive, which means that there you could come across

508
00:33:11,320 --> 00:33:14,040
Speaker 1: records of information that you have no way of accessing

509
00:33:14,080 --> 00:33:17,800
Speaker 1: because you do not have the tech capable of accessing it. Well.

510
00:33:17,880 --> 00:33:22,120
Speaker 1: D n A is a basic building block of organic life,

511
00:33:23,240 --> 00:33:26,800
Speaker 1: and so the idea is that because it's something so basic,

512
00:33:27,520 --> 00:33:31,320
Speaker 1: we will always have the ability and assuming that you know,

513
00:33:31,480 --> 00:33:34,600
Speaker 1: we don't have some sort of post apocalyptic event, while

514
00:33:34,640 --> 00:33:38,320
Speaker 1: an apocalyptic event that then leads to post apocalyptic events. Um,

515
00:33:39,440 --> 00:33:41,640
Speaker 1: then we should be able to have equipment that can

516
00:33:41,720 --> 00:33:44,440
Speaker 1: read this same information. Hey, do you have the instructions

517
00:33:44,440 --> 00:33:46,080
Speaker 1: on how to read DNA? Yeah, I say it on

518
00:33:46,160 --> 00:33:51,600
Speaker 1: that magnetic now here in Atlanta were used to post

519
00:33:51,640 --> 00:33:54,720
Speaker 1: apocalyptic events because we've got zombies. Yes, you may have

520
00:33:54,800 --> 00:33:57,920
Speaker 1: seen if you've watched the documentary The Walking Dead TV.

521
00:33:58,320 --> 00:34:02,120
Speaker 1: So um, yeah. The the idea was that this will

522
00:34:02,600 --> 00:34:06,360
Speaker 1: d n A does not degrade over time. Well, it

523
00:34:06,520 --> 00:34:09,719
Speaker 1: takes a much longer time than something like a paper book, right,

524
00:34:09,880 --> 00:34:13,480
Speaker 1: So since you're not worried about degrading. I mean when

525
00:34:13,520 --> 00:34:16,680
Speaker 1: I say it doesn't degrade over time, we're talking generations here,

526
00:34:16,960 --> 00:34:20,800
Speaker 1: hundreds of thousands of years. So yes, I wouldn't know.

527
00:34:20,920 --> 00:34:25,880
Speaker 1: I haven't. Eventually it will degrade, but for the foreseeable

528
00:34:25,920 --> 00:34:29,000
Speaker 1: future it won't. Uh. It takes up far less space.

529
00:34:29,080 --> 00:34:31,359
Speaker 1: We don't have to worry so much about not being

530
00:34:31,440 --> 00:34:35,000
Speaker 1: able to access the information anymore because against the basic

531
00:34:35,040 --> 00:34:38,440
Speaker 1: building block, we will presumably be still be interested in

532
00:34:38,560 --> 00:34:42,640
Speaker 1: DNA in the future. Uh. In fact, it become increasingly

533
00:34:42,760 --> 00:34:46,279
Speaker 1: interested as we learn more about how to uh to

534
00:34:46,640 --> 00:34:50,279
Speaker 1: tweet DNA to do things like fight off illnesses and

535
00:34:50,640 --> 00:34:56,360
Speaker 1: and other scientific applications of that knowledge. So that was

536
00:34:56,480 --> 00:34:58,320
Speaker 1: kind of the whole point was that it's great for

537
00:34:58,440 --> 00:35:01,080
Speaker 1: archival and that reason it's gonna it's it's it's a

538
00:35:01,680 --> 00:35:06,239
Speaker 1: it's a more permanent solution in multiple ways. And UH,

539
00:35:06,880 --> 00:35:09,400
Speaker 1: that's really where the focus is on the recent articles

540
00:35:09,440 --> 00:35:12,160
Speaker 1: that we've been reading, although there's still obviously quite a

541
00:35:12,200 --> 00:35:14,960
Speaker 1: bit of development on the research and about building a

542
00:35:15,080 --> 00:35:20,319
Speaker 1: true DNA computer that would uh have an incredibly small

543
00:35:20,400 --> 00:35:24,480
Speaker 1: form factor. I mean, you're talking about uh DNA being

544
00:35:24,800 --> 00:35:27,960
Speaker 1: the size of a couple of atoms, and this is

545
00:35:28,920 --> 00:35:33,600
Speaker 1: some small stuff. I mean, we could theoretically have a

546
00:35:33,719 --> 00:35:39,640
Speaker 1: DNA computer capable of performing huge calculations and storing an

547
00:35:39,840 --> 00:35:42,400
Speaker 1: enormous amount of data in a tiny, tiny form factor.

