Techfastly October 2021

OCT | 2021

w w w. t e c h f a s t l y. c o m

In Conversation with

Arun & Dinesh

Surbhi Rathore

In Conversation with

QUANTUM COMPUTING EDITION

From Bits to QuBits

by Barkha Seth

CEO and Co-founder of Symbl.ai

Co-founders of Yottaasys The Quantum Revolution - A New Paradigm Shift

Quantum Entanglement A New Era of Particle Interaction

by Rehan Husain

by Bhumika Dutta

What’s Inside p.4 From Bits to QuBits

by Barkha Seth

p.10 Quantum Computing

and the Rise of Machine Learning

by Utsav Mishra

p.18 The Quantum

Revolution - A New Paradigm Shift

by Rehan Husain

p.26 Quantum Simulators

An Overview

by Suraj

p.32

In Conversation with Arun and Dinesh, Co-founders, Yottaasys

p.47 Quantum Entanglement

A New Era of Particle Interaction

by Bhumika Dutta

p.54 Do Quantum Batteries

Ever Run Out of Charge?

by Zahwah Jameel

p.60 In Conversation with

Surbhi Rathore, CEO and Co-founder of Symbl.ai

p.66 Changing Dynamics of

Healthcare Sector Quantum Computers Taking A Leap

by Rehan Husain

p.74 Quantum Computing’s

Disruption In Finance Industry

by Vibha Soni

p.82 Google’s Time Crystal

Venture Using Quantum Computers

by Toulika Das

p.88 Does Quantum

Cryptography Cyber Security?

by Simmy Mohanan

p.94 Quantum Computing:

Challenges & Opportunities Ahead

by Ragini Agarwal

Editor’s note

Dear Readers Here we are, three months away from saying goodbye to another year like no other. The silver lining is that life has finally begun its slow and reassuring crawl to normalcy. What could be more normal than an Apple Event in September - where Apple enthusiasts wait with baited breaths as to what new magic might the tech giant once again unfold?

And in their usual style, they never disappoint.

Like one of our writers rightly said, “Big things happen when computers get smaller and faster,” and Apple’s innovations are a testament to that. Speaking of going smaller, we thought of taking a deep dive into the world of quBits, i.e., Quantum Bits. Quantum computing is all about cutting edge tech – we are talking faster computations, longer-lasting car batteries, precision medicines and even revamped banking, to name a few.

Yes, the shift to Quantum might still be a while away, but when you are in the tech industry, it’s okay to be guilty of “Tomorrow Vision”. With Quantum Computing, no matter how many aeons away its practical use could be, tech companies know the potential it holds, and they are actively encouraging developers to jump on board.

But this issue isn’t just about Quantum Computing; we are also bringing incredible insights from two successful CEOs in our interview series. Mr. Arun Pandey of Yottaasys talks about combing advanced machine learning with emotional intelligence to decipher social outcomes based on precise facial recognition and user validation. Ms. Surbhi Rathore of Symbal.ai, on the other hand, is out to revamp AI-powered communication experiences by tailoring storylines through its unique conversation intelligence. All in all, machines are getting smarter, way smarter.

The more we immerse ourselves in the tech promises of tomorrow, the more we feel we are at a precipice - an inflexion point of sorts, where from here, the narrative we create will decide the outcomes for generations to come.

Steve Jobs once said, “I think the biggest innovations of the 21st century will be at the intersection of biology and technology. A new era is beginning”. Profound words indeed, wouldn’t you say?

As always, we would appreciate your feedback, and if there were a topic you would love for us to cover, do let us know.

Here is your edition. Read it, enjoy it, and nourish in the knowledge. Happy reading!

Srikant Rawat

Chief Operating Officer, Techfastly

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FROM

BITS

0

1

TO

QuBITS 0

1

by Barkha Sheth

Every day personal computers, phones and tablets spin a fascinating array of cybernetical illusions. Click on a tiny icon of a browser, and in pops a window that lets you behold the world at your fingertips. Sitting in Canada, but want to map your holiday through the interweaving streets of Rome? No Problem!

‘Maps’ is always at hand. Switch over to the satellite feed to get the lay of the land and even the closest gelato shop. Oh wait, it’s new times. Let’s hold a team meeting or catch up for a coffee with a friend, virtually, of course.

Ever wondered about the wizadry at play?

Ultimately everything you see on your screens is being painted - one tiny dot at a time.

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Dozens of times a second, the screen is swept by a stream of bits. A constantly changing sequence of binary data tells each of the million pixels whether, at any moment, it should be red, green, or blue, or a combination to make many others. When you click on a file, drag it into a folder and then zip it and send it away to a colleague on the other side of the world, the whole activity seems so effortless.

Yet, in the background, we’ve issued a sequence of commands that get translated into ‘bits’ that eventually generate packets that stream through our high bandwidth networks.

Sustaining this illusion requires a staggering amount of information processing. Imagine sending sig-nals bit by bit through the internet where it is decoded and dispatched effectively so that they animate the correct block of the screen on the other side of the world. Now visualise multiplying these actions at least 4 billion times over per second (assuming that at least half of the world has access to the internet and a device). The sheer scale of processing happening here is staggering. Even on actions that are limited

BIT’S AND BYTES

to your personal computer, the amount of processing that is taking place in the background is boggling.

So how long can we hold up to the processing demands of the world?

It’s not just about faster streaming; we are talking about cryptocurrency, machine learning and all the new and upcoming trendy fields. Let’s face it – even with all the sprawling data centres, we will one day run short.

But if our progress is anything to go by - big things happen when computers get smaller.

Remember the iPod and the Smartphone?

Momentous change also occurs when these devices go faster, way faster. And quantum computing is about pursuing perhaps the most significant performance boost in the history of technology. The essential idea? Exploiting the befuddling physics of subatomic scales to shatter all the myopic processing hurdles of today.

Anyone who opens the most basic high-school text on computer theory almost immediately learns two comfortingly simple facts: Any kind of data that goes through the circuitry powering your device can be translated into a combination of two symbols - 1 and 0.

This data is handled using basic operations called AND, OR, and NOT. It’s the underlying principle on which every single computer in the world works, including the supercomputers. But this singular state has been both a boon and a hurdle.

Even with all the computational prowess in our hands, calculations that involve dense computation simply take too long.

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‘Multiple states’ mean that if you’re running an algorithm using qubits, you might need only a single qubit in a superposition to replace all those classical bits.

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Enter – Quantum Computers.

They hope to bring in substantial enhancements in many disciplines.

Longer-lasting batteries for electric cars, advances in chemistry or even enabling new medical treatments, the promise is multifold. Quantum computing has garnered some serious momentum in the last few years.

The appeal of quantum computers lies in their potential to help to quickly answer questions so challenging that it would take decades for today’s computers to solve.

A computer made up of qubit (quantum equivalent of bits) is simply a collection of circuits. The crucial difference between quantum computing and classical computing is that bits are binary. They are either zero or one. Qubits, on the other hand, can be present in multiple states at once through quantum entaglement. The process is aptly termed superposition. ‘Multiple states’ mean that if you’re running an algorithm using qubits, you might need only a single qubit in a superposition to replace all those classical bits. Sequence several qubits together into

a quantum circuit, and the possibilities are stupefying.

