Speaker 1: Get in tech with technology with tech Stuff from how
Speaker 1: stuff works dot com. Hey there, and welcome to tech Stuff.
Speaker 1: I'm Jonathan Strickland. I'm an executive producer at how Stuff
Speaker 1: Works and I love all things tech and I am
Speaker 1: continuing a special series of podcasts recorded on location in
Speaker 1: Las Vegas, Nevada during the two thousand and eighteen IBM
Speaker 1: Think Conference. So if you think this doesn't sound like
Speaker 1: a normal episode, that's why I am literally by myself
Speaker 1: in a hotel room. I've got an air conditioner blasting
Speaker 1: at me not far away, because I am in Las Vegas,
Speaker 1: a desert. There's no producer here, there's no studio here.
Speaker 1: It's just me and a recorder and a microphone and
Speaker 1: a song in my heart and a dream in my brain,
Speaker 1: and the A C just shut off so it'll be
Speaker 1: a little more quiet now. But the Think Conference is
Speaker 1: a pretty big deal. It's a hundreds thousands of people
Speaker 1: all gathered together learning about uh top topics in computing,
Speaker 1: getting education and workshops involved in all sorts of different things.
Speaker 1: And last night I went to a science slam at
Speaker 1: the conference where we were treated to five different presentations
Speaker 1: by scientists that are related to IBM Research, and we
Speaker 1: got to learn about some breakthrough sciences and some scientific
Speaker 1: work that was pretty pretty interesting, and I wanted to
Speaker 1: kind of report on that and what I saw and
Speaker 1: the sort of implications that the presentations have for us,
Speaker 1: as you know, human being type folks. Well, the presentation
Speaker 1: was opened by the Director of IBM Research, Our Krishna,
Speaker 1: who came up on stage and sort of set the
Speaker 1: ground explained what in brief the five different science breakthroughs
Speaker 1: we're going to be about. There was a lot of
Speaker 1: overlap between them, so expect that when I get into
Speaker 1: the nitty and the gritty. And he then introduced the
Speaker 1: actual MC of the evening, Jamie Garcia. Now, Jamie Garcia
Speaker 1: is a polymer chemist. She works on lots of different projects,
Speaker 1: including ways to figure out how to break down long
Speaker 1: chain polymers so that you can get rid of plastics
Speaker 1: that would otherwise pollute the environment. So an important work.
Speaker 1: It was pretty interesting hearing her talk. She talked about
Speaker 1: how her specific work is very tricky because if you
Speaker 1: want to create computer models of long chain polymers, it
Speaker 1: requires a lot of processing power. The bigger the molecule is,
Speaker 1: the more processing power it needs to simulate the interaction
Speaker 1: of molecules properly because the computer is trying to keep
Speaker 1: track of all the little sub atomic particles. All those
Speaker 1: little electrons have to be modeled and simulated, and as
Speaker 1: you add atoms to your molecule, creating these long chains,
Speaker 1: it creates exponential more work for your computer. So she
Speaker 1: has a vested interest based upon what she studies in
Speaker 1: the advancement of computer sciences. Then she began to introduce
Speaker 1: the actual presenters, and each presenter had about five minutes
Speaker 1: to present his or her study her work and explain
Speaker 1: what they were there about. And it was really interesting
Speaker 1: because there was a it was a good variety. There
Speaker 1: were two men and three women who each got up
Speaker 1: on stage, and they all were trying to explain to
Speaker 1: us the importance of their various projects and what what
Speaker 1: stage they were in, why we should be interested, and
Speaker 1: they all had very different styles, and it was very
Speaker 1: interesting to see these different uh approaches of present presenting
Speaker 1: this information to a general audience, because you know, a
Speaker 1: lot of people in the crowd were not scientists or
Speaker 1: data analysts or anything like that, so it was it
Speaker 1: is a challenging thing to have to communicate science to
Speaker 1: an audience where you're not entirely certain what their background
Speaker 1: happens to be, but they all did a really good job.
Speaker 1: The first one to get up was a guy named
Speaker 1: Andreas Kind, who is an expert on uh cryptography and blockchain,
Speaker 1: and I mentioned a bit in the preview episode the
Speaker 1: kind of Overview episode that blockchain was going to be
Speaker 1: one of the topics that I was going to look
Speaker 1: into here, and I've got a little bit better grip
Speaker 1: on what some aspects of blockchain are all about, and
Speaker 1: it really blew my mind. So Kind came out and
Speaker 1: mentioned that almost everything that we encounter, whether it's a
Speaker 1: product like a designer bag or shoes or car parts,
Speaker 1: or even drugs like medical drugs, has been copied at
Speaker 1: some point, and he cited a number that in counterfeit
Speaker 1: goods were valued at one eight trillion dollars. So you're
Speaker 1: looking at a massive problem across multiple industries where you
Speaker 1: could encounter copies of stuff being passed off as if
Speaker 1: they were the real thing, and in some cases that
Speaker 1: just ends up being kind of a a slap in
Speaker 1: the face to rich people who are buying luxury goods.
