Transforming Businesses Using Quantum Computing

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okay well thank you everyone for attending today's Workshop uh my name is Taylor Kern and I'm the senior coordinator of member engagement here at

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the chal Board of Trade thank you for joining us this afternoon at our value membered emphasis workshop on

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transforming business using Quantum Computing in this workshop with emphasis you will gain a deep understanding of qu

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Quantum Computing and explore its transformative potential in tackling business challenges with Quantum AI

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optimization and simulation solutions before we begin I'd like to acknowledge

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this land that we are meeting on which is home to diverse n First Nations Inuit and mate people though you could be

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joining us or watching from anywhere the board's offices are located on the traditional territory of many indigenous

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Nations they share with us a sense of responsibility intergenerational Equity the well-being of today and tomorrow and

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now without further Ado I would love to pass it over to VC and roit who are going to be today's hosts on your

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Workshop thanks Taylor hello everyone I'm Rohit so uh what I'll do is I'll share my

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screen just give me a

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minute I hope everyone is able to see my screen tayor could you please confirm

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that yeah just got to put it in presentation mode there there you go

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perfect yeah so uh uh hello everyone once again so as uh Taylor mentioned I'm

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going to present Quantum Computing uh uh and its applications for Industries

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today so uh just a brief about me I have around 14 years of experience with eight

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plus years in data science currently I'm leading the quantum Computing initiative at emphasis next slaps and I hold a

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bachelor's degree in electronics in communication and a MERS in Business Administration I have developed a lot of

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AI and Quantum Computing based Solutions and delivered client projects in areas of pfsi Logistics uh among

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others so the topic for today now so this is the agenda that is what I'm

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going to do first I'll just a brief introduction to the team I am part of emphasis nextlabs then we'll jump into

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Quantum Computing what and why where do you apply Quantum Computing then what is

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the state of quantum Computing today and finally what we we at emphasis are doing an area of quantum

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Computing so first of all the introduction to emphasis next slaps so

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uh next slaps is emphasis R&D um for for

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Research into disruptive Technologies and taking it to the market so you focus in areas of cognitive cloud and Quantum

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Computing on the left hand side you'll see a lot of solutions that we have built in uh the traditional AI that is

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uh uh that is like Solutions like mlops Solutions like customer 360° analysis

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process Mining and others these solution Solutions are available and we have used these to solve our customer problems

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then next more recently we are focusing on generative AI in fact we have launched a unit called emphasis. a which

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is our business unit to address AI related problems here we are working on large language driven models we are

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looking at synthetic data generation we are looking at ml governance issues which are coming up across the world

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given the use of decision making through AI under Computing we are looking at uh

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uh algorithmic development and deployment assessment and Consulting service ml optimization and process

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simulation driven Solutions so I'm going to talk about this today since we are an

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R&D driven lab uh we do a lot of thought leadership we have around five awarded patents we have 20 plus a Quantum

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Computing white papers published and since we also address customer use cases

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we have a design thinking driven Consulting model which allows our customers to identify rank prioritize

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and execute Quantum Ai and Quantum use cases uh we have a lot of Partnerships

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with Academy and Industry for example we are partners with AWS assure we are

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premium Premier partners with them for the AI side of things we have a partnership with University of Calgary

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here where we are the anchor business partner for the quantum City initiative they have taken uh other than that we are also

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partners with Alberta machine intelligence Institute in of area of uh solutioning for uh business problems now

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uh generally our output consist of uh customer projects uh industry oriented

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Solutions and Marketplace listings we have around uh we have around 250 plus a

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Quantum Computing Marketplace listings so if you go to AWS generally you will see we are in uh top the top three

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always so you can use these solutions to solve your business problems or if you want to scale your business problems you

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can reach out to us by looking at what is the art of the possible this is a brief introduction on

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next laps now the topic for today Quantum Computing what and why so uh I

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will take a drill down kind of an approach here where I'll just explain what Quantum technology in general is

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and then I'll go into the Computing side of things so bear with me so the idea is that the first Quantum revolution has

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already taken place once we were armed with the knowledge of behavior of subatomic particles and structure of the

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atom a lot of new technologies

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were which basically got translated into integrated circuits which created your computers uh you know atomic clocks for

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GPS uh you know about lasers very very important MRI machines electron

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microscope all these were made possible because uh the physicist identified the

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behavior of subatomic particles now uh more recently we have

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moved into the second quantum Revolution it started around say late uh early 80s

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where somebody uh thought of using quantum mechanics to build technology uh

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a different type of technology so if you look at it uh it is very if I have to make a comparison it is very similar to

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our current digital electronic technology where the idea is to build sensing machines computation machines

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communication networks and encryption systems you know about the internet today you know about our RS protocols

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and all these systems generally fulfill the human need to communicate to compute

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to encrypt messages and to measure things same idea is taken from a

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classical domain to a Quantum domain where we are again trying to build similar things basically sensors

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computers communication networks and encryption systems but the underlying technology that we are going to use is

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quantum physics quantum mechanics rather than the classical uh classical physics

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of today Quantum Computing is a part of this