The inspiration for a quantum computer came about much earlier than one would imagine.

In the early 1900s, Quantum mechanics emerged as a fundamental theory in physics to describe the physical properties of nature through the microscopic world of atoms and subatomic particles. This led to advances such as transistors, lasers, and magnetic resonance imaging.

The idea to merge quantum mechanics and computational theory arose in 1982 with physicist Richard Feynman. He reasoned that computing based on classical logic could not tractably process calculations describing quantum phenomena. Quantum physics has so many variables (much like nature) that we cannot keep track of them on a computer.

But, although his idea generated the field of quantum simulation, it didn’t spark much research activity at the time.

However, in 1994, mathematician Peter Shor devised a quantum algorithm that could efficiently determine the prime factors of large numbers, sparking a surge in interest in quantum computing. For laymen, this is a classic so-what moment. But when we realise that the security of nearly every online transaction today relies on an RSA cryptosystem that hinges on the unsolvability of the factoring problem, the situation takes a different turn.

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QUANTUM TIMELINE A Japanese tech company achieves quantum communications over optical fibres exceeding 600 km in length, a new world record

2021

2019 IBM announces a 5 qubit processer for developers and by 2017, upgrades that to a 16 qubit processer

2016-17

2011 Researchers at IBM-Stanford University use a 7-qubit computer to factor the number 15

Mathematician Peter Shor writes an algorithm that could tap a quantum computers power to break the widely used form encryption

1985

1981

Physicist Paul Benioff theorizes Quantum Computing

D-Wave announces the first commercially available quantum computer

2001

1994

David Deutch creates a blueprint of a quantum computer

Google Sycamore declares quantum supremacy

1980

Nobel winner, Phycisist, Richard Feynann coins the term quantum computing

How Do The Qubits Fit in Our Future?

Mathematicians are still canvassing what might be accomplished with all this quantum power when it finally grows up. Ordinary computers are great for solving “easy” problems — questions that can be answered in a reasonable amount of time,

like predicting the path of a hurricane or simulating the effect of a nuclear explosion.

Then there are “harder” problems – where solutions are difficult to find because it feels like searching for a needle in a haystack, but once a solution is found its easier to verify its authenticity. One such problem is the factoring of large numbers. With the threat that a quantum computer can potentially break any current cybersecurity system, the race has taken a different turn. Eventually, we will need a new generation of encryption technology to protect sensitive data from potential quantum computer attacks, and tech companies would give an arm and a leg to be at the forefront of that evolution.

Given this and more, companies are progressively investing in this space.

Microsoft’s Azure cloud has released quantum tools, as have Google and Amazon’s respective cloud platforms. IBM is even offering online access to some of its quantum processors, so anyone can experiment with them. In 2019, Google demonstrated that its 54-qubit quantum computer could solve in

minutes a problem that would take a classical machine 10,000 years. But this ‘quantum advantage’ applied only to an extremely narrow situation. Long term, though major technology giants see themselves generating cashflow by charging corporations to access data centres packed with supercooled quantum processors.

On the other hand, non-tech experts expect quantum computing to help us understand biology and evolution, cure cancer, and even take steps to reverse climate change. But all said and done, quantum computing is still in an embryonic state, and its real-world application still feels a while away.

If you are wondering what’s in it for the rest of us? Well, the dawn of PC’s has helped make life safer, comfortable, and more convenient. The age of quantum computers should have similarly sweeping and valuable consequences.

Perhaps it could result in a Smartphone-Q? Who knows…

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QUANTUM COMPUTING AND THE RISE OF

MACHINE LEARNING

by Utsav Mishra

Q

uantum computing has developed in recent years as a novel computing model that has the potential to take traditional computers to a whole new level. All technology-related media outlets have been publicizing all minor and potential advancements in this sector.

Even though this is an exciting period for the field, the field itself remains a mystery.

The mystery behind quantum computing remained in the closet for many years until the day it was discovered. And since that day, everything has changed in the computing world. A lot of things became extremely easy, and the machine learning scenarios took a leap in just a few years.

Saying this wouldn’t be wrong that quantum computing will revolutionize machine learning for years to come.

Let us begin with what quantum computing really is.

What is Quantum Computing?

Quantum computing is a field of computing that focuses on developing computer technology based on quantum mechanics (which explains the behaviour of energy and material on the atomic and subatomic levels).

Traditional computers can only encode/ decode information in bits that have a value of 1 or 0, limiting their capabilities.

Quantum computing is an exciting thing when we talk about machine learning (ML).

It combines with ML and gives us Quantum Machine Learning as a product.

But this is where quantum computing distinguishes itself; it uses quantum bits, also known as qubits. The theory used here is that subatomic particles can exist in one or more states.

The assumption of quantum computing is that it can be useful in a variety of applications that are deemed critical in today’s technological environment, ranging from cybersecurity to medical applications to machine learning. One of the primary reasons for the field’s popularity is its broad range of applications.

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What is Quantum Machine Learning?

Let us go a little back in time and look at machine learning in a broader context. Machine learning is made up of two components: data and algorithms. So, when we talk about quantum machine learning, do we mean the data, algorithms, or both?

At points where classical machine learning raises its hands and refuses to help us, the abovementioned quantum computers help us with quantum machine learning.

Tensor network

and de-quantized recommendation system algorithms are examples of quantum-inspired classical algorithms processing classical data.

Quantum algorithms, such as

quantum optimization algorithms

and quantum classification of classical data, are applied to classical data.

Classical methods,

such as neural network-based quantum states and optimizing pulse sequences, are applied to quantum data.

Quantum algorithms, such as

quantum signal processing

and quantum hardware modelling, are applied to quantum data.

Now that we are acquainted with quantum machine learning, let us look at how it can change the future, i.e., how it can improve the present machine learning scenarios to create a better future.

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OCT 2021

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THE FUTURE IS ALL QUANTUM Quantum computers are capable of quickly resolving complex problems If one of these industry giants succeed in developing a commercially viable quantum computer, these quantum computers would likely be able to finish computations that would take thousands of years to do using traditional computers.

Google now claims to have a quantum computer that is 100 million times faster than any current machine.

It will be important if we are to handle the massive amounts of data we create and solve extremely complicated issues. The key to

success is converting our real-world problems into quantum language.

Our data sets’ complexity and scale are expanding faster than our computer capabilities, putting significant pressure on the fabric of computers. While computers today struggle or are unable to tackle particular issues, the power of quantum computing is predicted to solve these same difficulties in seconds. It is expected that improvements in quantum computing technology would help artificial intelligence, particularly machine learning, and will continue to do so. Quantum computing methods enable us to improve on what machine learning can currently do.

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Solutions will be optimized by quantum computers Another way quantum computing will assist usher in a revolution will be to sample data and optimize all types of issues we face; from portfolio analysis to the best delivery routes to help identify the best treatment and pharmaceutical routine for each individual.

With the rise of big data, we have modified our computer architecture, necessitating a novel computational method to deal with large data. It is not just greater in scope, but the challenges we attempt to tackle are extremely complex. Quantum computers are more suited to solving sequential problems. The ability they provide businesses and even consumers to make better decisions may be all that is required to persuade firms to invest in this emerging technology whenever it becomes available.