Speaker 1: You know, it might be hard for you to feel
Speaker 1: any kind of sympathy for that, because who's going to
Speaker 1: feel badly about a billionaire walking up to a play
Speaker 1: a said buying, you know, some sort of ridiculously expensive wallet,
Speaker 1: and then finding out three months later that it was
Speaker 1: actually a cheap knockoff that was being passed off as
Speaker 1: the real thing. Most of us probably wouldn't lose very
Speaker 1: much sleep about that. Although that is a legitimate problem,
Speaker 1: and obviously anyone who has built their business on creating
Speaker 1: luxury goods of any kind has a really really powerful
Speaker 1: interest in this. They don't want their products to be
Speaker 1: copied because that obviously undervalues what they do. If no
Speaker 1: one trusts that the thing you're selling is actually from you,
Speaker 1: then you're not going to sell very much of it.
Speaker 1: But there are other issues as well that affect, you know,
Speaker 1: the common folk like myself, where even if we didn't
Speaker 1: feel sympathy for the rich people who we're buying these
Speaker 1: luxury goods, we may feel very strongly about these other cases.
Speaker 1: So Andrea's kind gave another example about car parts, and
Speaker 1: specifically he was talking about breaks, but it really could
Speaker 1: be any car part. He said that in certain parts
Speaker 1: of the world, depending upon where you are, you might
Speaker 1: discover that up to forty of auto parts in the
Speaker 1: aftermarket are copies. They are not the legitimate part that
Speaker 1: they are, you know, claimed to be, So that could
Speaker 1: be a huge issue. If perhaps you were getting new
Speaker 1: brakes put into your vehicle, your old brakes are wearing out.
Speaker 1: You go to an auto mechanic shop, you pay a
Speaker 1: certain amount of money to have brand new brakes put in,
Speaker 1: but you may not be absolutely certain that the brakes
Speaker 1: that are being put in are the real deal, like
Speaker 1: they are actually made by the company that you are
Speaker 1: told made them. It may be that they were cheap knockoffs,
Speaker 1: and thus they may not perform at the right level,
Speaker 1: and they might fail more readily than a real set
Speaker 1: of brakes would from the actual manufacturer. That the could
Speaker 1: be life and death, and that obviously is something that
Speaker 1: affects anybody. It's not just the people who have money
Speaker 1: to burn, it's all of us who may rely upon
Speaker 1: this sort of thing. And even if you aren't someone
Speaker 1: who drives, and you're you're not too concerned about auto
Speaker 1: parts and whether or not they're the real thing, or
Speaker 1: maybe maybe you think you know, I'll risk it, I'll
Speaker 1: be careful and maybe my skill as a driver will
Speaker 1: counteract any downfall of the parts there might be. It's
Speaker 1: still not that easy to just kind of walk away
Speaker 1: from this, uh. As Kind pointed out, another big issue
Speaker 1: is medical drugs. He cited a case of a blood
Speaker 1: thinning drug and some researchers who discovered that some instances
Speaker 1: of this blood thinning drug had up to filler material
Speaker 1: in them. In other words, there were instances of this
Speaker 1: drug where it had been replaced with non active ingredients
Speaker 1: are even harmful ones, and this obviously can cause medical problems.
Speaker 1: It can lead to uh serious issues, even even the
Speaker 1: death of the person who is taking the drug potentially,
Speaker 1: and that of course is absolutely unacceptable. And again depending
Speaker 1: on what country you are. In some countries, you you
Speaker 1: are not certain about the origin of the medication that
Speaker 1: you're getting. In certain countries, you know, if you're going
Speaker 1: to a reputable doctor and reputable pharmacist, you're in pretty
Speaker 1: good shape. You're reasonably certain that the medication you are
Speaker 1: taking is in fact what you were told it would be.
Speaker 1: But in other countries where the medical industry isn't as
Speaker 1: as well established and maybe not as well funded, then
Speaker 1: you can't necessarily be certain. You may be taking drugs
Speaker 1: that were bought at a discount, and it turns out
Speaker 1: that a lot of them just don't have the active
Speaker 1: ingredients they're they're supposed to have, and it's not going
Speaker 1: to be an effective treatment for you. So all of
Speaker 1: these different examples were problems that kind was pointing out
Speaker 1: that he said blockchain could help solve, and that raised
Speaker 1: a question. Guys, They're still more to come about the
Speaker 1: science Slam, but before we jump into the next segment,
Speaker 1: let's take another quick break to thank our sponsor. Blockchain
Speaker 1: is a digital construct, right. Blockchain is math and code.
Speaker 1: It's something that exists on computers, but not quote unquote
Speaker 1: in the real world. There's no physical presence of blockchain.