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revolution the other being the sensing the encryption and communication the difference generally

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lies again in the way uh the computation is done it is it uses certain Concepts

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like superposition entanglement interference and tunneling to solve certain problems with a significant

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performance Advantage we have to keep in mind that a quantum computer cannot solve all problems that you have today

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with the same efficiency or very much efficient than the current computers

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that we have so it is built for specific problems now uh we talked about Quantum

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technology a little I want to talk about Computing now so uh if you see on your

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screen right now I have put uh different typ type of computers that have been

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conceptualized or created over a period of time so if you have to understand

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Computing the the most familiar object that you can look at is the human brain

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the idea is that human brain looks at the real world takes that information and be it images be it sound be it be it

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tab data or whatever it creates a picture uh it creates an abstraction for

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the same which our brain can understand and process the same now keeping this idea of data representation and data

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processing in mind different machines can be able to do the same task so you

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can talk think about searching uh an item in a database or sorting a list or

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building an AI machine all these tasks can be done using different computers we

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have to keep in mind that Computing is a physical process you may write a software program to execute your

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competition but the end of the day there should be a physical substrate underlying physical substrate which does

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the Computing so in Alternative forms of computing in DNA Computing for example you make use of DNA strands to encode

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information and process them you can build a search machine using a DNA computer similarly with chemical

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computers or bages mechanical computers some some similar things can be achieved

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but more recently we have been looking at uh electronic Computing rather than

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the other forms and here we have taken a path since 1950s let's say where we have

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moved from vacuum tubes to transistors to integrated circuits which have now we

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have converted into uh your CPUs your graphic Processing Unit your dsps and

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others and then we have built super computers using the same thing the most

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recent Advent of this is a quantum computer uh it uses a different form of

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data representation and a different form of processing Elements which gives us certain performance advantages for some

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type of problems now the advantage is exponential in nature things that may

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take say a million years on classical computers for certain tasks can be done

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in milliseconds on a quantum computer so we have to keep that in mind for certain problems this Advantage is uh available

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and hence this area is being currently pursued now look coming from qu

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Computing to Quantum Computing these are some key ideas that you have to look at the idea of representation of

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information the information that is available to you in the real world will always in comes in form of images text

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sound tables whatever it is but the different computers represent it in

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different way in case of our digital computers that we use today it is a zero and one representation that is a binary

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representation your images each of those pixels get converted to a number

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that number can be converted to a binary formulation which is then processed in

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case of quantum that representation does not take only zero and one levels but a

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combination of the two this increases the way the uh information density as

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well as the algorithms that process that information their capability for certain type of problems so this Cubit

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representation of information is very important it is uh I generally uh look

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at these kind of representation in form of a language your quantum computer

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understands a different language from a human computer like me versus a digital computer versus a DNA computer so that

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information May remain the same but the representation of information is different which gives it particular

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advantages from uh execution stand of the processing point of view you can look at superposition entanglement and

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interference as things which allow you to do faster processing in certain cases

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now these are are complicated topics in themselves so I won't jump into it but you might have seen interference of

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interference in the Leakes right so that concept if brought down to the atomic

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level allows you to build computers that's the main idea now the second idea is there are

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multiple type of quantum computers that exist some are Universal in nature that

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is you can solve almost any problem on it uh and for example you want to build

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a sorting machine a searching machine uh uh AI machine any sort of machine can be

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built on those these computers are gate based very similar to what we have today that we use today your laptops your

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supercomputers your mobile phones everything but there are other ones as well which makes use of quantum physics

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at the back end but solve a lesser number of problems so Quantum anas is one type which mostly is focused on

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sampling and optimization kind of problems that occur in everyday life

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now there are different camps of quantum Computing uh when I say camps the idea

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is that Quantum Computing is still a new field it is progressing rapidly uh hence

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it we can divide it into two parts one is the useful quantum computers of today they are available today you can make

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use of them and you can solve certain problems these are called noisy intermediate scale Quantum that is

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they're noisy in nature and they have they are smaller in size uh and second is the quad inspired

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part of it these are not quantum computers but classical computers which are inspired by uh Research into Quantum

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uh uh Computing so these gives you some Advantage it is not 1 million years into

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1 milliseconds but say 10 years into four years or that sort of a thing now

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in the future once we solve the problem of noise as well as the scale that we are looking at we can get exponential

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power the 10 the 1 million years into to one uh uh to 1 millisecond these are

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called fall tolerant large scale and this path is progressing very rapidly

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people are able to uh they have made significant Pro progress in error correction as well as stability of

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things so it is not too far away in the future now what if they become available what will change the impact we have to

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know from business standpoint from societal standpoint from other standpoints right it's a disruptive

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technology it will change the world completely think about uh when the classical computers came into existence

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or when internet came into existence sorry this is the level of

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disruption we are looking at in fact more than that uh the gains will be exponential in nature if you can think

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about uh things running in one millisecond you can do drug discovery on

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click of a button which takes years today you can discover new materials which have properties which can take you

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into say you could through which you can build batteries or systems which can take you far away into space which is

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not possible so those kind of Discovery gains are possible and then it it will impact core systems we not looking to