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OCT 2021

Quantum computers could spot patterns in large data sets Quantum computing is predicted to be capable of rapidly searching massive, unsorted data sets for patterns or abnormalities. Quantum computers may be able to examine all objects in your database at the same time and detect these abnormalities in seconds. While this is technically conceivable today, it requires a parallel computer to look at each record one by one, which takes an inordinate amount of time and may never happen depending on the size of the data collection.

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For the first time in quantum history, anybody may access and run tiny to moderate programs on quantum computers.

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Quantum computers might aid in the integration of data from various data sets Furthermore, due to the integration of extremely diverse data sets, major advancements are predicted when quantum computers become accessible. Although this may be challenging initially without human interaction, human engagement will assist computers in learning how to integrate data in the future. So, if a research team wanted to compare various raw data sources with unique schema linked to them (terminology and column headings), a computer would need to grasp the relationship between the schemas before the data could be compared. Breakthroughs in the study of the semantics of the natural language are required to do this, which is really difficult in artificial intelligence. Humans, on the other hand, may provide input that trains the system for the future.

Quantum computers promise to enable rapid analysis and integration of massive data sets, improving and transforming machine learning and artificial intelligence capabilities.

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OCT 2021

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End-Note Quantum computing offers enormous promise for enhancing and altering the way technology works today. Despite the fact that quantum computing is not a new topic at all — it is as ancient as computing itself — it has garnered traction and a lot of attention in recent years.

However, quantum has recently progressed from pure theory to practice. That is the cause for the unexpected surge in media and scholarly interest. For the first time in quantum history, anybody may access and run tiny to moderate programs on quantum computers.

These signs are enough to provide the promise of a bright future that lies ahead of us in the field of quantum computing. Hope all these promises come true in the future.

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The Quantum Revolution - A New Paradigm Shift

by Rehan Husain As we seek to harness even more of the quantum world’s potential, the world is on the verge of seeing a second quantum revolution.

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OCT 2021

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Q

uantum physics has already altered our lives. Almost every electronic gadget we use today is an example of quantum physics in action; the laser and transistor were both invented owing to their innovations— both of which are products of quantum theory. As we seek to harness even more of the quantum world’s potential, the world is on the verge of seeing a second quantum revolution. Quantum computing and quantum communication can significantly influence various industries, including medicine, electricity, economics, security, and recreation. Recent estimates indicate that the quantum sector will be worth billions of dollars by 2030. However, substantial practical obstacles must be addressed before achieving this degree of widespread influence.

Quantum technologies can improve various processes, from online trading to sophisticated chemical simulations and even nanotechnology engineering. A quantum revolution is taking place, although it is still in its early stages. The scenario in which quantum machines unambiguously outperform any conventional (classical) hardware for a given computational task – is the real holy grail for quantum physicists.

If we can attain quantum supremacy, the world will ultimately benefit from quantum mechanics for the first time, which has never been feasible before.

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Two Extreme Ends: Quantum and Classical While quantum theory dates back more than a century, the present quantum revolution is predicated on the more recent insight that uncertainty — an essential characteristic of quantum particles — may be a valuable resource. At the quantum particle level, such as electrons or photons (light particles), it is difficult to determine all the particle attributes at any point in time exactly. For instance, the GPS in your automobile can provide you with your location, speed, and direction simultaneously and with sufficient precision to bring your destination. The GPS in your car can provide you with your sight, speed, and direction simultaneously and with adequate precision to bring you to your destination. In the quantum realm, we must communicate in probabilistic terms rather than absolute terms. And in the context of computers based on binary digits (bits) of 0s and 1s, this means that quantum bits (qubits) have a chance of being both 1 and 0.

Such ambiguity is first unsettling. In traditional computers, 0s and 1s are connected with switches and electrical circuits that turn on and off. From a computational standpoint, not knowing whether they are on or off makes no sense.

This would result in calculating mistakes.

However, the innovative notion underlying quantum information processing is that quantum uncertainty — a fuzzy in-between “superposition” of 0 and 1 — is a feature, not a defect. It introduces new levers for more robust data communication and processing.

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OCT 2021

The innovative notion underlying quantum information processing is that quantum uncertainty — a fuzzy in-between “superposition” of 0 and 1 www.techfastly.com

While mathematical encryption systems can be hacked by powerful enough computers, cracking quantum encryption would need breaking physical principles.

Quantum Communication in Action One consequence of quantum theory’s probabilistic nature is that quantum information cannot be accurately replicated.

This is game-changing in terms of security.

This fundamentally unbreakable encryption is based on physical principles rather than the sophisticated mathematical techniques employed today. While mathematical encryption systems can be hacked by powerful enough computers, cracking quantum encryption would need breaking physical principles.

Quantum encryption differs fundamentally from existing encryption approaches in mathematical complexity, while quantum computers vary fundamentally from current classical computers. They are as unlike a

car and a horse and cart. In comparison to a horse and carriage, a vehicle is built on harnessing distinct principles of physics.

It takes you to your goal faster and to previously inaccessible locations. The same may be stated of a quantum computer vs. a conventional computer. A quantum computer uses quantum physics’ probabilistic principles to process data and execute calculations in new ways. It can accomplish previously inconceivable operations like quantum teleportation, in which information stored in quantum particles disappears in one site and is precisely (but not instantly) reproduced in another position far away. This new data transfer method might be a critical component of a future quantum internet.

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The simulation and analysis of molecules for medication discovery and material design might be a particularly appropriate use of quantum computers. A quantum computer is ideally equipped for such jobs because it operates under the same quantum physics principles as the modeling molecules. Using a quantum gadget to mimic quantum chemistry might be considerably more efficient than the fastest conventional supercomputers now available.

Qubits are incredibly fragile as compared to bits. Quantum information can be destroyed by even the tiniest disruption from the outer environment. As a result, most modern equipment must be protected in isolated settings with temperatures much below outer space. Although a theoretical foundation for quantum error correction has been created, putting it into practice in an energy- and resource-efficient way faces major technical hurdles.

Quantum computers are also well-suited to tackling complicated optimization tasks and doing quick searches of unsorted data.

This might be useful for various applications, including sorting climatic data, health data, and financial data and optimizing supply chain logistics, labor management, and traffic flow.

The quantum race has already begun globally.

Globally, top-notch business people, governments, private investors are spending billions of dollars on quantum research and development. It has been demonstrated that satellites may disseminate quantum keys for encryption, providing the foundation for a quantum security-based worldwide communication network. Large-scale quantum computing hardware and software are developed by IBM, Google, Microsoft, Amazon, and other firms. Nobody has arrived yet. While small-scale quantum computers are now operating, dealing with mistakes is a crucial roadblock to scaling up the technology.

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The Quantum Supremacy Unsurprisingly, a massive global effort is underway to show that quantum mechanics-based technologies can outperform conventional systems in terms of computational capabilities, with businesses and research institutes from Europe, the United States, China, Japan, Australia, and Singapore all participating. In the following years, the total investment will approach a billion euros, with research focused on various physical systems, including superconductor circuits, photons, single atoms trapped by laser beams, and trapped ions.

