thank you so much dye it's a great pleasure for me to come here to Google but also a special privilege to be introduced by daya of a friend but also we have been constantly exchanging ideas and today I'd like to talk to you to talk to you what about I view as the three frontiers of information technology for the future quantum computing artificial intelligence and blockchain but especially also the possible symbiosis among these three major trends I think in these days in the world there are many experts in each one of those subjects but I think really exciting opportunity is possibly the conference or the symbiosis among these three major trends of the future of the information technology let me starts with a story of the recent scientific discovery a recent discovery but it had a long history so a lot of great discoveries in science also relates to some deep changes in philosophy we seem to live in a world of opposites a world of dualism we have whenever we have positive numbers we have negative numbers when we have credits we have deaths we have being and young good and evil angels and demons but in the natural world there's also a counterpart to these philosophy of the opposites or the duality so in 1928 the great and perhaps one of the greatest theoretical physicists of all time Paul Dirac was trying to unify Einstein's theory of special relativity with quantum mechanics in the process of doing so he was doing some mathematical derivations he had to encounter operation of square root and then he remembered from his high school days that the square root of 9 is not just 3 because 3 times 3 is 9 but also minus 3 because minus 3 times 2 minus 3 is also 9 so whenever you take a root you have to take both the positive and the negative roots at that time was very perplexing what that negative root means and he actually in one brain stroke of genius he predicted that for every matter in the world that's the opposite matter or the antimatter and so when you visit Westminster Abbey you can try to find the PAC commemorating the famous Dirac equation until 2012 one of the most humbling experience in my life is to receive the Paul Dirac a medal so just I said whenever you take the square root you have the positive branch and a negative branch and he brilliantly interpreted the mid- branch to be a universal law of nature that for every particle there's in the universe there's also a antiparticle except at a time everybody view this as a beautiful equation but except at a time of 1928 where he made this prediction there was simply no antimatter so for example the antimatter of the electron will be something that has a positive charge but there's a mess the proton has the opposite charge to the electron but has 2,000 times more the mass as the electron so nobody believed him then you know what he said he said my equation is so beautiful you guys simply just go look for it and people did and he was lucky and five years later in cosmic ray radiation it's very hard to naturally produce their town Earth but in the cosmic ray radiation people discovered antimatter namely the positron which has exactly the same mass but the opposite charge of the electron so I think this is the one of the greatest prediction of all humanity that something conceived of beauty also turn out to be true today we actually use this antimatter in medical devices a famous medical imaging technique called PET scan positron emission tomography was actually based on this anti particle the positron it also captured the imagination of Hollywood so there's the famous novel and the movie of da Vinci Code many of you have read the book and saw the movie but there's also a sequel to it's called Angels & Demons also played by also a book by them prompt I also played by Tom Hanks basically the novel depicts the epic struggle between between angels and demons culminating in the halation of particles and antiparticles so actually it's the highest information density one can possibly achieve anywhere in the universe if you have antimatter and which matter the energy they release is the most powerful they can ever be but it's also a fun analogy just as we have NGO we have daemon whenever we have positive a particle we have the opposite antiparticle but human curiosity didn't stop there so after the rocks prediction viewed as one of the greatest prediction of all time curiosity didn't stop there so there was a another great theoretical physicist but somewhat elusive during his time named Ettore Maya Rana and he asked a curious question could there be matter which doesn't have and he made or a particle which is its own antiparticle particle which would not have its own I will not have antiparticle is its own antiparticle is that possible so he asked this question and he also wrote down a beautiful equation which described it but this time he was not so lucky nobody believed him and nobody found it so he actually got very disappointed about that so everything's then it became a mystery in fundamental science so we have in fundamental science a most wanted list for example at the list included what is called a God particle or Higgs boson but in 2012 it was discovered inserting the laboratory in Geneva there's also the gravitational wave Einstein was less lucky than Dirac Dirac only his prediction only took five years for it to be experimentally confirmed but Einstein's prediction of gravitational wave took more than 100 years only two years ago was discovered was Einstein predicted a 100 years ago so this is such a list and and also something called the Dark Matter particle which we still try to find but also very much on the top of the list yes this very interesting concept of my araña Fumiya which is a particle which does not have antiparticle or is its own antiparticle but it's more mysterious maybe among all those on the most-wanted list maybe my Rana for me is most mysterious because not only my runner Lamia has not been found like I said he was very disappointed when nobody believed in his prediction and he was Italian and he boarded a ferry from Palermo – from Naples to Palermo like he never reappeared from that very right so you become a deep deep mystery and this year is exactly the 80 year of his disappearance but we also have some good news to report even though he himself was never found his particle now has been found and that's the highlight of my talk today so so then because he simply wrote down the equation but so he didn't tell people where to find it so that's why it took 80 years so nobody knew where to find them but my theory group has stanford predicted where and how to find this mystery particle and seeing during the period of 2010 and 2015 or theory group wrote three theoretical papers first one exactly to predict were actually quite surprisingly it's not true for this particle to be found in some huge accelerators but it could be in a tabletop kind of experiment very much like a semiconductor device people will usually use so it's a material called a topological insulator that I already