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solve peripheral problems but very core problems like portfolio optimization like last M root optimization Network

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design drug Discovery so very significant technology when you look at the type of use cases we can address

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using this technology I'll go to the next slide so uh where to apply it so before

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we talk about where to apply Quantum Computing what are the current Focus area so not each computer is built to

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solve each problem so if you look at your uh gpus today right uh they are

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used specifically for graphic processing or running AI workloads if you look at neuromorphic Computing they are building

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uh building processes which address a specific task your game Gamers have

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physics uh chips available or audio chips available to process sound or do a

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computation on physics of objects similarly so all these becomes co-processor quantum computer will also

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be a co-processor and right now the areas that we see where most focus is

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given is an area of uh machine learning optimization and uh simulation so

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simulation when I say it has different connotations and different scenarios but I'll say it is a natural process

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simulation where you can look at uh systems where atoms interact to produce results so

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drug Discovery uh uh chemical reactions all these come into this

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area now what is industry doing in this area right so we talked about the focus

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of algorithms and machines and every everything but is industry adopting

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these doing something with these computers today so yes is the answer so I'm I sorry divided this slide into

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three areas Finance Logistics and others in the area of Finance if you look at the slide here uh a field called Quantum

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banking has itself come into existence and you can read about it but uh the use

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cases that are considered and the same as enhanced credit screening was taken by Trade Tech portfolio optimization was

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taken by namura B and BBVA Goldman saxs looked into security pricing and so on

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and so forth one of those case studies from BBV where they used a machine from dwa which

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is a Quantum Anila they used the hybrid solver of it that is a classical qu the machine the

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number of portfolios that was possible of the data was in tune of 10 to the^ 382 now this is a huge number you have

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to find a few portfolios which give you the best risk return profile not easy

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for a classical computer to do the same so around 171 seconds of run time

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uh was taken by building the solution which is a very small time when you look at the possibilities we found uh they

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found portfolios of around 60% return with 15% risk and they achieved a sharp

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ratio of around 12 for certain portfolios these numbers are huge when they used the same classical some

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classical Solution on the same data their range of returns was minus 20 to plus 20% for a risk of 15% so you can

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see that better risk return portfolios can be identified using this using

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programs built on this technology sorry so now I'll go into the

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logistics side of things and I'll take two case studies one is from Toyota systems they wanted to solve the

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automotive part supply chain optimization problem more than 3 million routes were there to their dozens of

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factories and they wanted to F the most efficient routes they use the quantum

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inspired technology here it's called called digital Ana similar to a Quantum Ana and this is provided by fuju there

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was around 30 minutes of runtime and they said that it could cause a potential reduction in cost of 2 to 5%

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which is a big number given the size of the operations other one comes from Los

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Angeles Port of Los Angeles basically where they wanted to optimize operations

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in their third largest terminal P 300 they handle more than 1 million containers per year and 5,000 trucks

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today by building a Quantum Computing driven solution they were able to increase deliveries by 62% per day per

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crane to their dozens of factories and double their throughput and almost half

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their RTG movement other interesting one is performance modeling of jet engine

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designs that was taken up by rolls D they want to achieve Net Zero carbon emissions by

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2050 they looked at a hybrid methodology GPU and qpu and this is happening both given the size of quantum computers

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today they are being used in hybrid mode with uh other processors like gpus which

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allows them to build scalable Solutions now this is a very complex solution that

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they built using uh nvidia's GPU based framework there was around 10 million

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layers and 39 Cubit Quantum circuit it's basically a gate based system that they

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M use of to solve this problem so they are also looking into it and you can look at a a lot of use cases here drug

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development realtime risk modeling Waste Management all those things now where is quantum Computing

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today so before we jump so somebody is trying it out it does not mean that this

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will be the future but if we look at some indicators it's possibly will'll

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make sure that uh you have it available for your uh uh own execution as well as

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people are putting money into it so the first angle I will look at is the strategy and Investments going into Quantum Computing so it has been

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estimated by McKenzie that it will be around $16 billion by 2040 this is whole

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Quantum economy not just Quantum Computing this includes sensors telecommunication networks encryption

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systems everything uh governments more than 10 countries have invested over 1

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billion USD in this area uh 250 Quantum competing startups and uh I have been

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launched and 36 of those were launched in 202 to itself from 2020 the rise rise

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of uh number of Investments the number of companies all has been exponential

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due to the Advan advancement in research sorry there was an startup

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investment of around $5 billion USD and uh uh from 2020 to 22 and seven deals in

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2022 were greater than $100 million so VC's governments everybody's taking

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notice in investing here uh universities are also taking notice where 50 Quantum comput Quantum technology master's

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degree program and 180 universities have launched Quantum technology research groups and uh there has been

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establishment of R&D driven Quantum ecosystem such as Quantum sitting so these things indicate that things are

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moving fast and in the right direction now what is coming out of it if you look at it we are rebuilding the whole Tech

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stack we looking at the hardware the middleware the system software the application software so through this

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research a lot of money is going into Hardware today all these companies that are listed here some already known some

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new have built quantum computers with atom Computing just few days back they