So yet, there hasn’t been a clear winner, and each piece of gear will be better suited to a particular purpose. With single photons traveling within the present fiber networks, integrated photonics will undoubtedly be a significant participant in any quantum communication. It’s unclear when or if the full capability of quantum computing will be available, given the current state of the science. Nonetheless, corporate executives should think about establishing plans for three major areas:

1

Quantum security planning:

Current data encryption techniques are susceptible to future quantum computers and ever-more-powerful conventional computers.

New encryption standards (whether classical or quantum) are unavoidable. Planning, resources, and quantum knowledge will be required to transition to a quantum-secure architecture and supporting infrastructure for data security. Even if quantum computers are

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OCT 2021

a decade away, it would be too late to adjust then. The moment has come to begin the procedure.

2

Identifying use cases entails the following steps:

Nobody could have imagined how traditional computers would affect every part of our lives in so many different ways. Quantum applications are similarly difficult to predict. As a result, to fully realize quantum computing’s potential, business executives and specialists from many industries, such as health, finance, and energy, must collaborate with quantum researchers and hardware/ software developers. This will make it easier to create industry-specific quantum solutions customized to existing quantum technologies or future scalable quantum computers.

Building and developing the quantum app marketplace will require interdisciplinary skills and training.

3

Designing with responsibility in mind:

Who will create quantum technology and access it, and how will consumers interact?

The influence of AI and blockchain has highlighted the importance of considering emerging technologies’ social, ethical, and environmental consequences. The quantum industry is still in its infancy. This presents a once-in-a-lifetime chance to develop a reliable and long-term quantum computing roadmap by including inclusive principles from the outset.

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Conclusion The quantum technology sector’s explosive rise over the last five years has been thrilling.

However, the future remains uncertain. Fortunately, quantum theory explains why unpredictability isn’t always a negative thing. Indeed, two qubits may be locked together to remain undecided individually but are entirely in sync collectively — either both qubits are 0 or both are 1. Entanglement, or the mix of joint certainty and individual unpredictability, is a potent fuel that powers several quantum computing processes. It might also be instructive in terms of how to develop a quantum industry. Businesses may increase their chances of being ready for the quantum future by preparing responsibly and embracing future unpredictability.

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Quantum Simulators An Overview

by Suraj

Q

uantum simulators are the promising technologies that allow scientists to conduct complex studies or experiments which are nearly impossible to conduct in traditional laboratories. These simulators are used to perform quantum studies using supercomputers. They could prove to be extremely beneficial in taking the research activities to an advanced level.

Nowadays, it is the heart of physics and various scientific researches because many scientists are trying to frame this outlandish theory into an advanced possibility to find solutions to the various physics questions. However, simulations are not simple, and it is far beyond our current technologies. If scientists turn this incredible theory into a successful possibility, it will make understanding atomic, high energy, and many other condensed physics concepts easier.

This article will provide foundational information about quantum simulators and how they will benefit the world.

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What Is A Quantum Simulator?

Before we understand quantum simulators, let’s understand what a simulator is. Simulators and computers are the devices that calculate mathematical questions. However, calling a physical technology or device simulator or computer depends not only on the device we use. But it also depends on what type of mathematical question you are supposed to ask and how you use that answer for further activities. When the interpreted part of the mathematical question is considered the portion of the physical model, it is more likely to be said as the simulator. Now we also need to understand quantum devices; quantum technology explains the dynamic structure of all the objects. It is developing concepts of physics engineering and a crucial part of studying quantum simulators.

Quantum simulators are explained as the technologies which allow studying the quantum system. That is extremely difficult to understand with current technologies.

Currently, scientists are putting their efforts into getting these simulators to use in supercomputers in their laboratories. With quantum simulators, they can do specialpurpose calculations designed to calculate extreme level insights about the specific questions of physics.

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Quantum Simulators Use Quantum simulators are used to reveal information about another real system that exists but is complex to explain. Although this world of complex physics exists and can be used for many purposes, we need to use the quantum simulator to use this concept.

With the accurately designed quantum simulators, the scientist can choose the ideal research model and add the area of interest they are willing to know. With the available information, these simulators can give output describing crucial insights.

Thus, it is the important use of a quantum simulator, which gives the information about

the research model and compares the same with the existing interest system. These simulators explain whether the solution for the given research is good and can benefit the real world.

The Fermi-Hubbard model is a brilliant example of a quantum simulator. The FermiHubbard model explains the transition between the conducting and insulating devices. It is essential because it can monitor or capture some properties of some high technology superconductors. However, if we developed a highly accurate simulator, we can have efficient use to enhance the current technologies.

These simulators are needed to understand complex molecules and have clear information about interacting with their components.

Why Are Quantum Simulators Needed?

The concepts of Quantum simulations are centuries-old. However, the suggestion to make quantum devices generally goes to Richard Feynman in 1982. He suggested that quantum simulators can be the better version of current devices. The current devices produce inefficient results for calculating the complex or large number of particles in the model. However, quantum simulators can solve this problem and can easily give brilliant insights into particle numbers.

It is not needed for the general use devices like our computers, mobile devices, and toasters.

But it is significant for the scientific and advanced research that can be used to make

advanced level calculations. These simulators are needed to understand complex molecules and have clear information about interacting with their components. However, current technologies cannot calculate advanced level computation because these technologies need to be fast and more advanced.

Therefore the scientists are pushing their limits to bring this brilliant concept into a grand reality.

How Can Quantum Computing Be Practical?

With the help of quantum systems, we can simulate another quantum technology as a simulator.

It will be easier to control and offer efficient results. Here are some use cases of quantum computing in the real world that can completely replace the current technology or update it for advanced research purposes.

1

It Can Help Advance Superconducting Components.

Do you know we lose around 10% electricity in transmission every day? If the world has quantum simulators, these technologies can transmit electricity with zero loss from one place to another. Also, current superconductors work if there is a -100 degree temperature. However, quantum simulators can transmit electricity if the temperature is high.

2

Quantum Computing Can Be Used For Medicines.

Many health experts have noticed that Huntington, Alzheimer’s, and Parkinson’s disease have some similarities. All three diseases are caused because of misfolded molecules of proteins. Quantum systems could be used to efficiently understand the ideal treatment for these diseases.

3

It Is Constructive For The Environment.

Once we precisely understand the quantum simulators or quantum dynamic reactions between the various chemicals, it can help save the world’s natural environment. With the help of quantum systems, we can have a solution to reduce or eliminate CO2, which is increasing rapidly. Also, it can help in making fertilizers by producing a high amount of vital energy. Hence, if we have accurate and efficient technology of quantum simulators, it can benefit the world in many ways.

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4

It Can Advance Spin Electronics.

The spin electronics or such devices use electrical waves and electrons to store and work with the data. Quantum simulators help in innovating and developing devices to make spintronics faster and more efficient.

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How Many Quantum Simulators Are Available, And What’s Their Use?

Presently, we have over 300 quantum simulators, and all of them are designed to perform several purposes. Here is a shortlist which contains a few names of available quantum simulators with their use.

QCIRCUITS

BRAKET

It is one of the quantum simulators designed for students and new candidates willing to know about quantum computing.