mentioned introduction something I discovered ten years ago but they put it into it some magnetic dopants also the topological insulator can be something that business theory right and there you can put in some magnetic dopants which could be chromium and then on top of it you apply a superconductor so we predict that in this system you can find these mysterious my runner phobia but that's not good enough not only you have to predict where to find it but to what to measure in order to find it and there I think a common sense can even guide us so somehow the regular particle is like two sides of a coin whenever you have the upside you have the downside whenever you have the positive particle you have the antiparticle associated with it but it's my Ronna particle is only only one side it is only a particle but no antiparticle so in some vague sense it is half of a usual particle so this concept of 1/2 would be very very important in the later part of my talk about quantum computers so somehow this Marana particle is half of a regular particle so but regular particle has some phenomena of their conductance like the resistance or conductance we usually measure can be quantized in units of 0 1 2 3 and so on so they behave like integers in quantization as depth so we once had had a Eureka moment that if the Marana particle is in some sense half of a regular particle then they should display some plateau at half integer steps namely at 1/2 3 1/2 and so on and so forth so that became our prediction that in this system you can experimental a construct but what you measure is this 1/2 step and last year in a close collaboration with experimental colleagues at UCLA UC Davis and UC Irvine so they exactly constructed this system as we erect a proposed and they perform the measurement exactly according to a theoretical prediction and lo and behold besides this integer step at 1 something at 0 you see there's a step at 1/2 and this 1/2 is a crucial idea that my Arana particle being half of a regular particle you should display was regular particle display integer quantized step my runner particle should give you half quantized step so that is really the smoking gun it was celebrated last year with the publication in the science magazine so in that very exciting moment I remember the famous novel and famous movie I saw about angels and demons and I proclaimed that is as if we discovered a paradise with only NGOs and no demons so I call this the NGO particle so now what is it good for so today or classical computers are already very very powerful but they are good at doing some things and not good at doing some other things so if I give you very two very large numbers and ask the computer to multiply they do this in a split second on Google couch you were maybe a nano nano a second but if you give a number and to ask the computer with a dead number effect arises into two other numbers giving the example for example 15 is equal to 3 times 5 but 11 cannot be vectorized as a product of two numbers the only thing you can do just to say 11 is 1 times 11 which doesn't mean very much but then if I give you a very very large number and if you want to ask whether that were in the large number it can be expressed just like 15 as the product of two other numbers or it is more like 11 which cannot be expressed as a product of two numbers the computer the classical computer will have a very very hard time to answer this question the only way it can do is to do an exhaustive search it tries to divide this very large number by first by 2 then by 3 then 5 by 7 and so on so forth and then it takes forever to to – to do this exhaustive search so what you live do you think about maybe all of the most important computational problems what we were like a computer to do with Google cloud with all the data what we would like to do is to find some optimal solutions or something so when we try to find optimal solution we basically have to enumerate all possibilities computer all of them maybe there's some function optimizing function associated with it and you try to find maybe the least path or biggest profit or something like that but you also have to do an exhaustive search and that takes very very long time so that's why computer has a lot to advanced but then enter the function world what is the mysterious world of the punctum world so if I have two slits and I use a classical and to randomly shoot through these two slits then obviously a bullet either at one given time goes through the right or it goes through the left and on the back of year two you will see two blobs one coming from the right and the other coming from the left but not so if you try to shoot elementary particles through the double slits so somehow on the backgrounds you don't see two blobs associate was the right or one associated was the left you actually observe a rather intricate interference pattern and that pattern can only be explained if the particle went through double slits at exactly the same time it went through both the right and the left at exactly the same time if it didn't do so and if you knew which way it went it wouldn't lead to this intricate interference pattern so somehow the quantum worlds the mysterious quantum world is parallel at one given time a particle is both going through the right and going through the left and then people somehow started thinking that's this very difficult problem the computer classical computer has a very difficult time to solve namely has to go through C really it's an exhaustive search of all possibility maybe it can be done by a quantum computer which is intrinsically parallel so basically then it can search through all these possibilities exactly at the same time and give you one results in one step of computation so there were truly truly be wonderful and will increase computational power in such a tremendous way so but in order to construct such a quantum computer you first need to have the basic elementary unit which will be called a quantum bit or a qubit so a classical bit as you have on your classical computer one bit it's either 0 or 1 but just like a quantum mechanical particle can go through double slits at the same time a quantum bit a qubit somehow is a linear superposition between 0 and 1 it's neither exactly 0 no exactly 1 somehow he lives in this mysterious superposition state between 0 & 1 so in order to do a quantum computer you need necessary have to construct such a elementary qubit a quantum bit but being quantum mechanical is also very very fragile in the classical world if you are very curious to say wow is it really zero is a really one you try to observe it they immediately clutch two zero one and you loose this mysterious quantum concept so therefore in all the most of the approaches that has been proposed to construct a quantum computer it's has a lot and lots of arrows these qubit it's very very fragile and very unstable and it's very easily collapsing to a classical qubit so therefore it's a it's a daunting number that for one use for logical qubits