548
00:35:43,360 --> 00:35:45,920
Speaker 1: It would be amazing if we could look into the future,

549
00:35:46,040 --> 00:35:48,920
Speaker 1: maybe I don't know, twenty fifty years something like that,

550
00:35:49,120 --> 00:35:52,960
Speaker 1: where perhaps we have reached the point where this technology

551
00:35:53,320 --> 00:35:57,719
Speaker 1: is viable and and reproducible and economic, where we could

552
00:35:57,800 --> 00:36:02,360
Speaker 1: see it in applications that actually the average consumer could access.

553
00:36:02,840 --> 00:36:05,640
Speaker 1: It wouldn't just be the realm of the scientific community

554
00:36:05,800 --> 00:36:08,640
Speaker 1: or the research community. It would also be within our

555
00:36:08,719 --> 00:36:10,600
Speaker 1: grasp because then can you imagine you can have a

556
00:36:10,680 --> 00:36:16,160
Speaker 1: smartphone that could literally contain all the data that we

557
00:36:16,320 --> 00:36:22,400
Speaker 1: have ever generated, ever since the dawn of man on

558
00:36:22,520 --> 00:36:24,680
Speaker 1: your phone. I was waiting for you to go all

559
00:36:24,719 --> 00:36:27,680
Speaker 1: the data. No, that was it, just all of all

560
00:36:27,719 --> 00:36:30,759
Speaker 1: the data, um well, all the data we have access to.

561
00:36:31,239 --> 00:36:36,200
Speaker 1: Um there there. It's astounding to think of something uh

562
00:36:36,520 --> 00:36:40,560
Speaker 1: so common that has been with us for so long

563
00:36:40,880 --> 00:36:46,120
Speaker 1: being an answer and a fairly easy answer to a

564
00:36:46,200 --> 00:36:47,839
Speaker 1: lot of these problems. I mean, like I said, it's

565
00:36:47,840 --> 00:36:50,440
Speaker 1: not easy to get there. But the idea is like

566
00:36:50,560 --> 00:36:53,239
Speaker 1: really just DNA. As it turns out, you know, they've

567
00:36:53,239 --> 00:36:56,880
Speaker 1: they've been using synthetic DNA to to run these experiments,

568
00:36:57,200 --> 00:37:01,000
Speaker 1: and there are some drawbacks. One of where is it

569
00:37:01,120 --> 00:37:03,879
Speaker 1: can't be rewritten. That is true. So once you write

570
00:37:03,920 --> 00:37:06,759
Speaker 1: that data, it's that's another reason why people are talking

571
00:37:06,760 --> 00:37:11,480
Speaker 1: about for archival purposes. Once you write the data, that's it. Now. Granted,

572
00:37:11,600 --> 00:37:14,759
Speaker 1: you're talking about a construct that's so small that you

573
00:37:14,840 --> 00:37:18,160
Speaker 1: could keep doing that indefinitely and not have to worry

574
00:37:18,200 --> 00:37:23,279
Speaker 1: about taking up too much space. But right now, right,

575
00:37:23,440 --> 00:37:26,239
Speaker 1: but but you know you can't you can't always think

576
00:37:26,320 --> 00:37:31,280
Speaker 1: that way, because someday that will catch up to you apparented.