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launched a 1,180 cubit computer uh recently to give a uh to to put some value to that number

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uh 50 Cubit machine if you look at it will surpass a superc computer today 50 Cubit properly built machine where all

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the cubits are connected to each other it can superp pass a super computer but since they are noisy since they are not

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well connected 1,180 is still a leap but still behind what we can do today uh now

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Hardware is being done system and application software is being developed by fisu CQC Nvidia and others and all

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this is made available over Quantum compute as a service providers so Azure has its own service IBM has its own

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service AWS has Zeno and so on so you can see that an ecosystem is coming up

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money is flowing in you can make use of these systems to build Solutions

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today now what we are doing with Quantum Computing at emphasis is an interesting question so we started this area around

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three and a half four years back and our goal uh since it was started in nextlabs

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the goal was to take these this disruptive technology to the market and we did when we did that uh we looked at

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these uh for these seven areas specifically I'll talk about a few so

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our Focus has has already been applied R&D driven so we look at uh the fundamental research that is being done

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in this area and how we can convert that to uh softwares or applications which we

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can uh take to the market we have built in that ve we have built industry Focus

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Solutions we have done Partnerships with Academy and Industry we have written a lot of white papers we have done a lot

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of webinars and we have also created a design thinking driven engagement model which allows customer to adopt Quantum

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computing our industry Solutions will fall in these areas optimization AI simulation

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and finally we're partnering on cyber security cryptography and other things now this is our solution

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portfolio so it is mostly Quantum machine learning and optimization portfolio and if you look at it uh the

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solutions that we have built are in area of logistics supply chain Life Sciences

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uh the airlines all these areas so last my root optimization is one where we

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look at the delivery of packages to the end customers from a Depot from FedEx

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ups and others portfolio optimization we have applied it to uh risk building risk

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return profile for stocks from dow30 S&P 100 NASDAQ 100 brain tum detection we

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have applied Quantum machine learning for image processing similarly we are looking at each feature selection for

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high dimensional ml it is a complicated process today if you want to run High dimensional machine learning model

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sorry because it consumes a lot of compute power and that uh basically

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increases the runtime and computer requirements for the same and you may not get the right quality of result

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Quantum provides a method to do to identify the right features to build a more accurate and more generalizable

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model so a lot of things we have done Airline creu scheduling is another one where we look at how we can uh allocate

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Cru to how we can GR group different flights together and then assign crws to them at minimal cost while maintaining

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all the constraints that coming in it is a very complicated problem and we have built a solution around it as well so what I'll do for now is I have

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more slides but before I keep talking I'll show you two demos at least that we have built uh internally and so that you

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can get uh what we are trying to build using this technology it is very similar to what we build today but just using

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quantum computers at the backend so I'll stop sharing and I'll reshare my

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screen somehow yeah let I hope you can see my

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screen so uh this is a portfolio optimization and asset allocation solution that we have built the idea is

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that if we can uh apply uh Quantum Computing to portfolio optimization

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problem so this is a recorded video because running the solution still will take a little longer if not years uh

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like in a classical computer if I play this so if you see we have looked at three different stocks th 30 stocks uh

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uh your NASDAQ 100 and S&P 100 and I'll show you all three one by one and I'll

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compare it against the classical solution so we have selected the Dow 30 we have taken data from Jan 15 to

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December 19 we did not take recent data because of the because when Co occurred everything changed so we looked at that

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five years of historical data to create the forward-looking risk and return for

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each of the stocks in theor now taking that as the base the statistical return

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and statistic iCal risk for each of these stocks we tried to combine these different stocks together to build

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portfolios which will give you the risk best risk return so I'm showing the first one this

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is just the descriptive page you can review the data and then you can run the portfolio optimization so once we press

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this button the quantum engine is at works this is running on d-wave so this is the

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first result now I'll explain this a bit so if you see this portfolio Frontier which is the most important graph here

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the blue dots are a classical uh solution a classical Monte Carlo enhan solution that we have built where it

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generates different portfolio each dot is a portfolio and the Amber ones here

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are the portfolio generated using a quantum computer now if you look at

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these two you will see some Advantage for similar returns you are for similar

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returns you can find some stock some portfolios with a lower risk now given it's a 30 stock thing with 1

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million invested uh classical computer can handle it in a good way let's see what

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happens when we go to the next solution the next uh uh next indices so right now

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it shows some annual amount this is the yearly return and also we choose NASDAQ 100 and let's see what happens here so

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I'll directly jump into the results now this is interesting if you

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see again the Amber dots are quantum the blue dots are classical for the same portfolio risk

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you find a lot of uh a lot of portfolios with a better return so classical could

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not do it quantum did now this is the second one each of these graphs here

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basically show how much should you invest in each of these stocks we have limited it to 10% at most for each stock

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because there will be Market limits to it this is not exact replication of how Market works but for a comparative

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solution with a classical system this works well enough now if you go to the last one

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this is S&P 100 and here the results again are phenomenal so if you look at it the classical solution basically for

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the same risk same uh risk range the returns are very high and vice versa so

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this at least establishes to certain extent that Quantum uh driven Solutions