you have to use ten to even perhaps 100 error correcting bit to correct a one use for qubits and that's obviously it's very very very difficult to scale and that's why we don't yet have a truly functional quantum computer yet which can factorize a very big number now enter my scientific discovery so we discover this mysterious a very interesting angel particle which is half of a regular particle so then for so it's a little bit complicated scientific diagram but somehow when you enter in with one qubit which is a regular particle it can be immediately split into two of this Marana vermeer or these angel particles so then each being half so one qubit you already think is the minimal thing you can have but one qubit is now stored in to Angel particles so just like one qubit entering here it's partially start here and partially stopped there then if you have local perturbation it's very hard for local perturbation to destroy the global these two and your particles together function as one qubit so it's very very hard for local perturbation to destroy this qubit and therefore it's a very very robust way of doing computation in fact in this experiment measurement what is happening is that this angel particles are reading with each other so if you have some lines and if you try to braid them that is kind of a digital operation if you either braid it or you didn't whereas in order most other approaches to quantum computing it's almost an analog computation it you can make very easily make little errors but if you do what is called a topological operation of braiding then then it's actually very very robust so you now approach one qubit is just one qubit you don't need error correcting qubits so these are still after our discovery it's is still kind of a new approach so it's coming up but compared to other approaches which may already have many many qubits but a lot of them are serving as error correcting qubits to one useful qubit I believe or approach were eventually scale are much much faster because it's one-to-one so this is the first part of my talk about quantum computer but now let me switch to the second part of my talk which is about artificial intelligence when we look at the human history it is or it has a long kind of Earth it took a very long time for the most intelligent species to develop on earth and it took maybe three million years of evolution but finally we became the dominating species but now we actually face was so our challenge may be a more intelligent species namely AI could be some emerging but era has been developing maybe since the 60s so why we suddenly have this such rapid increase in the progress of AI so it's Mason basically due to the conference of three major trends in computation a1 is the most law so the most law basically is about computational power so it is it doubles the computational power doubles every 18 months according to the progress of the most law so now most law is facing some challenging that's the bad news but the good news is that too maybe we'll have something so much more powerful when then the most law predicts namely we have Moore's law has being a quantitative incremental increase even though it's very very fast but Ponton computer can be one quantum jump in the computational power because of this massive parallelism associated with quantum computing so on the horizon were has see both chanting the in terms of computational power we see both challenges to the classical Moore's Law as the device gets smaller and smaller but we also see tremendous hope maybe quantum computer can can arrive at a scene and so when you try to search among optimization problem you came to one search for one rather than a exhaustive search in a serial fashion so this is something on the horizon that could really fundamentally be a game-changer but the other reason why artificial intelligence today is exploding is because was the arrival of the Internet and the Internet of Things you provided a massive amounts of data and machines need to learn and they learn only from epic Terra and the other is the rapid progress of the AI algorithm and this is also one of the main reason for example the deep neural Nets which is providing the main kind of engine behind this rapid growth so in the field of AI we always ask this question when would someday AI surpass humans and what is the objective test so we're all totally amazed so to see the progress Google has made announced two years ago about deep mind having alphago which beat a human player in playing the game so aunt I was very fortunate that our son Brian was also at working at the deep mind these kind of projects at the same time at that time so when we asked this question so I'd like to revisit a question that we always have been asking namely the so-called Turing tests when is the objective tests that AI really passed the human mind so Turing proposed the following test long time ago he says that if we have a human and then we're having a conversation with a something behind a curtain either another human or a a I machine and if you talk for one long day and afterwards you cannot tell the difference whether it's a human behind or whether it's a machine behind that may be the day when a I really reached to human intelligence but I think it's not an objective test so first of all because the human brain it took a long long time to evolve and a lot of these human brain has a lot of irrational emotional components and maybe it can not be so imitated by the Machine maybe also totally unnecessary for the machine to imitate every human irrationality that's possible because one strategy is you talk to the machine in totally irrational way maybe a rational machine will be very hard to food a human head to to see that it's actually a human so but then what about the Google's success a deep mind of our goal which is a game of human and looks little bit more objective but still it is a game invented by humans why should intelligence test be based on a game that's invented by human so what will be the most objective test that AI really reached human intelligence so I like to have a proposal which could possibly replace the Turing test and then I asked her to play a game of nature namely ask the machine to make a scientific discovery and before the humans do and maybe and then we can objectively such as a prediction of my honor firm young gravitational wave some of the greatest prediction of the human scientific mind and see if the machine can make a prediction before the humans do and when were to an objective experiment and verified the prediction we say this is the day when machine surpassed human intelligence so can we see whether this is possible or not so I am a usually a theoretical physicist but I for the first time I wrote Rai which will soon be published so basic idea is that let's pick so first of all we haven't made the progress of making a prediction that humans has not made but we are idea still be winder history to say that if humanity is still at a point where one great discovery