Speaker 1: With cryptocurrency. It's easy to understand more or less at
Speaker 1: a high level why blockchain is effective because every single
Speaker 1: trans action that you make with cryptocurrency becomes part of
Speaker 1: this blockchain that you cannot alter, at least you cannot
Speaker 1: reasonably alter it without having to rebuild the entire blockchain
Speaker 1: from that point of transaction moving forward, and since the
Speaker 1: blockchain is constantly getting added to essentially every ten minutes
Speaker 1: in the case of bitcoin. Your computer is never going
Speaker 1: to be fast and strong enough to build back that
Speaker 1: chain and uh and beat out the rest of the
Speaker 1: system so that you can alter a transaction and make
Speaker 1: it look legitimate. So anytime you buy something with bitcoin,
Speaker 1: anytime you transfer bitcoin to someone else, that transaction becomes
Speaker 1: part of a block of transactions that the overall system
Speaker 1: will validate, and once validated, it joins the chain, and
Speaker 1: every future transaction that is made will contain a record
Speaker 1: that includes your transaction. Though this ledger of transactions is
Speaker 1: shared across the entire network of computers that are participating
Speaker 1: in that blockchain. So if you have ten thousand computers
Speaker 1: in this network, all ten thousand can see that ledger
Speaker 1: and they can see the history of transactions that includes
Speaker 1: the one that you just did. So it makes it
Speaker 1: impossible to really alter things. It's a very reliable record,
Speaker 1: and it makes it very difficult for you to claim
Speaker 1: that you didn't actually spend that bitcoin, and you in
Speaker 1: fact still have that bitcoin and you could spend it
Speaker 1: on something else, well the ledger will say otherwise, and
Speaker 1: that will mean that you will not have a legitimate argument.
Speaker 1: That is fine for bitcoin transactions, but how can you
Speaker 1: use that same technology to ensure that real physical things
Speaker 1: are what they say they are, because if you could
Speaker 1: tag a physical object in such a way that it
Speaker 1: was related to a point of data within a blockchain,
Speaker 1: then you could trace the movement of that that physical
Speaker 1: component as it moved through a system. As Kind pointed out,
Speaker 1: manufacturing in the twenty first century is really really complicated
Speaker 1: because you have lots of different entities that contribute to
Speaker 1: making all sorts of stuff, whether it's drugs or electronics
Speaker 1: or car parts. You might have factories and manufacturing facilities
Speaker 1: that are spread around the world that are all contributing
Speaker 1: toward this. Even if you're talking about food supply, you
Speaker 1: might be able to go to your local grocery store.
Speaker 1: Let's say that you live someplace like San Francisco, California.
Speaker 1: You might be able to go to a market in
Speaker 1: San Francisco and pick up food that was originally grown
Speaker 1: in Japan. Well, you don't know the pathway that food
Speaker 1: took from the point of origin where it was grown
Speaker 1: or caught. Let's say it's fish. You don't know where
Speaker 1: that fish was caught. You don't know who that fish
Speaker 1: was sold to, you don't know where that fish was processed.
Speaker 1: All you know is where you bought the fish. That's
Speaker 1: your last point of contact. You don't know anything else
Speaker 1: about it. But with blockchain, if you were able to
Speaker 1: somehow physically link the fish into a blockchain operation, you
Speaker 1: can actually look at that chain of events and trace
Speaker 1: back every single point of contact that fish had all
Speaker 1: the way back to where it was caught, and you
Speaker 1: would be able to verify that in fact everything was
Speaker 1: UH was safe and healthy, that it didn't pass through
Speaker 1: any hands where there might have been contamination, or at
Speaker 1: least it decreases that, and if there were contamination, you
Speaker 1: would be able to trace exactly where that happened because
Speaker 1: you would be able to look at the chain of
Speaker 1: events and say, well, according to this, it must have
Speaker 1: happened at this processing facility, which would make it much
Speaker 1: easier to UH to do inspections to make certain that
Speaker 1: everything is on the up and up. But how do
Speaker 1: you actually tag that? How do you have some sort
Speaker 1: of record between the physical object and the digital record,
Speaker 1: Because if if you don't have some way of verifying
Speaker 1: that the physical object you're looking at is in fact
Speaker 1: the same one that's in the digital record, you can't
Speaker 1: be certain that the blockchain is an effective uh list
Speaker 1: of transactions for that specific physical object. If I'm looking
Speaker 1: at a pair of shoes and the blockchain tells me
Speaker 1: that the pair of shoes is absolutely legitimate because I
Speaker 1: can trace everything back, But it turns out the blockchain
Speaker 1: is a record of a different pair of shoes, I
Speaker 1: don't I don't know that because there's nothing that's tying
Speaker 1: the physical object in my hands to this digital record.
Speaker 1: It doesn't do me any good. So here's the problem.