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have some capability to surpass what is available class Bally today so this is the first demo I wanted to show

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unfortunately I'll have to stop sharing again because uh Zoom is not allowing me

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to share that share the other demo in the same application so I'll share again just hold on

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please yeah now I hope you can see my screen again now this is the last myot

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optimization demo as I said if you look at companies like FedEx ups and others

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their uh their goal is is to send packages from point A to point B the structure it takes is that there is a

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city station where the packages are collected for delivery or pickup and

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then they are sent over uh in a hub and spoke model so the last part of it which is connected to the customer for uh for

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pickup or delivery is where a lot of cost goes around 53% cost according to

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one of the reports if you are able to optimize the distance traveled by

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different trucks given your Fleet you'll be able to save a lot of cost and in

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that way it's a very complicated solution think about if there are 10

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drivers five time Windows 100 packages or 10 packages it is 10 into 10 into 5

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500 the number of solutions that uh become feasible are 2 to the^ 500 a very

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large number and FedEx and companies like these operate 20,000 packages with thousands of truck at some of the

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location ations they are not able to solve it using any optimization software available today but rather they break

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down the problem into smaller pieces which is suboptimal in nature Quantum does have the capability to handle the

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larger problem in one go and gives you give you the most efficient routes so this is the landing page where we

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start now here what we do basically is we select a new data set here you provide the capacity of the vehicle you

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can give your own Fleet also but we are giving only the vehicle capacity now you schedule your uh pickup and Delivery for

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the day so for today let's say so now you have the depot and the

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customers what is to be delivered how much to be delivered this is the depot this is the location how much to be

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delivered where to be delivered what is the time window in which it is to be delivered so now what we do is we

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basically review that data and same thing is shown on the graph now you run the quantum

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optimization engine it runs and finally if you see it assigns to each customer of vehicle so

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this is after uh running after identifying the number of vehicles required and secondly uh uh secondly

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designing a route after that how much uh which ve which package should go to

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which vehicle basically and on the right hand side in the chart you'll see uh the

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different colors indicating different trucks and P and D saying uh pick up or delivery with customer IDs and vehicle

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combined together now you can review these you can move on and go to the next

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level here basically we showcase uh some uh kpis with respect to our solution so

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if you see total time taken is 19 hours 616 miles covered $185 of fuel cost

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given some mileage and uh uh mileage and cost of fuel uh cost of per unit fuel as

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considerations also did we miss any customers uh was there any overload in

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any of these vehicle all these are important things that we have to consider when building a

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solution now if we go here uh we can go vehicle by vehicle and see the routes that have been designed using this new

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algorithm that we have put into place it gives you the order it gives you the time it gives you the customer

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everything it goes down to vehicle level details distance traveled per vehicle and all some some different kpis

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now since this is a pickup as well as delivery it also shows vehicle load by

34:33

time so when the delivery happened or pickup happened whether anything was overloaded or offloaded all that is shown in this graph so we are building

34:41

the next version of it where we are not just considering the weight constraints of the vehicle but the volume

34:46

constraints we are looking at equitable distribution of work in this case all that has been is being developed this a

34:53

second demo and given we have some time I would like to show one more Dem demo

34:58

here uh I may have to again share my screen so let me just open the demo and

35:03

then I'll proceed forward yeah I hope you can see it so

35:10

this is Airline creu scheduling very important this problem uh basically uh

35:16

if you look at what happened during uh Christmas when the different flights were landed and what knew how to reach

35:23

schedule and all these problems become very important they are large scale problems not easily solvable and some

35:29

sort of uh uh some sort of comput computation compromise is being done

35:35

today to get the solution quantum computers gives you a way to solve these

35:40

problems in their entirety and uh on in this way and we have built this problem this problem is called Airline Cruise

35:46

scheduling it is a two-part problem first you are given a monthly schedule of some Airlines say United Delta or

35:54

WestJet from that monthly schedule say of 500 flights you have to create

35:59

certain groups based on constraints now these constraints are no two flight should overlap there should be a gap of

36:06

1 hour between each flight these sort of constraints are put by labor organization Airlines uh operating team

36:14

Airport operating Team all those now considering those constraints you have to create these groups say you create 10

36:20

groups of 50 flights each easiest solution for now now to each of these groups you have a crew which are at

36:27

certain base locations these crews are to be assigned now again there are constraints when the crew is available

36:33

how many hours they should work all those is considered so the first part where you have to form the groups is

36:38

called Airline crew pairing the second part where you have to uh where you have to assign Crews to the group is called

36:45

Airline crew rostering now again we'll start with a new one here you have to give the

36:51

monthly schedule first so upload your new flight schedule

37:01

now all this is done you add certain constraints that I talked about you can see flying hours of the group The number

37:08

of flights in the group the interflight rest time Duty period all this is to be

37:13

considered so once you do that we are showing some dashboard one so this is a real world data of uh one of the one of

37:20

North American Airlines which had 13 1,3 flights around from 26 different

37:25

airports with 34 million flights per day this dashboard that you see right now we