Braket is another quantum simulator managed by Amazon, and it can be used for developing quantum algorithms.

SILQ This quantum programming language comes with a safe uncomputation and intuitive semantics. Therefore, it is considered as the high-level QPL.

QUANTUM PROGRAMMING STUDIO It is a web-based quantum IDE and simulator which provides a drag and drop option to make a circuit.

It also has cross-platform functionality and supports Rigetti and IBM.

STAQ It is a toolkit designed to get used for full-stack quantum processing.

QISKIT Qiskit is supported with IBM, and this framework works for the noisy quantum computers used to measure the circuits, pulses, and algorithms.

CIRQ Cirq is the python framework created for editing, invoking, and generating NISQ circuits.

Conclusion Quantum simulation is a fundamental theory which exists for hundreds of years. However, still, we need to find one of the most accurate and practical aspects of quantum simulators. To use in making complex calculations more accessible and more efficient to help people in many ways. Currently, we have over 300 quantum simulators that are used worldwide for various purposes. Some of the popular quantum simulators are Qiskit, Silq, Staq, Cirq, and Braket. Braket is the service offered by Amazon, and it is used for building quantum algorithms. Most of these quantum services perform various quantum calculations, which revolve around circuits, algorithms, and another research model. So, in this article, we learned what quantum simulators are, how they work, and why the world needs this technology. We also learned how it could be helpful if it becomes practically possible to use.

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Arun is serial entrepreneur with a passion for technology and challenges.

Dinesh is a multifaceted serial entrepreneur with a passion for sales and marketing.

In Conversation with

Arun& Dinesh

Yottaasys AI Inc is an AI/ML and CV-based product Startup based out of MI’ USA. The core offering, 3i is a visual intelligence product that analyses visual data (real-time or stored) to provide business-specific insights via facial, emotional & dimensional intelligence.

3i helps in improving 2 core functional business areas:

1. EMPLOYEE EXPERIENCE

2. CUSTOMER EXPERIENCE

A modularized solution to monitor & manage employee satisfaction, performance, data compliance, cues while hiring and much more.

There are multiple modules that can add values & provide insights for key functions like CISO, CIO, COO, & HR in an organization.

Helps in empowering customer-focused brands and services to understand their customer preferences better through quick, low-cost unbiased research & analysis of a diverse set of customer group or target group while interacting with their product or service.

Dinesh

Arun

Dinesh is a multifaceted serial entrepreneur with a passion for sales and marketing.

Dinesh has co-authored books and participated in patents, Dinesh currently is discovering computer vision at scale by reducing latency while maintaining high accuracy and helping businesses to solve two of their most complex problems:

Arun is serial entrepreneur with a passion for technology and challenges. Arun has authored books, participated in patents, and won several industry/startup awards.

Retaining Happy Employees and Finding Customers for their New Products.

Along with his work, he loves to play badminton, tennis, swim and do yoga.

Q|

Can you share with us the story of your journey? How did you guys come up with the idea to start Yottaasys?

Arun and Dinesh: The name Yottaasys comes from Yottabyte, the largest amount of data on the bit scale; as we were always focused on computing and providing insights, the name perfectly resounded with our target. The seed of Yottaasys was planted during our COE experience; as part of the COE leadership team, we were researching the upcoming technologies and their impact on our ways of working and living. We have been working in the data science and business intelligence space all our lives, but during the COE experience, we saw the value addition and automation AI would bring to the table. We realized that AI is the new frontier and is going to change the way we do things; this was further accelerated by a challenge thrown by one of our respected mentors to create a worldclass AI product company from India; slowly but eventually, we took the challenge.

When we started, we wanted to create a setup that is exciting, meaningful, flexible, and focused (almost meditative in nature workwise) and hence Yottaasys.

When we started, we wanted to create a setup that is exciting, meaningful, flexible, and focused (almost meditative in nature workwise) and hence Yottaasys.

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Q|

Start-ups face a lot of challenges before they become successful. What are some of the biggest challenges you faced particularly being an ‘AI start-up firm’?

Arun and Dinesh: Our top three challenges were access to capital, ramping up a world-class deep tech team, and customer education.

Access to Capital: Until a few years back, it was hard to get funded as an AI product start-up; it took great efforts to convince investors about the possibility of a successful AI product start-up from India.

Only when we moved over to the US and other geographies did access to capital became less of a problem.

their businesses; it took a lot of our time during the early days. Only after 2020, our customers were ready to take the AI journey, and now it is happening so rapidly that we are finding it hard to keep pace with our pipelines.

We did not have a deep pocket to attract the best team members.

Hiring: Our second biggest challenge was hiring deep tech team members, especially in the full stack and data science area.

Captives and unicorns were throwing in money like anything (it has only further accelerated now), and we did not have a deep pocket to attract the best team members. Though it is still an open challenge, we have partially mitigated this problem by ramping freshers or 1-2 years experienced members and bringing in only a few highly experienced team members and empowering them with ownership.

Customer Education: The third challenge was customer education, first explaining AI to B2B customers then convincing them the value addition AI can bring to

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Q|

Facial recognition is one of the driving forces of the fourth industrial revolution. Can you talk about how Yottaasys’s recently launched deep learning-based product ‘3I’ would help businesses?

Arun and Dinesh: Talent retention in this global digital age is an equation that includes managing both productivity and employee happiness. This is where we see 3I playing a significant role in capturing Employee Micro Expressions and identifying Emotion Behaviour Patterns. The next big part we see 3I playing is improving customer experience, especially helping companies understand customer preferences better prior to a new product/service or a new variant of an existing product/service.

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Q|

The company’s products already cater to various domains including the Banking, manufacturing, BPO and Online EdTech sector. Are you planning on expanding further to any other verticals? What are your future goals?

Arun and Dinesh: Yottaasys is taking a totally disruptive approach. Rather than sector wise, we are taking a function-based approach. Our major goals include: 1. Enhancing Employee Experience 2. Enhancing Customer Experience

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Q|

Why did Yottaasys choose to address this industry problem of increasing Employee & Customer Experience?

Arun and Dinesh: Yottaasys, as a philosophy, has always believed that ‘Disruption is the key to deliver and impact the topline or bottomline’.

• As an organization, we felt rather than a sector-based problem; we needed to address it as a function. For us, disruption 38

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was the Key. By leveraging two of the most prevalent issues in the market, we were able to solve problems across all sectors.

This is where we are also creating value for the industry as a whole.

• While we are helping companies increase their bottom-line by keeping their employees happy, we are also impacting their topline by helping them understand their customer preferences.

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How does organizations use 3I to increase employee experience & customer experience?

Arun and Dinesh: Employee experience impacts the customer experience in more ways than one can realize. When companies focus on creating a culture and providing a great employee experience, it affects every aspect of the business, including the customer service that the employees deliver.

There are two things at play here. With the battle for top talent at an all-time high and people staying at jobs for shorter periods, recruiting the best and figuring out how to keep them around is a priority for HR and senior leaders for organizations of all sizes.

In addition, finding prospects, turning them into customers, and keeping them happy and satisfied is what makes businesses grow and prosper. There is a connection between the two, i.e., happy and satisfied employees lead to happy and satisfied customers.