hasn't yet been made whether the machine at the same level can make that scientific discovery so we know some great predictions in theoretical physics such as gravitational wave Dirac antiparticle and so on but maybe the greatest scientific achievements in chemistry isn't Mendeleev's periodic table so Mendeleev looked at all the chemical compounds and he discovered in a brain stroke of genius the organizing principle of the world namely that the order materials that we see can be reduced to elements but these elements organize in itself into a periodic table so at that time he there's only some limited number of elements discovered and whence he organized them into a periodic table he sees some host in the periodic table and he says oh these elements must be there you guys look for it so there was the brilliant prediction and I think certainly I will rank this as the greatest scientific discovery in chemistry maybe of all humanity so the question we like to ask ourself is that if we rewind history that we are in the stage that periodic table has not yet been discovered but if we feed all the chemical compounds to a machine what machine be able to come up with the discovery of the periodic table so that's maybe is quite related to all the AI work that's going on at Google and we actually call or algorithm at Inuvik so once you see the name you immediately see that there must be a lot of connection to maybe all the work you guys are doing here namely this or the Google Translate or the natural language processing is based on a algorithm called words to two met words into a vectorial form and once you map words into a vectorial form you can understand the machine the vector actually encodes some semantic meaning of the word itself and then it can discover certain relationships so hard as were Tuvok work basically try to understand a word in the context of other sentences if two words often occur together like king and queen in one sentence the machine will understand maybe in bacterial space they're somehow close to each other so our idea is to borrow this kind of idea from the natural language processing and try to see if it is possible to be used to make scientific discoveries so we're basically just like Google here would feed all the corpus of texts into a machine using word to back and then discover the meaning of the words and then do translation and so on so forth we basically feeds in a totally unsupervised way or the list of all chemical compounds to the machine and to see whether the machine can come up with the organizing principle and lo and behold the machine or algorithm discover the periodic table because the periodic table can be viewed as nothing but a tool dimensional vector ER arrangements of other elements but if we can do something like atom to Veck it will all similarly map each element into some some vectorial form and the when you collapse this to two dimension you will exactly discover the periodic table so for example like let's seeing a large corpus of text whenever you see King you see Queen a lot the co-occurrence a lot but in chemistry whenever you see NaCl you see KCl a lot so you somehow the machine will understand in a and C and K may be very related to each other so in factorial space there must be close to each other so based on by borrowing the ideas for natural language processing we actually could organize its them in totally unsupervised fashion the machine actually discovered the periodic table so I think we're getting into a very very exciting time there that's one of the greatest scientific discovery can at least be replicated by a machine discovery without any supervision whatsoever but once these algorithms start to work then we can use it to discover new materials and possibly be a user to discover new drugs before the humans do so now let me move to the third stock pic of my of my talk today and namely about the blockchain and maybe some of you are already wondering what AI in quantum computing and blockchain can possibly have anything in common with each other so basically the Internet has always has provided a tremendous value in as a communication tool to to for all of us to communicate but then we have to at some point we have to exchange values over the Internet but whenever we have to exchange value over the Internet we have to agree on a common standards of value so therefore the most important thing when you try to move to the next stage of the internet development possibly moving into the world of finance for example the key essence of finance is to have some consensus about a value the reason why we use goat previously is because compared to something like Apple as a medium of exchange it's because everyone can agree on what one ounce of gold actually means we can do position measurement to determine its content and quality but it's very hard to do it for one Apple because there's so many different kinds of apples so it's not suitable as a medium of exchange so therefore the key element of a medium of exchange is consensus so if I have very broad distribution about the value then it's not suitable to use as a media exchange if we all agree on the value reaching consensus then it is extremely valuable so the internet taught us one very important thing is to namely to do things in a distributed fashion but if they have a very distributed network how can they possibly agree on something so previously in human economy we always thought there has to be some centralized entity which is to control a lot of it and get people to agree some values but when you actually observe the natural world there is a way for the natural world to reach consensus so let me give you one example out of physics for example where every day when you walk up and walk towards your refrigerator to get a glass of milk or something you people usually like to stick a magnet on their refrigerator so how does a magnet really work so actually all materials consists of electrons and electron works like a compass it has a North Pole and a South Pole so electron actually works like a methods but the most of the time they don't agree on the direction to point to so they all pointing in random directions and therefore globally macroscopically they don't behave like a magnet but the magnet their sticks on your refrigerator somehow miraculously a consensus has been reached or electrons decide to point in the same direction and that is happening without any centralized entity telling electrons with what to do somehow there's the mechanism of protocol of exchange somehow they miraculously agree to a point one direction so details about something very very profound about the net natural world to agree on something is what is called a low entropy state and to be disordered is in a high entropy state the natural trend of the world is to gradually always the entropy has to increase over time the world always becomes more more disordered but somehow in a subsystem you can actually reach hung high consensus reduce entropy but then the Caesaria has to there