37:31

trying to establish the complexity of the problem so if you see flight departure

37:38

by day the by hour of the day by flight frequency per day those sort of things

37:44

we have shown you see a lot of overlap between flights from the same airport or

37:49

same arrival and departure airport combination so it's not easy to solve this problem through any method now here

37:55

we are solving the first problem where we are finding groups called pairs from this initial data now if you see we have

38:02

found some pairs for each pair contains certain number of flights and if you see

38:08

each flight leg has been assigned a pair now if you look at each of those pairs

38:13

some some number of flights are assigned now we have compared this between Quantum and classical and Quantum uh is

38:21

working well and we have to keep in mind these are new smaller computers and still they are almost match almost

38:28

either breaking or matching the performance given by classical computers and they're progressing rapidly so some

38:35

comparison by each pair what are the flying RS what are the overall RS all these become

38:42

important this is the first problem that we have solved in the second problem we have to supply the crew data so at three

38:48

different bases the crew are available we upload this

38:54

data now again you have to supply apply certain constraints from the crew so rest period for the crew the flying ass

39:00

of the crew the overall ass the number of crew members per flight all that is to be given and again the second problem

39:06

is solved for each crew we have given the flights that they're going to cover in which pairing they'll be allocated

39:11

all that is given here sorry so again we have done a classical

39:18

Quantum comparison here to Showcase uh what are the results and though this is

39:24

a demo I uh I would encourage you to look at the white papers they are available uh for free on our website

39:30

where we have done a detailed comparison of uh the the different solutions we have run and as we as what we have found

39:38

that as we increase the size of the problem classical computer stopped giving Solutions all together we waited

39:44

for in fact three days no solution quantum computer was done uh say in half

39:49

a day uh basically in fact so every optimization problem has two part one is

39:55

a formulation part part where you encode your objective and constraints programmatically second is the solver

40:01

part in the classical World both are time consuming solver is more time consuming in Quantum case solver is not

40:08

that time consuming it is it sometimes it takes just 7 seconds or something to

40:13

return return the results so this is where I stop with the demos and what I'll do next is I just go

40:20

back to the deck yeah

40:27

sorry my mouse is

40:32

beh yeah so this is where we were now uh we talked about what we have built but

40:38

uh nobody can do Quantum alone in this world it's it's a very complicated field you need uh you need Academy on your

40:44

side you need uh tools and Cloud providers on your site so our ecosystem is built in two two places India and

40:52

Alberta Alberta is our Quantum headquarters in in India we have we are

40:58

uh one of the two industry partners with uh government of India for their Quantum Computing applications lab initiative uh

41:05

we have partnered with I Madras where we have opened our own Quantum Computing research lab uh we are partners with

41:13

krishi which is a startup working in this area again founded by uh a team from I Delhi uh and other universities

41:21

in Alberta we are anchor business partners with University of Calgary uh it is called Quantum for the their

41:28

initiative called Quantum City we are partners with Calgary Economic Development Alberta Government and invest Alberta and we have a shared uh

41:35

ecosystem of providers such as AWS dawave classic Ando now the goal is to

41:42

basically bring uh uh work with our customers in Alberta Canada North

41:47

America and globally to solve uh their Quantum machine learning optimization

41:52

simulation problems using Quantum computing uh this is a special relationship and

41:59

the goal is to create a client focused Quantum Computing ecosystem just hold on sorry and uh here

42:07

we have joined hands together with University of Calgary for the quantum City initiative they are uh the training

42:14

Partners Talent Development R&D partners for this partnership where emphasis

42:19

brings in Industry relevant Innovations and use cases sorry job creation technology

42:27

Partnerships and all uh this collaboration the goal is to do Quantum awareness and training programs for

42:33

industry build a Quantum Readiness engagement model for adoption of quantum Computing access to Industry scientific

42:40

and Technology experts all this now uh since we're addressing

42:46

client needs there has to be an engagement model is placed our goal is to get our customers Quantum ready the

42:52

technology is take Taking pace and a l adoption has consequences so given that

42:59

idea we want our customers to uh start exploring Quantum technology and for the

43:04

same we have built an engagement model so this is the engagement model for Quantum Computing adoption here uh if you look at it we

43:11

have divided this into four parts given the novelty of this technology and the awareness in the market so we start with

43:18

Quantum awareness sessions the idea is to help you create an in-house team or Coe to focus on your Quantum Computing

43:24

goals these take the of a workshop which can be customized based on audience so

43:30

it takes Business technical and strategy point of view now this generally runs

43:35

throughout the engagement we don't want to run it at the very start it depends on when the Right audience is available

43:41

or when they are ready now once other than that what we start with is an assessment Workshop uh the idea is

43:49

basically you don't know where to apply Quantum Computing we come and help you out if you don't if you already have a

43:55

team in place you don't need to do these workshops but the idea is during this design thinking driven uh phase our

44:02

experts work closely with you to identify Rank and prioritize use cases so you identify the use cases you look

44:08

at parameters like whether this use case benefit from Quantum Computing or not if

44:14

it benefits how much benefit you'll get whether it will make uh decent noise in

44:19

your organization to take Quantum Computing forward and many more things do you have the right data in place to