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Yottaasys addresses this problem uniquely by providing AI-driven feedback loops and metrics on employee and customer engagement. We are grabbing every data element essential for the employee engagement area, be it data from the keyboard, mouse, browsing history, or visual data from the employee webcam. The data is captured in real-time and run through various deep learning and supervised models to get holistic metrics on employee engagement. Our automated data capture replaces the needs for surveys, discussions, and HR meetups.

We capture emotions from the visual data in real-time along with the distractions. By combining these avatars of input data, we can derive Top C level matrices (such as the general motivation levels) and other operational matrices (such as which event, time and instance act as a factor in enhancing or decreasing employee engagement). Finally, we also provide APIs that can help integrate these data predictions with the traditional ERP, CRM, HRMS and obtain C-level summaries on employee and customer engagement.

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According to reports at least 2.5 quintillion bytes of data are produced every day. It is extremely challenging to go through this pool of data and feed AI models to create predictive models. How do you and your team deal with this massive pool of data to predict production delays?

Arun and Dinesh: We would like to divide the answer into two sections for this question; these sections are current and future:

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Current: Instead of focusing on the quantity of data, our focus is on the quality of data; we have a few of our mutually agreed customer sources that continuously feed data to us. Our modules, such as deep optimizer filters, enhance and select meaningful data, automatically label them, and then feed them to our models. So instead of a brute force approach, we have a more efficient qualitative approach for handling data.

Future: We are working on something which is fundamentally very different; right now, the entire math behind AI is driven by the physical aspect of our mind/brain. Now our mind is multi-dimensional; there are many other aspects to the mind which are dimensionally different from the physical nature of the mind.

These dimensions help us with capabilities such as intuition, imagination, creativity etc.

Internally we call this domain CI (Conscious Intelligence); we are a work in progress in defining the fundamental math, logic, and models needed to support CI.

This is one area for which we will need lots of capital, and we are working on it.

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Q|

Can you suggest some of your favorite books on AI for our readers?

Arun and Dinesh: We would like to divide the books into two categories: foundation, which is for future aspirants of AI, and progressive, which is for the C-level executives who want to leverage AI for their business.

A. Foundation: 1. The Elements of Statistical Learning

by Sir Trevor Hastie, Robert Tibshirani and Jerome Friedman 2. Python Machine Learning by Sebastian Raschka www.techfastly.com

3. Machine Learning Certification by Stanford University (Coursera) 4. Articles on Medium, especially by writers like Adam Geitgey, Jason Brownlee, and others.

5. Anything and Everything by Sir Jeremy Howard (Founder of fast AI and a true guru in all aspects).

6. Yottaasys AI Ramp up Content (we will be releasing it as an open-source very soon)

B. Progressive: 1. The Book of Why: The New Science of Cause and Effect by Judea Pearl and Dana Mackenzie 2. How to Create a Mind: The Secret of Human Thought Revealed by Ray Kurzweil 3. The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind by Marvin Lee Minsky

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A strong understanding and bonding between the co-founder team is crucial.

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Q|

Finally, could you share some tips on leadership, start-up struggles, and maintaining a positive outlook through it?

Arun and Dinesh: We would say a strong understanding and bonding between the co-founder team is crucial.

The core of any startup is the trust factor which can either break or make a company.

After this, we would say the other qualities for a successful startup will be:

1. Being Passionate and Resilient As both go a long way to sustain the constant challenges that one faces in a startup environment.

2. Persevere It’s very important in a startup to move an extra mile and never give up.

3. Transparent Extremely transparent and being candid about accepting mistakes.

4. KISSES (keep it Small, Simple, Empowered, and Short) is a key ingredient of our leadership ideology: 4.1 SMALL: We always believe in small teams for all our functional units. Too many people in anything creates lots of communication, dedication, and ownership challenges.

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4.2 SIMPLE: There is a lot of complexity in what we do on a day-to-day basis, so it’s our responsibility to create an execution plan which is extremely simple and logical.

We truly believe in the saying,

“Any intelligent fool can make things bigger and more complex. It takes a touch of genius - and a lot of courage - to move in the opposite direction.”

– Albert Einstein

4.3 EMPOWERED: We honestly believe in picking the best and empowering them to take risks and decisions related to executing those risks. We deeply emphasize the importance of leading from the front, which means the leadership team should code or do sales calls, especially when their respective teams are finding it challenging.

4.4 SHORT: Our conversations, meetings, emails are always short and very much to the point. Our experience has been that lot of times, meetings are actually corporate-sponsored pastimes and can be dangerously unproductive, so we have kept our meetings to a minimum. We follow meditative conversations, which means if you are not clear in your head about an item and cannot define it in 3 lines, don’t call in others for a meeting or conversation.

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Quantum Entanglement A New Era of Particle Interaction by Bhumika Dutta

A

ny technology enthusiast must have heard about Quantum Computing by now since it has caused a massive upheaval in the technological area and has had a significant influence on numerous industries.

For those who are unfamiliar with quantum computing, it is a branch of computing that creates technologies based on the concepts of quantum theory.

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Quantum theory is a fascinating field of study and research because it deals with the behaviour and energy of materials at the atomic and subatomic levels.

Incorporating quantum physics into computing has resulted in one of the most exciting disciplines of research to date.

A quantum network is an essential and powerful tool of quantum computing, as it connects with quantum data stored in the form of individual photons. Quantum networks, by utilizing the intrinsic power of quantum states, might allow innovative approaches such as: physics-based unhackable security, more powerful quantum computers that can accomplish jobs that would normally take years, and networks of entangled quantum sensors.

The idea of quantum entanglement emerges from this. The initial function of a quantum network is to spread entanglement, but first, we must define the term. As we all know, ‘bits’ 48

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hold classical or non-quantum data. Qubits are a comparable probabilistic quantity of quantum data. When two qubits connect, their probability distributions interweave, and they become reliant on one another—this aids in comprehending the measurement of one qubit by examining another in the relationship. Entanglement refers to this type of relationship or association, and a quantum network is used to distribute entanglement across the globe through different processes.

But what is the objective behind this distribution? Entanglement gives the users the advantage of using the correlations to innovate new applications that were otherwise not possible with classical data, thus allowing global Entanglement as a Service (EaaS).

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How Does EaaS Work?

EaaS, or Entanglement as a Service, is a cutting-edge technology that connects users of quantum networks with entangled qubits (quantum bits) over vast distances via quantum repeater networks. Quantum networks will enable new services, ranging from ultra-secure communication to highperformance computing (HPC). We will talk about quantum repeaters in a bit.

EaaS is completely dependent on the internet, and even though it works on a simple concept, it might be a little hard for the users to grasp.

To understand EaaS better, let us look at the process behind any applications of the internet. The internet’s core service is just transmitting data from point A to point B. Because the internet allows computers to

connect with one another, data is transferred in the form of bits. The internet has divided communications into packets that are made up of bits. Packet switching enables the internet to handle huge amounts of data.

So, what is the process that the quantum internet follows to provide its fundamental service? As discussed earlier, quantum entanglement provides correlations between qubits that can be used for many purposes.

For basic communication, teleportation or transportation of qubits can be done.