Speaker 1: How do you How do you link those two? Andrea's
Speaker 1: kind talked about a way of doing that using something
Speaker 1: called crypto anchors. These are anchor points on physical objects
Speaker 1: that can link them to digital ledgers like blockchain and uh.
Speaker 1: The whole idea is that you have to have some
Speaker 1: sort of encryption, physical encryption that you can attach to
Speaker 1: those physical objects in some way that would allow you
Speaker 1: to verify that, in fact, the chain of events is
Speaker 1: exactly what the digital record says it is. But what
Speaker 1: does that even mean? Like, what what sort of physical
Speaker 1: crypto anchor could you come up with? He gave a
Speaker 1: couple of different examples. One of them I thought was
Speaker 1: incredibly interesting. He talked about a malaria test. Now, if
Speaker 1: you are in another country and you need to take
Speaker 1: a malaria test, you've been bitten by a mosquito, and
Speaker 1: you want, obviously you want to make sure that you
Speaker 1: are testing negative for malaria. You want to also be
Speaker 1: certain that that test is legitimate, that it came from
Speaker 1: a trusted source. So he showed off a type of
Speaker 1: malaria test this piece of paper that had very tiny,
Speaker 1: little colorful dots on one part of the paper, and
Speaker 1: those colorful dots represented an algorithm, a code. So first
Speaker 1: you would look at those colorful dots and you would
Speaker 1: make certain that it was the right pattern, the right colors,
Speaker 1: and you would have a blockchain record of this malaria
Speaker 1: test that would correspond to the code that you're looking
Speaker 1: at the physical code. So as long as the physical
Speaker 1: code on the malaria test matched the one that was
Speaker 1: on the blockchain, you then could feel confident that, in fact,
Speaker 1: this test is a legitimate one. But you say, what
Speaker 1: about counterfeiting? What would happen if someone was able to
Speaker 1: look at the blockchain, they were able to see what
Speaker 1: the code was supposed to be. They take some regular
Speaker 1: old paper that doesn't have a malaria test on it
Speaker 1: at all. Then they very very carefully placed those dots
Speaker 1: in the right configuration, in the right set of colors. Well,
Speaker 1: the secret to this is that the actual code itself
Speaker 1: is the thing you see is only half of the code.
Speaker 1: When you expose that piece of paper to liquid, then
Speaker 1: the ink dots, which are on little bitty micro pillars,
Speaker 1: some of them wash away, some of them are revealed,
Speaker 1: and you have a new code that will be there
Speaker 1: in replace. It's usually in this case with the malaria test,
Speaker 1: you would actually use a serum to do this. So
Speaker 1: only with contact with the legitimate serum would this series
Speaker 1: of dots change and they would change it to a
Speaker 1: new code. And that new code is also tied to
Speaker 1: the blockchain, so you would have a before and after.
Speaker 1: So after adding serum to this malaria test, you could
Speaker 1: then verify that in fact, the malaria test is a
Speaker 1: legitimate one, it's a legitimate source. Then you can actually
Speaker 1: use the malaria test on a patient. So that is
Speaker 1: sort of the way to confound counterfeiters. If you think
Speaker 1: about it, it's not that different from like a special
Speaker 1: water mark on uh uh a unit of currency, or
Speaker 1: one of those elements where you have like a transparent
Speaker 1: panel that's inside a dollar bill or or some other
Speaker 1: unit of currency. It's one of those things that is
Speaker 1: meant to to uh make counterfeiting much more difficult. So
Speaker 1: by having this dual layer of code that only gets
Speaker 1: revealed if you add serum to the malaria test, you
Speaker 1: have helped ensure that the the test that you you
Speaker 1: have in your possession is in fact an authentic one
Speaker 1: and it is linked back to this instance of the blockchain.
Speaker 1: And by having this unique kind of code for every
Speaker 1: single malaria test, you make it incredibly difficult for anyone
Speaker 1: to make a legitimate counterfeit or a legitimate a seemingly
Speaker 1: legitimate counterfeit. And I thought that was really neat this
Speaker 1: idea of making sure using these physical uh components, something
Speaker 1: that you could then link to a digital record. It's
Speaker 1: really really clever. Now kind also talked very briefly, because
Speaker 1: he was coming towards the end of his his presentation
Speaker 1: at this point, about the use of micro chips. I
Speaker 1: was gonna say microelectronics, and I guess technically it kind
Speaker 1: of is, but I mean they're super super small. We're
Speaker 1: talking about chips that are about the size of a
Speaker 1: grain of rice that have more than a million discrete
Speaker 1: components on them, so essentially like a million transistors on
Speaker 1: this little size of rice chip, or even the size
Speaker 1: of a grain of salt. These chips can still have
Speaker 1: very sophisticated components to them, including things like motion sensors
Speaker 1: or or a transmitter sensor. And the idea is that
Speaker 1: these particular chips will cost very little less than ten
Speaker 1: cents to create a single chip, and that they are
Speaker 1: able to monitor and analyze and communicate and even act
Speaker 1: on information. And these little tiny chips would be able
Speaker 1: to analyze products and measure them in such a way
Speaker 1: to make absolutely certain that they are in fact um legitimate.