577
00:37:31,360 --> 00:37:34,239
Speaker 1: That might be when we're actually saying, hey, hey, we

578
00:37:34,320 --> 00:37:35,880
Speaker 1: finally got a plan on how to get off this

579
00:37:36,080 --> 00:37:39,760
Speaker 1: rock because the sun's gonna swallow us up in another

580
00:37:39,840 --> 00:37:43,960
Speaker 1: million years. That that would never happen. By the way,

581
00:37:44,120 --> 00:37:46,480
Speaker 1: don't don't write into me and explain to me why

582
00:37:46,600 --> 00:37:49,000
Speaker 1: that would be ridiculous. I understand. I was just using

583
00:37:49,040 --> 00:37:51,960
Speaker 1: that as a an example. Well, and and the other

584
00:37:52,080 --> 00:37:55,880
Speaker 1: thing is, um, you know, And yes, I realized that

585
00:37:56,000 --> 00:37:59,600
Speaker 1: this is you know that you could destroy DNA, but

586
00:38:00,360 --> 00:38:05,120
Speaker 1: um thinking about that, the sensitive information can't be erased,

587
00:38:06,000 --> 00:38:09,759
Speaker 1: then you would need to keep up with your Let's

588
00:38:09,760 --> 00:38:12,040
Speaker 1: say you had a DNA drive like you have a

589
00:38:12,120 --> 00:38:15,440
Speaker 1: flash drive to carry back and forth with you, uh,

590
00:38:15,520 --> 00:38:18,400
Speaker 1: and it gets lost and it had I don't know,

591
00:38:18,520 --> 00:38:23,960
Speaker 1: important sensitive documents related to national security or um, you know,

592
00:38:24,080 --> 00:38:29,759
Speaker 1: the secret um uh copy of your unpublished book, and

593
00:38:29,840 --> 00:38:32,440
Speaker 1: somebody else runs across it and makes billions of dollars

594
00:38:32,480 --> 00:38:35,239
Speaker 1: off of it because they found it. You can't you

595
00:38:35,320 --> 00:38:38,360
Speaker 1: can't remotely wipe that information. I don't know how you

596
00:38:38,400 --> 00:38:43,759
Speaker 1: would do that without without physically destroying the material. So

597
00:38:44,400 --> 00:38:47,600
Speaker 1: it's that's sort of a uh, a minor drawback really,

598
00:38:47,640 --> 00:38:50,360
Speaker 1: but it's something it's it's something very different from the

599
00:38:50,480 --> 00:38:53,279
Speaker 1: media that we typically talk about so clearly in that case,

600
00:38:53,320 --> 00:38:55,160
Speaker 1: you would be talking about, all right, well, now we've

601
00:38:55,200 --> 00:38:58,400
Speaker 1: got this incredible archival ability. Now we have to figure

602
00:38:58,440 --> 00:39:02,480
Speaker 1: out a way of securing it. Well, don't see that. Well,

603
00:39:02,719 --> 00:39:05,439
Speaker 1: and this brings me to my brilliant science fiction idea,

604
00:39:06,360 --> 00:39:08,439
Speaker 1: which I I said in the pre show. I said,

605
00:39:08,480 --> 00:39:12,000
Speaker 1: if if someone steals this, I will find you. See.

606
00:39:12,040 --> 00:39:14,040
Speaker 1: That was my That was my like shout out to

607
00:39:14,160 --> 00:39:18,480
Speaker 1: your no, no, I'm sharing it because if someone out

608
00:39:18,520 --> 00:39:21,520
Speaker 1: there makes this, I want to cut. So here's the

609
00:39:21,560 --> 00:39:25,400
Speaker 1: sci fi idea. Guys. You have a character who is

610
00:39:25,520 --> 00:39:28,640
Speaker 1: just an ordinary guy or girl, you know, someone who

611
00:39:29,360 --> 00:39:31,719
Speaker 1: is going through life and they've got the same sort

612
00:39:31,760 --> 00:39:35,080
Speaker 1: of challenges and problems and joys and despairs as all

613
00:39:35,120 --> 00:39:38,320
Speaker 1: the rest of us. But then suddenly they noticed that

614
00:39:39,080 --> 00:39:41,319
Speaker 1: they're being watched and people are closing in on them,

615
00:39:41,360 --> 00:39:43,600
Speaker 1: and they don't know why because they're just a normal person,

616
00:39:43,719 --> 00:39:45,960
Speaker 1: and so they're trying to get away, and it turns

617
00:39:46,040 --> 00:39:50,400
Speaker 1: out they find out that they themselves are a synthetic