has to be a cost you have to dump the extra entropy somewhere else so it's consensus can't happen in some self-organized distributed way but there has to be a cost associated with it that seems consensus is a state of low entropy you have to dump the extra entropy somewhere else yet I think is the fundamental explanation of why blockchain is working so blockchain has distributed the world of computers and the early approach to have managing a distributed system of computers is to ask whether there's some centralized master algorithm deterministic algorithm possible which will coordinate and and direct all these distributed computers even though some of them have very long latency very broad distribution of latency and some one of them can't even be hacked and behaved maliciously whether this is still in all these circumstances master deterministic algorithm possible to tell all these computers exactly what to do and reach consensus then there's a famous result in computer science called official inch Patterson theorem which actually is a no-go result which says such a master deterministic algorithm is not possible so this actually is the very reminds me of the central result of physics namely the entropy always have to increase if such kind of a master algorithm exists actually we have a name for it it's called Maxwell's demon so somehow this demon has very high intelligence for example if you have a compartment of a gas and you have a war dividing between them and you have a little hole the Maxwell's demon when you sees a high energy particle founder left it opens the shutter ladies through and to low energy particle coming through and then closest a shutter and doesn't match so then if this demon can do all this choreograph in efficient way then little bit later this site will be much hotter than this side and then you can extra some walk to it so such centralized entity to coordinate will really be able to extract energy out of nowhere and this obviously is not possible so I like to make the analogy of the Fisher Lynch Patterson theorem with the concept of the Maxwell demon none of them are possible the master algorithm is not possible and Maxwell demon is not possible so what's it the solution the solution is provided by the blockchain so if you want the entire distributed internet to agree on some temporal order which is the most crucial thing for financial transactions which transaction happen first which transaction happens later you want to order machines to vote but voting at a cost by solving what is called a hash puzzle only those machine can which can solve a hash puzzle which is very deep culture soft but very easy to verify there was some machine solve this hash puzzle every machine will agree that yes this is true and we agree on this temporal order so it's such two szostak algorithm and it actually requires energy to compute and to reach this hash puzzle so therefore in the self-organized blockchain consensus mechanism we reach consensus namely in a state of low entropy but we dump two extra entropy somewhere else through the computation of the hash puzzle and that is very similar to what's happening the physical world namely we can in principle reach this state of consensus of low entropy provided if we dump extra entropy somewhere else so I really think this is really one of the most brilliant invention of in human history somehow we can have a natural and objective mechanism in a distributed world to reach consensus but there's a cost to it namely you have to do this mining work so that the extra entropy can be dumped somewhere else so once will you have this consensus mechanism I think this offers a great new opportunity to last new kind of symbiosis between blockchain and AI so I talked about AI be in conference a magic conference of three major trends I alluded to to the computational power Moore's law and then possibly quantum computers I also talked about some new inventions in the algorithm but what a AI needs the most is to have data so that AI can learn but right now oh data are concentrated as centralized platforms so that's very little incentive for individuals to contribute data because they basically get nothing in return and maybe their privacy could even be violated so I envision the future of the world where the ownership of that data should be completely be returned to the individuals so all my personal data or my behavior data or my online data or my genomics data or my medical records everything should be owned by the individual and the privacy should be completely protected but then you say Wow then calculation possibly realistic if everybody keeps their secret private and there is a beautiful thing called privacy preserving computation and that will make it possible to have a data marketplace so I first of all protected all my privacy data but I can leak information out one bit at a time totally at mine control and such a world will be a data marketplace there individually so it's a peer-to-peer marketplace where individually under their private data and then there can be a bidding and selling process very selectively control by performing privacy preserving data marketplace so such a future world of of marketplace based on one principle which I call in math way trusts and that is possible that it's that you can still preserve privacy but still maintain and but still can't do a computation that only leaks out very very selectively one in piece of information at a time so the famous problem is called a secure multi-party computation or a millionnaire promise so obviously private wealth is very very private people don't like to reveal but there could be so happened that two millionaires want to compare who is richer but without revealing to each other if they review to each other Wells they have obviously they will find out but leaks too much privacy data but there's a computational protocol called Yass Yass doubled circuit that they can exchange particle in the end of the day they only find out one bit of information namely who is richer without revealing anything there's a idea of differential privacy namely adding noise to private data so that they don't become individually identifiable but if I want to conduct a corrective survey I can add noise in such a way that in the statistical aggregate the noise will cancel out so the statistical information is completely accurate but no not much individual private data has been leaked because there's so enough noise that individually identical information it's not there but but overall over statistical information still accurate and then there's also the idea of zero knowledge proof I can prove to you for example that I solved a very difficult game let's say the Sudoku game but I want to only give you one bit of information namely I solve the game but I don't want to reveal you my entire solution I want you to keep on trying card and this is also possible through the zero knowledge proof so there's really a world where mathematics will enter economics in a very sensual way in