Speaker 1: They would concentrate on what are considered to be unique
Speaker 1: identify irs or whatever the product is, whether it's the
Speaker 1: specific shape or the chemical makeup or uh any other
Speaker 1: sort of physical property that is considered to be unique
Speaker 1: to that product, that it would be almost impossible, if
Speaker 1: not outright impossible, for someone to duplicate that exactly. You
Speaker 1: would have the chip program in such a way to
Speaker 1: detect that quality, and if the quality is not present,
Speaker 1: then obviously the chip would indicate that, and the chip
Speaker 1: would be the thing that's low. That's that's tied to
Speaker 1: the blockchain. So as long as the chip is active
Speaker 1: on this uh, this product, whatever it may be, and
Speaker 1: that it's verifying that it is in fact authentic, and
Speaker 1: you can record the process of where the chip was
Speaker 1: from one point in the supply chain to the next,
Speaker 1: all the way to its end point, whether it's a
Speaker 1: consumer or a doctor or a manufacturing facility, whatever it
Speaker 1: might be. You could then look at the blockchain verify
Speaker 1: that in fact, all the right steps were taken, it
Speaker 1: went to all the right points of contact, all the
Speaker 1: right processes were uh were performed on this product, and
Speaker 1: the chip is still verifying that the product that is
Speaker 1: in your hands is in fact authentic, then you have
Speaker 1: this ability to say, yes, this is the real thing.
Speaker 1: And at least according to kind Uh, he said that
Speaker 1: using this you could end up cutting counterfeiting in half
Speaker 1: within the next couple of years, and then moving forward
Speaker 1: you could reduce it even further. So this again would
Speaker 1: help people be certain that the thing they got was
Speaker 1: completely legitimate and they wouldn't have to worry about whether
Speaker 1: or not the product they had was going to fail
Speaker 1: on them or be harmful to them or otherwise not
Speaker 1: be what they thought they were getting. So that was
Speaker 1: number one of five. Still have some more people to
Speaker 1: talk about, some more ideas, more cool notions that were
Speaker 1: brought up at the IBM Research Science Slam. I think,
Speaker 1: but first let's take a quick break to thank our sponsor.
Speaker 1: The second person to come up was a PhD student
Speaker 1: named Chichilia Boscini and chi Chilia. She talked about lattice
Speaker 1: based cryptography and I loved Chichilia's presentation. UH. This young
Speaker 1: woman got up on stage and began to speak about
Speaker 1: post quantum cryptography lattice based UH encryption systems, and she
Speaker 1: made it funny and engaging, which is kind of a
Speaker 1: magic power. She talked about how once you learn the
Speaker 1: fundamentals of mathematics, you can build all sorts of things,
Speaker 1: and that when she was a child, she fell in
Speaker 1: love with math. She thought math was fun. She liked
Speaker 1: coming up with problems and solving them. She talked about
Speaker 1: a teacher who would use a story of a fictional
Speaker 1: old old lady who had an electric wheelchair, and a
Speaker 1: fictional old lady kept on getting into various problems. Various
Speaker 1: situations and the math problems were all related. To figuring
Speaker 1: out how this nice old lady in electric wheelchair could
Speaker 1: get out of a various predicaments. So it was this
Speaker 1: sort of this real world kind of of scenario to
Speaker 1: frame all these very ethereal math problems. And Chilia loved it.
Speaker 1: So she went into looking UH into math further and
Speaker 1: studying it, you know, is her primary area of focus.
Speaker 1: She also talked about things like number theory, where you
Speaker 1: take integer numbers and you take prime numbers and their properties.
Speaker 1: And you may remember in the review episode I talked
Speaker 1: about how cryptography is very much reliant. Our current status
Speaker 1: of cryptography is very much reliant on things like prime
Speaker 1: numbers and factoring. So to give you a quick update
Speaker 1: on what I said or a quick refresher, I guess
Speaker 1: on what I said. If you're looking at modern day cryptography,
Speaker 1: modern day encryption UH strategies, typically what you do is
Speaker 1: you take an extremely large prime number. That's a number
Speaker 1: that's only divisible by itself. It doesn't have any other factors,
Speaker 1: so you can't divide by two or four or seven
Speaker 1: or anything like that. It's only divisible by itself. But
Speaker 1: you take a really really big prime number. I'm talking
Speaker 1: about a number there's hundreds of digits long, so enormous number,
Speaker 1: and then you multiply it another equally huge prime number,
Speaker 1: and then you get a product. You get you get
Speaker 1: something that is the product of these two enormous prime
Speaker 1: numbers that becomes sort of your key to encrypting everything.