44:24

solve this use case and the and finally we take one use case now the next step

44:30

is a Consulting Workshop this is a in this case we fall we basically address

44:35

two major objectives if you don't have a Quantum Computing service provider on

44:40

your side we help you identify the right one so the idea is for example if you

44:46

want to solve optimization use case at scale today I would say that go with d-waves Quantum Manila if you say no we

44:53

want to do machine learning I will say let's explore some Gateway systems from IBM atom Computing and others so that we

45:01

help you with then we also do some deep dive and find tuning of shortlisted use cases so the use case that we have

45:07

shortlisted in the last phas we looked at those and we basically try to uh Deep

45:13

dive into it what data would you require to solve this use case what kind of kpis you have today how will the system

45:19

integrated how will it work overcloud all those things we address in this workshops and finally when we are done

45:25

with all this we jump into a longer session a longer phase which is a Quantum solution development this we

45:32

work with you to design and implement the solution the goal is not to build a solution and hand it over to you and run

45:38

away the goal is that we build it and we have continuous sessions with your team

45:43

to help you understand how it is being built so that when you pick up the next use case your team is also ready even if

45:50

not to execute but to understand what we are doing and assess the same so sorry so once so now this is the

45:58

engagement model but how do we execute this engagement model so this we have taken a p driven model uh for this B

46:05

driven delivery model the goal is that your use case and it it can be oriented

46:11

towards IP development client delivery capability building any of those each part is a self-sufficient entity which

46:17

contains a Quantum Project Lead a technical lead a domain expert or Quantum developers project managers who

46:23

look at your use case and apply those four phases to it the ones we saw

46:29

earlier these people are they're multi-disciplinary in nature they understand business they understand

46:34

technology and they work together to solve this problem now we have a strategy pod also in place which

46:41

basically is multi-disciplinary emphasis and partners and they look at the

46:46

direction we should take to build Solutions uh address the different strs of quantum Computing which Partnerships

46:54

to take so on and so forth so the this helps you in getting a guidance on where the uh technology is going and we have

47:00

some very strong Partners like University of Calgary where we have who are experts in this field for more than

47:06

30 years now they know in and out of this technology we bring the industry

47:11

angle as well now these are the three use cases we have done till date and we are

47:17

addressing a few more right now the first one is the last phase of qu uh the

47:23

engagement model we were given the use case all we had to do is to apply Quantum Computing to the use case we did

47:30

not do awareness sessions we did not do assessment or Consulting workshops in this we applied a Last Mile route

47:36

optimization solution that I talked about earlier to a last M

47:41

container container delivery with reverse pickup so this for a five Monon project

47:48

uh and this was done for one of the largest uh freight service providers in

47:53

North America uh that is one now uh next one

47:59

is a qu next one is a Quantum Readiness program that we run for one of the largest American healthcare companies

48:04

this was recently concluded uh this again we did for five to six months here

48:10

we did the end to endend engagement model that I talked about awareness session assessment model Consulting

48:15

model as well as the quantum solution development this started with a team of

48:20

zero people who was part of their Quantum team right now they are working with five people in their team

48:26

addressing different areas finally the last one is an interesting one it is ongoing but the

48:32

goal was given uh bodily fluid samples

48:38

can you identify the chemical profile uh that exist within your blood your serum

48:44

your urine and come up with the pathogens that exist in your body so

48:49

that can be addressed using a machine learning solution and we applied Quantum machine learning for it so in this case

48:55

of also the problem was given to us all we had to do was quantum solution

49:00

development now this is my last slide and after that I can take questions this is the analyst response I have we have

49:07

received from our work in this area so from HFS highlight global data it noara

49:13

Gartner all of them have looked at our work and given these comments so this is

49:18

where I'll stop uh over to you VI or Taylor and I

49:24

can address the question awesome thank you Rohit great work uh we do have a couple questions in the chat

49:31

and then once we get to those if anyone would like to unmute themselves and ask any questions please feel free uh the

49:37

first question is from Naveen and they ask does Quantum Computing require specific Hardware or chip yes so Quantum

49:45

Computing itself means a quantum computer a different type of computer it requires a chip based on principles of

49:52

quantum physics and quantum mechanics and these chips are available from different Hardware vendors over Cloud so

49:58

IBM has it Google has it uh Pascal has it atom Computing has it and they have

50:05

uh provided it over Quantum comput as a service providers overcloud IBM Quantum experience AWS bracket Azure Quantum all

50:14

all of them provides hardware and software tools for you to solve the

50:19

problem awesome thank you uh Raphael asks it's it's a bit of a three-parter

50:24

so I'll start if you want to address it in three different parts we can Rafael says can you explain Energy savings when

50:30

using quantum computers to run these Solutions do Quantum Solutions run on

50:36

real time or do they apply to batches and cues okay so I'll address these one by one the first one about Energy

50:43

savings so I do not have an exact answer with this but uh the idea is this that

50:50

right now most of the computers that are many computers that are available today the system has to be cooled down to say