making a data marketplace possible so that's why all of us were on or individual data and then Google Cloud and all these entities then can compute in centralized they can compute useful statistical information without revealing without in having us to be revealed this privacy death so I really think about this world where both AI and and blockchain combined can do great social good in this new era of crypto economic science based on in math we trust because when you really think about what's the problem with our society today is because there's discrimination against minority and there is a fundamental of our society but when you really think about AI learning let's say if my AI everything is already working accurately 90% of the time but I want some extra data so that I can go from 90% to 99% but that I need is not yet another kind of data which looks very similar to all the previous that I have seen I want data which is called to have high mutual entropy namely the data that's most distinct and that by definition is owned by the minority but then in such a data marketplace I will be to the highest for those data which most in the minority so then the economic incentive structure will be aligned or society will be value the minority the most and that's exactly what we need to do social good so finally there's a vision that the ugly duckling can somehow become a beauty swamp because ugly duckling is not ugly it's different but now difference will be valid the most minorities in this fear that a marketplace will not be discriminated against so I really see this wonderful new world in a conference of three major trends quantum computing AI and blockchain but I also see myself being coming from academia and opening interactions with colleagues in industry we really can enter a new world where the latest scientific idea it's really really fascinating and totally amazing that these mathematical concepts was purely invented by mathematicians in a chat could turn out to be so useful so something like number theory every day when we conduct a transaction using HTTP uses number theory in the most essential way so this is a wonderful new world where collaboration with academia in the industry can really lead to great progress as I said the greatest opportunity of making progress is oftentimes see a conference of some major trends before in anyone who does in their specialized area couldn't see the overall picture and I really think that the symbiosis among these three major trends will be the defining characteristic of the future of information technology thank you should I entertain some questions so you talked about consensus and how proof-of-work systems achieve consensus by distributing and by increasing entropy yeah how does it how does that work yeah so actually I think in the end of the day there should always be some trade-offs so I think find a fan I see the future of the blockchain were out and those cryptocurrency will happen in some what like or what we have in the current world the current war will have m0 m1 m2 different layers so I believe that the most fundamental layer Universal currency should be completely based on proof of work because then the entropy that you dump is extreme it's a totally transparent not only it has to be there but there's also totally transparent I think that the most basic and fundamental layer proof of state will not work because there's so much possibility of collusion that you can lose something I'm chained but gain something off chain it can be bribery and so on so I think we're the the what the true exciting thing about the block chain world is that at the most fundamental layer there can be something that's totally objective and only connects to the natural world namely energy and not so much about proof of state which human irrationality can get involved but I can't very well imagine I'm the higher layers then they will prove a role but the most fundamental layer such like M 1 or M 0 should be completely robust and I still think the proof of work oh there's something another approach which is called proof of space-time proof of space which is based on storage and that's I think it's also it's a quantifiable physical resources I think that the most basically human things shouldn't be involved but maybe it is so I mostly think about quantum computing may be useful for AI as a search algorithm so one algorithm for so all these also happening so one of the most interesting approach to AI is the gang right generative adversary' and networks so I don't mean these three trends all always necessarily have to work together they can actually leads to progress by competing with each other so in one aspect quantum computing and blockchain some were competing with each other because a lot of the Crito encoding algorithm could be broken by compton but on the other hand i also see that kontin can help AI in doing the most efficient search and that's what also a I needs to do right so this relationship is very much like a symbiosis in your ecosystem there's post competition and collaboration yeah we cannot just use a human whale to decade they will always do the same thing they the I think in the process of competition they will all become stronger but there's a metal layer of consensus to be reached that's like I actually agree into this titute distributed system yeah currently in crypto there's many fragmented pools of liquidity quote unquote so how do you bridge that gap between where we are now in these so I think for example the relationship between the Bitcoin blockchain and lightining network very much fits to this framework of m1 m2 so basically the blockchain is completely objective based on proof of work and so this is the try to reach the most universal consensus among parties which totally don't know each other and they need still need to transact but when you really think about business transaction maybe two of us already have been working very well as partners in the last ten years so why should we still use treat each other as as totally strangers so what we can do is we enter into each other state channel by putting or collabos on the blockchain but we keep on doing very very fast trading but we still saddle once a months so this is I think exactly like the relationship between m0 m1 m2 the relationship between writing and Bitcoin is like the relationship between m0 and m1 so where you go above every layer so there should be it's less robust but will be more efficient but the trade-off comes from our history that were already had a history of trust so if you have business partners they already someone know each other they don't absolutely have to use the most universal robust later they can establish a higher layer where they sacrifice some universality but in exchange for efficiency yes no question on the NGO particle yes intra particle is one that's not possible yeah so it's a half a cube it sounds like identity element in your actual art brewing or field right identity element you know when up is again it itself is