Speaker 1: And encryption obviously takes other steps past this. You've got
Speaker 1: your encryption key, but then you've got to keep on
Speaker 1: going and actually encrypt everything. But the point being that
Speaker 1: someone could get hold of that encryption key, but they
Speaker 1: don't know the secrets of how things were encrypted because
Speaker 1: they don't have the actual prime numbers that you used
Speaker 1: to create the key. In order to figure out what
Speaker 1: those prime numbers are, you would have to start setting
Speaker 1: a computer program to taking that enormous product and starting
Speaker 1: to divide by various large prime numbers and making certain
Speaker 1: that the other, uh any any you know, reasonable or
Speaker 1: real integer number that you would get by dividing by
Speaker 1: a prime number was also a prime number. And this
Speaker 1: whole process is very very difficult for a classic computer
Speaker 1: can take an incredibly long time to solve. We're talking
Speaker 1: years or decades or even longer to solve some of
Speaker 1: these really hard problems because computers are just going to
Speaker 1: do it sequentially. They're just gonna keep trying, and once
Speaker 1: they try one prime number, they might try a prime
Speaker 1: number and the result they get back is not a
Speaker 1: real number, or it's not a whole integer. Well, that
Speaker 1: that result has to get tossed out because it cannot
Speaker 1: be an answer to your question. Or it might get
Speaker 1: a prime number and it takes this huge number, divides
Speaker 1: it by a prime number, and it gets a second
Speaker 1: whole integer. Everything is cool there, but then the second
Speaker 1: whole integer turns out not to be a prime number,
Speaker 1: which the computer also has to test, right. It has
Speaker 1: to make sure that the result is also a prime number.
Speaker 1: If the result was not a prime number, then that
Speaker 1: result is invalid and the computer has to keep going.
Speaker 1: So this is a very very long process once you
Speaker 1: get to truly large numbers. However, we don't know for
Speaker 1: certain that this particular process is uh is truly a
Speaker 1: hard problem. There's no mathematical proof that it is a
Speaker 1: hard problem. There's circumstantial evidence that it's a very hard
Speaker 1: problem because computers are not very good at solving it,
Speaker 1: but that that alone is not a mathematical proof. Mathematical
Speaker 1: proofs and evidence are two different things. I think I
Speaker 1: actually listened to a gentleman talk with this young woman yesterday,
Speaker 1: and I think he was getting proof. The word proof
Speaker 1: was was causing him to hang up a bit because
Speaker 1: he wasn't thinking mathematical proofs. He was thinking proof. I said, hey,
Speaker 1: I have evidence here, I have proof that this is
Speaker 1: a hard problem. It's not exactly the same thing. They're related,
Speaker 1: but not the same thing. But she explained that with
Speaker 1: quantum computers, if you're able to quantize the information, and
Speaker 1: you're able to use quantum computers, because quantum computers use cubits,
Speaker 1: and if you have a sufficient number of cubits, if
Speaker 1: you have a quantum computer that's powerful enough, it could
Speaker 1: take minute it's to solve a problem that would take
Speaker 1: a classical computer years and years and years to solve
Speaker 1: a classical computer to solve a problem like this. Like
Speaker 1: I mentioned in the preview episode, quantum computers are not
Speaker 1: necessarily great for all computational problems, but for a certain
Speaker 1: set of computational problems, they would be far more efficient
Speaker 1: assuming you had a powerful enough quantum computer. Now, she
Speaker 1: did say, there is some good news. We don't have
Speaker 1: to worry about our encryption schemes falling apart overnight. That
Speaker 1: it took years and years and years to create a
Speaker 1: quantum computer with just a single cubit, and these days
Speaker 1: you're talking about quantum computers that are only at around
Speaker 1: the fifty cubit range, and you would need many, many,
Speaker 1: many more cubits in order to be a serious threat
Speaker 1: to cryptography. That before we get to that point where
Speaker 1: there's gonna be more years of work and development to
Speaker 1: make quantum computers reliable and make sure they don't just
Speaker 1: decohere easily and decoherences when the quantum states all begin
Speaker 1: to collapse in on themselves. So if that happens, then
Speaker 1: a quantum computer turns into a classical computer, and then
Speaker 1: you're just back to where you were before. UH. You
Speaker 1: have a computer that's going to go through the old
Speaker 1: process of trying to solve this problem. Quantum computers sort
Speaker 1: of solve problems in parallel. They kind of test all
Speaker 1: possible UH answers simultaneously because cubits can act in superposition
Speaker 1: and be zero one and all technically all values in between.
Speaker 1: And because of that, you can run multiple problems and
Speaker 1: each bit is acting as either a zero or a one.