50:57

below zero kind of a thing right so uh given that a lot of energy is expended

51:04

but room temperature Quantum Computing using photonics is also being addressed

51:09

and they will consume very low energy the reason being is these are reversible competition a special thing that you

51:15

have to look at that during competition they do not lose energy so the overall

51:21

cost to run these is going to be low that is my understanding now are these Quantum Solutions are real

51:28

time so uh let me take it uh in form an

51:33

example if you talk about machine learning let's say when you are trading the system uh it's a similar task as what

51:41

you do in classical machine learning only the backend compute has changed but

51:47

when you look at uh running the inference they will be real time you can

51:52

basically uh uh you can provide your batch data or streaming data and they

51:58

can predict what you want to predict so it applies to batches it applies to Q it depends on the type of problem you're

52:04

trying to address rather than the technology you can look at the classical technology how IT addresses these

52:10

problems the exact same thing will be done by a quantum computer there's no difference only thing is backend machine

52:16

has changed awesome thank you roit uh just a couple more for you before we um before

52:23

we head out of here the first one is Will quantum computers once mature replace classical

52:28

computers uh okay so no uh they will not so as I said earlier also that today

52:35

also there are different computers that exist and each has their own specific task uh quantum computer will also have

52:43

have some task which it will excel at for example it is a very important

52:48

technology for fields of chemistry and Material Science to find new materials

52:54

or drugs or do drug discoveries not easy on a classical computer quantum

52:59

computers can give a big Advantage there for example they're not going to be used for web search classical computers do

53:06

that well enough so no they are not going to replace it but they'll work with classical computers similar to how

53:12

qpu uh your uh C gpus physics processing unit and all that work together to say

53:18

build a gaming system today amazing and the last question we have here I think this is really

53:24

important too is what should be the timeline for adoptions of for adoption of quantum Computing so uh nobody can

53:31

say for certain uh numbers the answers are different somebody says that proper fault tolerant large scale Quantum

53:38

Computing will available only in a decade but that does not mean the comput

53:43

quantum computers that are coming up slowly in or will come up in a course of

53:49

one or two years will not change the way uh your operations can be realized so

53:55

your operations still you are not looking at exponential Advantage but some Advantage which gives you cost savings so from that perspective

54:03

adoption should be faster another reason is it is not an easy technology to master it requires an organization wide

54:10

adoption given two these two things it takes time it is not easy to adopt it

54:15

immediately it's not like for example when we switched from CPU to GPU for

54:20

certain tasks still it was not that difficult the underlying technology is same the principles of programming are

54:26

same many of the things are same and uh we were able to address it here the pro whole prog programming Paradigm itself

54:32

is different you're looking to use superposition interference and entanglement very physics based concept

54:40

to write programs but if you can understand them well enough and you can write certain Solutions the advantages

54:47

are humongous and people do understand it your whole organization do not have to switch to Quantum you need a small

54:53

team to begin with which understands Quantum and then grow that team slowly

54:58

hence we are working in this getting Quantum ready model where we start with a small team and then subsequently grow

55:05

them up so that you can uh get the advantage in the longer run it will be applied in certain scenarios again as I

55:10

said it won't be applied in each scenario so you need a particular team size to get the

55:16

benefits awesome uh somebody has a question here with their HR please feel free to unmute

55:21

yourself uh thank you for the presentation this was really great I wanted to ask about the

55:28

commercialization of uh Quantum Computing products in the SAS space uh

55:33

just like how we're seeing the peration of AI products and machine learning products and SAS um how long how many

55:40

years do you think before we start to see off-the-shelf products that allow us to be able to solve very specific forms

55:47

of quantum problems so you can so SAS so if you talk about SAS products can come

55:54

out anytime but the idea is the only issue with Quantum today is solving problem at scale so even if I give you a

56:01

SAS space solution today and we have already have a SAS space solution deployed an Azure for anomal detection

56:07

you can use it the problem is when it comes to scale uh it may not be it may

56:14

not satisfy the requirement you have the scalability is a bigger problem than the specification of it so people are trying

56:20

to solve the same but still as I said uh few days back only 10 days back this

56:26

1,00 Cubit computer has been launched as I said when it became 50 Cubit it already surpassed the capability of a

56:33

classical computer had it been fall tolerant 1,100 is a big number if they

56:38

achieve fall tolerance tomorrow and connectivity you see that the scale has

56:43

changed completely and you can address some large problem classfication will not take time because everything that

56:49

you do today on a classical computer the way uh the apis work the way the solutions are deployed nothing changes

56:56

right now also the all the solutions that you saw that uh today we made API calls to a quantum computer to get the

57:03

result the programming language used was python nothing changes from that perspective only back backend machines

57:10

are changing so SAS Solutions can come up any time but will they be useful or not is the bigger question at this point

57:17

in time awesome thank you Rohit last call

57:22

for any questions before we wrap up for the day

57:28

okay well thank you all so much for attending today um Rohit and VC will be able to send you all the slides he has

57:34

your they both have your contact information and this recording will be uploaded in a couple of days on the

57:39

charm Board of Trades website uh YouTube website so stay tuned for that and again thank you all for attending today's

57:45

session and enjoy the rest of your