618
00:39:50,840 --> 00:39:53,719
Speaker 1: life form. They were built in a lab from the

619
00:39:53,840 --> 00:39:58,040
Speaker 1: ground up, and in fact, their DNA contains this incredibly

620
00:39:58,160 --> 00:40:03,040
Speaker 1: important information. In coded into this person's very being is

621
00:40:03,080 --> 00:40:06,719
Speaker 1: a secret message of such import that various forces are

622
00:40:06,800 --> 00:40:09,959
Speaker 1: closing in on them, determined to get hold of this person,

623
00:40:10,480 --> 00:40:12,440
Speaker 1: lop off a finger and figure out what the heck

624
00:40:12,560 --> 00:40:14,920
Speaker 1: is going on, And so the character has to go

625
00:40:15,040 --> 00:40:18,399
Speaker 1: through this incredible series of adventures in order to figure out.

626
00:40:18,680 --> 00:40:21,040
Speaker 1: It's kind of a journey of self discovery as well

627
00:40:21,120 --> 00:40:23,880
Speaker 1: as protection. And there's a whole like hero arc and

628
00:40:24,520 --> 00:40:26,840
Speaker 1: the credits are great and Bruce Willis stars and I

629
00:40:26,960 --> 00:40:32,960
Speaker 1: want to cut I've got data under my skin, are

630
00:40:33,160 --> 00:40:36,200
Speaker 1: in it and through it. So, guys, yeah that was

631
00:40:36,920 --> 00:40:38,640
Speaker 1: I'm sure someone's gonna write in and say, yeah, that

632
00:40:38,760 --> 00:40:43,160
Speaker 1: was a great story when so and so wrote years ago.

633
00:40:43,360 --> 00:40:46,400
Speaker 1: I want to read it. Yeah, yeah, I I have

634
00:40:46,520 --> 00:40:48,680
Speaker 1: no illusions that someone has not already come up with

635
00:40:48,760 --> 00:40:51,160
Speaker 1: that idea. But if they haven't, and then you guys

636
00:40:51,239 --> 00:40:52,600
Speaker 1: think that's a great idea and you want to go

637
00:40:52,640 --> 00:40:54,920
Speaker 1: out and make it. Remember, I want to credit and

638
00:40:55,080 --> 00:40:59,360
Speaker 1: some money or at least a sandwich. Come on, writer's

639
00:40:59,400 --> 00:41:02,759
Speaker 1: gotta eat all right, assassinating stuff though it's it's the

640
00:41:02,880 --> 00:41:04,680
Speaker 1: kind of thing that I would never have thought to do.

641
00:41:04,920 --> 00:41:07,480
Speaker 1: So yeah, I mean I'm blown away by that. Yeah,

642
00:41:07,600 --> 00:41:10,319
Speaker 1: it's a it's a pretty fascinating subject. And like we said,

643
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Speaker 1: there's that we have some great articles on how stuff

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Speaker 1: wor actually can go and check those out and read

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Speaker 1: up on DNA and DNA computers and you know, like

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Speaker 1: I said, there are the articles on the Guardian as

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Speaker 1: well as other places that are talking about this storage

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Speaker 1: medium and it blows my mind. I'm really really excited

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Speaker 1: to hear more about this and to see it develop

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Speaker 1: over time, because in another decade or so, the technology

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Speaker 1: may be there where this is not such a a

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Speaker 1: huge task and we could see like the entire Library

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Speaker 1: of Congress stored in a computer that fits in a

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Speaker 1: drop of water. Yeah, it's pretty amazing, it is, alright, guys, Well,

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Speaker 1: if you have any other topics you would like us

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Speaker 1: to cover in future episodes of tech Stuff, stuff that

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Speaker 1: will truly shake the tech world to its knees, or

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Speaker 1: maybe just think that's kind of cool, let us know.

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Speaker 1: You can email us. Our address is tech Stuff at

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Speaker 1: Discovery dot com, or drop us a line on Facebook

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Speaker 1: or Twitter or handle. There is tech stuff. H. S

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Speaker 1: W and Chris and I will talk to you again

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Speaker 1: really soon for more on this and thousands of other topics.

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Speaker 1: Because it has stuff works dot com