Speaker 1: That means you get every single potential combination depending on
Speaker 1: how many cubits you have at your disposal. Right, so
Speaker 1: if you have fifty cubits, that's the equivalent of fifty bits,
Speaker 1: except the bits can be both zero and one at
Speaker 1: the same time. You can run any problem that would
Speaker 1: require fifty bits or fewer, and it will run all
Speaker 1: the potential solution simultaneously, and then will analyze those results,
Speaker 1: and it then assigns sort of a threshold of confidence
Speaker 1: for each of those results at the end of the process.
Speaker 1: And technically usually whichever result has the highest level of
Speaker 1: confidence is most likely the correct one. Uh, this is
Speaker 1: kind of it sounds like I'm dancing around things, but
Speaker 1: that's because quantum is weird. Quantum does not answer in certainties.
Speaker 1: Quantum answers in probabilities. So it may say that I'm
Speaker 1: confident that this particular result is in fact the solution
Speaker 1: to your problem, and you have to decide where's your threshold,
Speaker 1: where is the what is the cut off for certainty
Speaker 1: that you need before you go forward and say, all right,
Speaker 1: this is our result. But if you do have a
Speaker 1: quantum computer with a sufficient number of cubits and you're
Speaker 1: presented encrypted information, then you could potentially do the equivalent
Speaker 1: of a brute force attack of figuring out what that
Speaker 1: encryption scheme, what what numbers it uses if you have
Speaker 1: this this quantum computer, because it can run all those
Speaker 1: calculations I talked about earlier essentially simultaneously and then give
Speaker 1: you the most likely answer, and then you would have
Speaker 1: essentially the keys to the kingdom. And it's it's kind
Speaker 1: of like thinking about someone has found the perfect way
Speaker 1: to create a skeleton key that fits every single lock
Speaker 1: that's ever been made. Once you do that, then locks
Speaker 1: are useless because someone could get hold of one of
Speaker 1: those skeleton keys, they can get access to everything. So
Speaker 1: this is why people talk about quantum computers as being
Speaker 1: the end of our current encryption strategy, because it won't
Speaker 1: do you any good. If someone actually has access to
Speaker 1: a quantum computer, they can decrypt anything that's out there
Speaker 1: that's using that particular approach. So she said, well, eventually
Speaker 1: we're gonna get there. We're not there yet. We're at
Speaker 1: fifty cubits. And in order to get a quantum computer stable,
Speaker 1: you have to keep it at an incredibly low temperature
Speaker 1: to maintain that quantum state, and you cannot interfere with
Speaker 1: that machine at all, because if you do, then the
Speaker 1: coherence dissipates and you're back to having a less powerful
Speaker 1: classical computer. But eventually we're gonna get to a point
Speaker 1: where they are going to be powerful enough. So we
Speaker 1: have to start thinking about what the next evolution in
Speaker 1: cryptography must be in order to protect our data from
Speaker 1: the quantum world. And this brings us to the lattice
Speaker 1: based approach. I had no idea this was a thing,
Speaker 1: and it blew my mind when she talked about it.
Speaker 1: Classic cryptography, we're using large prime numbers. With lattice based approaches,
Speaker 1: you create a a applotting system. Imagine a two dimensional grid,
Speaker 1: so just grid paper. You've got that grid in front
Speaker 1: of you, and you take a point. You make a
Speaker 1: point on that grid, and the lattice problem requires that
Speaker 1: you find the points in a grid that are closest
Speaker 1: to that fixed point you've chosen. That fixed point you've chosen,
Speaker 1: it's called the origin. And so your job as a
Speaker 1: computer is, all right, let me find the points that
Speaker 1: are closest to the origin, and that will be the
Speaker 1: basis of my cryptography. If it's two dimensional. You could
Speaker 1: do it yourself. You can just look at a piece
Speaker 1: of grid paper. You see a point that's on there already.
Speaker 1: You can quickly identify which points are the closest to
Speaker 1: that central point, and you would have the answer right
Speaker 1: in front of you. It's it's it's a it's not
Speaker 1: a difficult problem. What Chilia said was, imagine that you
Speaker 1: don't use just two dimensions. Imagine you use use more
Speaker 1: than two dimensions. Imagine you use one hundred dimensions. Here's
Speaker 1: the thing. We can't really imagine that we live in
Speaker 1: a world of three dimensions that we observe directly. For
Speaker 1: if you argue about time being a dimension, although you
Speaker 1: cannot physically see time, you see the effects of time
Speaker 1: through the causality. But if you were to add extra dimensions,
Speaker 1: which you can do computationally, even though we as human
Speaker 1: beings are not capable of really imagining that, it would
Speaker 1: it makes this problem far, far, far more difficult to solve,
Speaker 1: perhaps too difficult even for quantum computers to solve in
Speaker 1: an arbitrarily easy fashion. So if you do make such
Speaker 1: a problem a lattice based problem, where you know the
Speaker 1: answer and the person that you're sending information to also
Speaker 1: knows the answer, but no one else knows the answer. Then,
Speaker 1: even if they have a quantum computer, they can't just
Speaker 1: brute force figure out the solution to your cryptography strategy
Speaker 1: because it's too difficult to map out. Uh. There's no
Speaker 1: mathematical proof that can simplify this nos, no sort of
Speaker 1: shortcut to the in destination, and so a lattice based
Speaker 1: strategy for cryptography might be the few sure of cryptography
Speaker 1: in general. I think that's amazing, and honestly I still
Speaker 1: only have kind of a semi basic grasp on the concept.