a node a more precise analogy it's like a complex number can be expressing in terms of two real numbers so the complex number is like a particle the complex conjugate is like the antiparticle if you have the real number the complex conjugate is the same as itself okay so the NGO particle is more like a real number I see how would you now we we think about yeah what would be neutral yeah yeah so so yeah so yeah well I think the analogy is just to say that that so here there's one incoming quantum qubits but actual computation before you do actual computation you're splitting them and by splitting them they're already kind of become non-local their entangled but the classical noise is not entangle so it's impossible to destroy it using classical noise so that's why topological quantum computer can be so much more robust yes okay so combining a couple of the themes of your talk if you're able to harness the power of Kwan competing and if we're able to then secure our data through you know privacy encrypted ways of being able to share it yeah I'm wondering how you see the future of Google because that seems like a truly extant all threatened can spin up a quantum computer that can do extremely efficient parallel search yeah and then they can harness everyone's data I think the only way is to not resist changes but embrace changes right so how do you see examples yeah yeah yeah actually I have an answer to these so in this way actually we can do the following construct that's a for example my private data I want to store it in a secure way but still be possible to do some computation so we know Google Cloud competes with Amazon clouds so what we can do is that on the Amazon Cloud I stole completely random numbers but on the Google cloud I store my information plus rendering information as to our Amazon Cloud so if I really can't assume this these two entities are really competing very hot maybe there's no collusion and there's no way they will secretly exchange but then you can use the protocol of secure multi-party computation to do a computation which gets only one result without revealing any details so in this world centralized entity still is useful but in order for this to work you have to assume that they are competing but not colluding hi I'm just wondering the use of trim entropy is interesting because it seemed to be this mysterious thing but it's also reap resize that in thermodynamics you can have a logarithm term in um in classical thermodynamics and then you have Claude Shannon with information cereals that have an entropy and then you make energy using energy so kinda reminds me of like some sort of free energy yeah yeah it's exactly yeah so so I think the blockchain world is exactly extracting extracting some free energy out of it so so so you're basically you're achieving something but whatever you achieve the total amount of energy the useful amount it's only the energy you spent minus the entropy that you have to waste so the subtract so a lot of you actually today still see a lot of white papers they claim to do miraculous things and these kind of white papers reminds me of the proposals in the 18th century about perpetual mobili I'm just I'm wondering can you extrapolate that now to further then you need a temperature term for the creature to work yeah yeah yeah yeah actually temperatures very naturally if whenever you have a conserved quantity as such as conservation of energy the temperature concept naturally a boss because anytime you have a random but conserved system it's the most generic what is called a Boltzmann distribution so the entropy their temperature comes in naturally but I think could why I get so excited about these is for the first time I see a convergence between social science and natural science yah-tchi provides an anchor for the social scientific world namely a defender my idea for IM 0 m1 m2 the fundamental anchor is now entered natural science we can precisely see the entropy it's wasted so we can see why it consensus reached and then you can build more human things on top of it but the most basic layer is now common bitching social and the natural science and fundamentally reduces to any energy entropy a information thanks so much for your time so I think in your talk you were saying that you're gonna see this first layer of one block chain and then further layers built on top of that so what do you think of the various projects or companies are trying to build their own block chain and how does that relate to your talk so do you think well I think yeah so there has to be some unique thing that you provide so brought a Bitcoin blockchain and you seen are really different so because as a fundamental layer of trust you actually don't want universal Turing machine because it can be maybe hacked but then you have to do some more transactions on top of it and then if the room looks more natural so the evolution of the blockchain world will emulate the evolution of biological species you see for King you see here different species if they long enough maybe they become a different species but there's always something fundamental namely all biological beings are based ourselves so this kind of basic constructs will not change but to some organization the different organisms are different organizations of different cells that may change yes thank you for your time so my question is when do you think quantum computing would be in the application like after your findings and research and when it is in the application do you think it's gonna be in the hands of only big certain companies or its visit scale yeah so so yeah so I think quantum computing research most ideally should be done in open environment I think because yeah let me just make this statement because I know a lot of companies are trying but the very nature of company trying is they have to protect shareholder interest they have to protect a secret but for something so powerful and its implication for Humanity so I know that I think it should be best conducted in Open University research and this is exactly what I'm doing so my approach to quantum computer I have many many temptations to do a company on quantum computers but I resisted that with or without my invention I think if you use this old way of if you use this way of trying it will take a long long time can you just imagine for one useful qubit you need 70 qubit to serve it I think it wouldn't scale but with this approach it was scale okay I think we're about wrap up I'm gonna ask one last question okay yeah does it change any other requirements of quantum computing like such as absolute zero temperature no no no it's a still operates a of most proposals operated at low temperature unfortunately yeah yeah but our approach could work at room temperature if a room temperature superconductors discovered but that hasn't been discovered yet we wouldn't mind that maybe for some very very hard computation if you were there's really a qualitative improvement we can just go it to low temperature [Applause] you