In addition, entanglement can be used for applications that are not possible through today’s internet. Quantum networks can use entanglement to enable an encrypted connection in which information is conveyed 49

using entangled qubits without ever needing to transmit it over a potentially hazardous network. Furthermore, entanglement may be used to build even bigger quantum computers via distributed quantum computing.

But what is the role of EaaS in this?

A quantum networking company called Aliro Quantum is advancing its efforts to develop quantum EaaS. As Jim Ricotta, the CEO of Aliro, said,

“If you entangle two photons and someone makes a change to photon A, another person can observe that change at photon B, because they’ve been entangled; it’s the law of physics. But it’s invisible to the naked eye.”

Quantum networks work by entangling photons with data, which may then be encoded and sent through the same groundbased telecom fibre that is already in use.

Entanglement enables the safe transportation of qubits, which carry quantum information.

Thousands of such entangled photon pairs must be produced each second in order to yield significant information. The bandwidth of these connected photons is comparable to that of a regular network. We are still in the early stages of quantum computing, and in the future, unfathomable applications will be created on quantum networks.

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What is Quantum Internet?

In the above discussion of EaaS, there have been many mentions of Quantum Internet.

The quantum internet is a network that will allow quantum devices to exchange data in an environment that uses the strange principles of quantum physics. In principle, this would provide the quantum internet with new powers that are currently difficult to achieve with web apps. Qubits may be transmitted over a network of physically isolated quantum devices with the assistance of quantum internet.

This all might seem similar to standard internet; then why do we need quantum internet? Transmitting qubits over a quantum channel rather than a conventional one basically implies exploiting particle behaviour at its lowest scale — so-called “quantum states.” Interestingly, qubits cannot be utilized to convey data that we are accustomed to, such as emails and WhatsApp messages.

However, qubits’ unusual nature is opening up tremendous potential in other, more specialized applications.

What are Quantum Repeaters?

Now that we grasp the significance of quantum internet in sending quantum data over great distances, we must learn about quantum repeaters, which serve as the key to unlocking the services of the quantum internet. The work of the standard repeaters is to measure the signal coming in from one side, copy it, and retransmit it to the other side at a greater power level. As a result, the quantum internet can safely transport data across very vast distances. But this cannot be done for quantum information, as quantum information cannot be copied due to the no-cloning theorem.

We cannot evaluate quantum states as they travel from point A to point B without destroying them. Although this gives some of the incredible benefits of quantum communications, such as ultra-secure communication, it also implies that we

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can’t utilize the same notion from conventional repeaters to avoid loss in quantum channels. To avoid this loss, we use quantum repeaters.

To deal with the problem of loss, quantum repeaters employ a totally different technique than conventional repeaters.

The central concept is based on the entanglement switching approach.

The fundamental objective of quantum networks is to disperse entanglement across network members. Entanglement distribution enables a wide range of applications, including the transmission of qubits.

Entanglement switching is a smart solution to the problem of loss that does not violate the no-cloning theorem.

Final Words Although there are currently no commercially manufactured quantum computers, quantum computing is widely utilized since it is far more powerful than normal computing and is employed by large corporations such as IBM, Rigetti, Toshiba, IonQ, and many more for Big Data analysis or simulations. Although complicated, quantum computing is extremely safe for transactions and many times quicker than conventional computation. At the 2019 IBM Summit, Google’s quantum computer, Sycamore, did a computation that was 158 times quicker than the world’s fastest computer. However, quantum computers are extremely costly to create and are not available to everyone. Hopefully, as the field advances, it will be freely accessible to individuals at a fraction of the present cost.

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Do Quantum Batteries Ever Run Out of Charge?

by Zahwah Jameel

W

ould you believe me if I told you that there’s a possibility of the creation of a battery that would never lose charge?

Quantum batteries sound like stuff from sci-fi novels, but they are batteries that never run out of charge.

They would come as a blessing to our digital world filled with electronics, where almost everything around us runs on energy.

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What is a Quantum Battery?

A quantum battery is a hypothetical concept that charges faster than standard chemical batteries. They charge when the qubits gain a higher energy state, and the battery loses charge as the qubits fall to lower states.

Qubits are quantum bits that form the fundamental blocks of quantum theory.

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In a way, these quantum batteries will change the way we operate our electronic devices, like PCs or phones, because they would never require charging. It would also make electric cars more accessible since there would be no charge, making them more cost-effective.

These quantum batteries would also help our environment in numerous ways since the lithiumion batteries we use these days generate heaps of waste. A battery that doesn’t run out of charge wouldn’t cause any non-biodegradable waste, making our surroundings cleaner.

How does a Quantum Battery Work?

The quantum batteries work on the basic principles of quantum mechanics, a branch of quantum physics that studies the physical properties of nature at the scale of atoms and subatomic particles.

So, how does quantum mechanics help these batteries achieve such long shelf life?

contain five layers - three conductive (metal or semiconductor) and two insulator layers ordered in a sandwich-like structure. This structure will ensure that the batteries do not lose charge and can last for years and which the scientists describe as the battery being “highly robust to energy losses.”

According to quantum mechanics, all matter either moves as waves or particles. Scientists have thought about using an open quantum network, a structure in which they can store excitonic energy. Excitonic energy is the power harnessed when an electron absorbs an energetic photon of light.

With this model, there will be no energy loss despite the battery being in an open environment. These batteries will be flowing with electrons that must be contained inside a “dark state” so there is no energy loss since the system can’t exchange energy with its environment.

In essence, the system becomes immune to all environmental influences, which will ensure that these batteries always remain fully charged. This “dark state” will (presumably) 56

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Do Quantum Batteries Exist?

Although quantum batteries aren’t yet a reality, many scientists have come up with theories about creating one, but they aren’t getting any viable ways in which we can test it out.

A team of scientists from the universities of Atlanta and Toronto carried out research where they created a blueprint that lists the above ways to harness the power in a quantum battery. More specifically, it’s possible by the storing of excitonic energy in a dark state. A principal investigator of the study Gabriel Hannah explained that a quantum

battery is a nano battery meant for nanoscale applications. This means that even if created, the public won’t use these batteries for a long time since the technology is still relatively new, and putting it for use by the public would lead to severe problems.

Scientists are still trying viable ways to use these batteries since making these batteries is a challenging task. Still, since they have already come up with a blueprint, it won’t be long before they create one in their labs but thinking that the public would use it is not possible soon.

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Graphene vs. Quantum Batteries A new generation battery that has been in the news has been the graphene battery which is a kind of battery that practically charges almost instantly and delivers very high currents.

Graphene is a material that is a sheet of carbon that is just one atom thick. This makes graphene a supercapacitor that stores current just like a traditional battery but can charge and discharge incredibly quickly.

Therefore, these batteries would make charging our smartphones a piece of cake, and it would also mean that large devices like

GRAPHENE BATTERIES

QUANTUM BATTERIES

an electric car would get charged in no less than 30 mins.

So, if we go through this definition of a graphene battery, it gives tough competition to quantum batteries. It also comes as a lasting blow that graphene batteries are more likely to be used sooner since they will be released to the public by 2024, whereas quantum batteries still exist in theory.

But the quantum batteries have the upper hand since they would practically never run out of charge while graphene batteries would need recharging regularly.