Speaker 1: But the presentation was fantastic and I highly recommend you
Speaker 1: look into it if this sort of stuff sounds interesting
Speaker 1: to you. To Chilia made mathematics sound really entertaining and fun.
Speaker 1: Uh I liked her approach. I don't think I would
Speaker 1: find it nearly as fun. I think I would quickly
Speaker 1: run up against the very limits no pun intended for
Speaker 1: all my calculus fans out there, but the very limits
Speaker 1: of my understanding of mathematics, and then I would get frustrated.
Speaker 1: Because I loved math up through triggonometry, and then once
Speaker 1: you got to calculus, I I I hit a wall
Speaker 1: and I just suddenly could not get my mind wrapped
Speaker 1: around those concepts. So I have a huge admiration for
Speaker 1: people who not only understand the concepts, but they are
Speaker 1: capable of communicating not just the general uh way that
Speaker 1: this sort of stuff works, but also their own interest
Speaker 1: and enthusiasm for the subject. Alright, guys, I recorded the
Speaker 1: full episode about the Science Slam, and it turned out
Speaker 1: to be a little long, So rather than do a
Speaker 1: full epic length episode about the Science Slam, I figured
Speaker 1: out end this episode here and we'll pick up in
Speaker 1: the next one to talk about the other presenters who
Speaker 1: took the stage at Think Conference two thousand eighteen IBMS
Speaker 1: conference to chat about the science they've done and the
Speaker 1: work that they're looking at and how that has the
Speaker 1: potential to really change our world. I am incredibly thankful
Speaker 1: that I got a chance to see these brilliant people
Speaker 1: speak and to to get some inspiration from them, because
Speaker 1: it was really cool to hear about stuff that usually
Speaker 1: I just read like a press release about, but to
Speaker 1: actually hear the people who are doing the research talk
Speaker 1: about it and to kind of convey their excitement about
Speaker 1: their fields of study was really invigorating. So make certain
Speaker 1: you tune into that next episode to hear the conclusion
Speaker 1: of the science slam and what else I learned, because
Speaker 1: it was really cool stuff and I hope you guys
Speaker 1: find it interesting too. If you guys have suggestions for
Speaker 1: topics I should tackle in future episodes of tech Stuff,
Speaker 1: you know, once I get through with this little mini
Speaker 1: series over at the Think Conference, I'm gonna be right
Speaker 1: back to my normal recording schedule and uh, you know,
Speaker 1: good old reliable Jonathan talking about technology. If you have
Speaker 1: anything that you would like me to talk about, maybe
Speaker 1: there's a particular company or a technology or a person
Speaker 1: that you think I should profile, or maybe there's someone
Speaker 1: I should interview or have on as a guest host.
Speaker 1: Get in touch with me let me know what you think.
Speaker 1: The address for the show is tech Stuff at how
Speaker 1: stuff works dot com, or you can always drop me
Speaker 1: a line on Twitter or Facebook. The handle for both
Speaker 1: of those is text Stuff h s W. Don't forget
Speaker 1: to over to Instagram. Check out tech Stuff over there.
Speaker 1: We've got lots of behind the scenes photos and other
Speaker 1: goodies for you to look at. And also I live
Speaker 1: stream when I'm recording in the normal studio on Wednesdays
Speaker 1: and Fridays. If you would like to see me record
Speaker 1: this show live, you can go to twitch dot tv
Speaker 1: slash tech Stuff on a Wednesday or Friday. The schedule
Speaker 1: is up on the page there, and you can watch
Speaker 1: as I record these shows, as I stumble my way
Speaker 1: through mistakes, as I restart, and actually doesn't happen that often.
Speaker 1: I'm mostly mostly what you hear is what I record,
Speaker 1: and you can chat with me. There's a chat room
Speaker 1: in there, and whenever I get to a break, I'm
Speaker 1: happy to chat with all the people in there. Sometimes
Speaker 1: you guys help shape the show and I really appreciate that,
Speaker 1: So join in. Come on over to twitch dot tv
Speaker 1: slash tech Stuff, be part of the group. I look
Speaker 1: forward to seeing you and I'll talk to you again
Speaker 1: really soon for more on this and Bathos of other topics.
Speaker 1: Is that how stuff works dot com wh