He doesn’t come across as.. depressed hmm 🤔

I feel so so so sad for his death! He is my personal hero!

Too good he speaks about data privacy in front of GOOGLE 😅 50:50

张老师，请在未来等着我们！

Was he talking about the IOTA Blockchain?

6:59 he talks about a scientist who committed suicide… premonition?

It is a brilliant talk in each aspects, I appreciate and very much respect you Mr. Zhang so sorry to lost you, RIP. BTW Blockchain begins on 29:15 .

Thanks professor Zhang for showing us such a promising and inspiring future and It's so sad that you may not witness it anymore, R.I.P

39:29 — Zhang has revealed that "noise" or sound codes can be used in quantum entanglement to ensure that information or data stored cannot be hacked without having the exact same sound code, and that in trying to intercept the statistical aggregate of data the "noise" can be cancelled out.

It’s so sad that Prof. Zhang sacrificed his life for the mankind, we need to find out the truth. Long live Prof. Zhang!

R.I.P. Shoucheng Zhang's untimely death is a great loss to humanity. I surely hope that there was no foul play in his death, but if there was, G-d will avenge his death.

His death is absolutely not suicide. The murderer/murderers eventually need to pay for such a heinous act against a brilliant mind. U.S. is becoming such a horrible anti-human country!

don't know what he's talking about… but just sounds so intelligent brilliant… can't stop watching. so sad the world lost someone like him. murdered by the trump adminstration.

Nothing new in this talk, doubt his research, maybe suicided because of fake papers

这件事美国真的做过了。其它国家就不可以发展吗？一个科学家是可以给整个世家做贡献的，不能总想着自己的利益。如果都这样的话，人类还要不要发展?

RIP, he was killed one day after he met Huawei's CFO. guess who did it?

R.I.P. Those who like murder theories please catch this: US government is investigating his link with ccp investment and connection with Zhongguancun Development Group through Danhua Horizon Capital according to 301 report update, Page46, there is obviously no reason to let him die before everything is clear, as they will lose the clues. Let him rest, PLEASE!

this was just a superficial glance on all three subjects 🙁

A bit surprised his English is not as good I thought….rip

obviously it is donald trump who sent out the assassin to kill Mr.zhang. disgusting the US

fuck CIA

america isnt even in the race in 5G. They have banned all Chinese 5G equipment and resorted to importing from Sweden and Finland.

Huawei warns bans will increase prices and put US behind in 5G race

Huawei's Eric Xu told CNBC that blocking the company's 5G networking products will increase prices and make it harder for the US to become No. 1 in 5G. However, it has been a huge benefit to the two Scandinavian suppliers: Ericsson and Nokia.

They are assassinating Chinese who live outside China now. Xi Jinping really needs to start selling off us treasuries before america defaults. Build thousands of SSBNs. Can use it to protect overseas Chinese and Chinese overseas possessions.

量子计算机指日可待

完全听不懂 什么量子通信技术….我没有机会上研究生了怎么继续学习好呢？

自杀的那位?

Maybe CIA figured out he's the real satoshi

RIP

RIP no matter what had happened it's a lost for all the human beings. Science knows no borders !

out of 7 billion, one

The Chinese communist party is lethal… after years of this guy working his backside off to steal high tech software from the US they did him to hide the fact now that the cat is out of the bag. SUICIDE my foot. Anyway pretty much sounds like the end of G5 ambitions for Huawei.

he was one of the best physicist of all time like Fermi

very sad that such an intelligent man would sell his soul to the communist devil, RIP…..

I AM CIA BLACK OPS.I KILL him

He was so smart. There is no way he will choose to throw his life away.

the best scientific lecture that I have ever seen, this guy is fucking genius, he just use less than an hour to illustrate how our world should be in the next 100 to 200 years, his speech is so persuasive, im overwhelmed.

张首晟先生 你是一位世界公认的伟大的科学家, 但很可惜你竟为 '共' 匪作歹, 被邪恶的中共产党所利用, 竟落到如此收场,可惜,太可惜了!