Made from single sheet carbon.

High probability of using these in the future

Require charging at short intervals.

Made wholly based on quantum mechanics.

Only exist in theory, so there is no probability of using them shortly.

No charging is required

What the Future Holds for Quantum Batteries So, are quantum batteries the future of batteries?

Yes, if scientists can produce it needs to be practically applicable for the real world.

Since the batteries would need production in controlled environments, mass production would prove a difficult task. But if we look at the state at which technology is advancing,

it would be safe to say that quantum batteries will be a reality no sooner than later.

Send us the topics you want us to explore. contact@techfastly.com

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In Conversation with

Surbhi Rathore CEO and Co-founder of Symbl.ai

ABOUT

Surbhi Rathore is the CEO and co-founder of Symbl.ai.

Symbl.ai is bringing to life her vision for a programmable platform that empowers developers and businesses to monitor, act, and comply with voice, video conversations at scale in their products and workflows without building their in-house data science expertise.

This Techstars alum co-founded Symbl.ai almost 3 years ago and is now backed by Amazon and has raised an early-stage venture round of $6.5M which deployed capital to grow a global team of tech enthusiasts to more than 50 people. She comes with experience from technical and customer-obsessed roles in both startups and enterprises such as Nevis Networks and Amdocs. Before co-founding Symbl.ai, she worked in the Conversational AI space with a focus on delivering value to Telecommunication users. Surbhi is an international tech leader who advocates for Women in AI with a personal mission to inspire more women to work in Data Science. She is a national speaker, and accessibility equity champion, and the ultimate adventure capitalist.

Surbhi has been honored with the Women in Voice Award for Founder of the Year, Amazon’s Top 10 Women to Watch in 2020, and the Will Reed Top 50 Companies in 2021.

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Q|

Let’s start with what is Symbl.ai?

Symbl.ai. is an API-first Conversation Intelligence platform that enables developers to analyze, monitor, comply and act on the voice, video, or text conversations in their products or workflows. We like to refer to ourselves as “Conversation-as-a-Service’’ that empowers businesses to build nextgeneration communication experiences and unlock the potential of conversation data without investing heavily in building the AI/ML infrastructure.

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What excites you most about conversational intelligence and what inspired you to start Symbl.ai?

I have always been interested in building software products and platforms that operate with conversations at scale. I have seen firsthand so much information and knowledge getting lost and not used rightly as a function for the growth of businesses. I am passionate about making this technology accessible to more builders so that we can push the boundaries of the adoption of conversation intelligence in the ecosystem and generate shared knowledge.

Could you talk about Symbl.ai’s patented context understanding engine, and how it helps you to stand out in the market?

action items, topics, trackers, summary, and much more. We also offer several speech-totext capabilities like transcription, speaker separation, and speaker diarization in realtime as conversations happen or after they are completed.

Symbl.ai is a one-of-its-only-kind end-to-end conversation intelligence platform built to leverage our patented context understanding engine. The platform works with multichannel data i.e., voice, text, and audio to provide capabilities like sentiment analysis,

Symbl.ai stands out from the rest because we provide solutions for simple and complex use-cases alike. Our out-of-the-box solutions such as action items, follow-ups, topics, questions, speech-to-text, can be used

Q|

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upfront while our programmable features such as trackers and conversation groups can be optimized to suit complex implementations tailored to a specific domain or use-case.

We’re at the dawn of conversational intelligence and only just scratching the surface.

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How can companies benefit from solutions like Symbl.ai?

Symbl.ai offers a suite of APIs that help companies build their own low-cost call tracking, compliance, and coaching solutions at a scale that they can go live in just 2 weeks!

Organizations that have huge business conversation data that is unstructured and unruly, can benefit largely from Symbl.ai. to search and index conversations, moderate content, redact, comply and detect profanity, understand characteristics for coaching, track conversation characteristics and automate workflows.

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According to you, what is the future of conversational intelligence?

We’re at the dawn of conversational intelligence and only just scratching the surface. There’s tremendous potential in how human conversations will be utilized to bring in predictability and automation in solutions that have a very personal touch.

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Since conversational intelligence is an emerging technology, what are the challenges in this space, and what worked for you to overcome some challenges initially?

Human conversations are by nature messy. The biggest challenge has been to understand underlying patterns, recognize anomalies, and design models that can intuitively understand the context and extract insights that have business value.

Building a context-aware platform that works horizontally on any conversation 63

while enabling developers to build their own domain-specific intelligence was the key here. Working with early customers and involving feedback loop as part of the early product development lifecycle, specifically for emerging technologies is one of the key factors in iteratively getting to product-market fit.

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What is the current growth of the company and existing customer base?

We opened our platform in general availability last year mid-covid that also led to the fueling the adoption of digital communications and what comes beyond. We are excited to work with thousands of developers building on our platform and trusted by businesses from small startups to enterprises like Yac, Airmeet, Racket, Intermedia, SpectrumVoip, and many more.

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How do you see Symbl.ai’s future and its growth?

We plan to become the operating system for the modern communication stack. With our end-to-end, context-aware conversation analytics and management platform, Symbl is set to become the intelligent workflow automation engine for the language-enabled enterprise.

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Which of the few (three of four) emerging technologies do you find the most promising and why?

In addition to speech and NLP which are my core passion areas, I am excited to follow the maturity and adoption of VR and wearable technologies. I look forward to conversation

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intelligence at an intersection of these emerging tech.

Q|

Can you share some tips for young entrepreneurs?

Marketing in the early stages of the company can be hugely valuable - get a marketing cofounder.

Invest in building your content engine early and share your hypothesis out there.

There is so much value in pushing your knowledge out there early - it will only come back!

Q|

What is the best way to get in touch with the Symbl.ai team and learn more?

You can follow us on Twitter, LinkedIn or directly write to me - surbhi@symbl.ai. I am always happy to huddle and discuss use cases, brainstorm implementations for your voice-enabled experiences. We also have an active community on Slack for one-andall. Please feel free to join us here: https:// symbldotai.slack.com/ssb/redirect#/ Additionally, you can visit our website: https://symbl.ai/ and read through our docs: https://docs.symbl.ai/. to understand more.

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Changing Dynamics of Healthcare Sector - Quantum Computers Taking A Leap

by Rehan Husain

Quantum computing is a trend right now. The concept of supercomputers working at speeds unimaginable by today’s computers has been around for a long — and while it may seem like science fiction, it is incredibly near to (if not already) becoming a reality.

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Q

uantum computing radically changes how we think about the digital world, the world of 0s and 1s, and how data is conveyed in real-time. It also makes grandiose promises of change and revolution – from one industry to the next, from one sector to the next, and from one area to the next. Quantum computing promises to open new possibilities for quicker, more agile, almost dreamlike efficiency in everything from finance to problem-solving and corporate operations — and healthcare is no exception.

But, to fully comprehend the influence quantum computing might have on the field of healthcare, it’s necessary first to understand how quantum computing works.

You might be wondering how quantum computers vary from the computers you’re

familiar with. It turns out that the distinction between the two is rather significant.

Ordinary computers work based on certainty: everything is black or white, and data is represented as a series of bits, or 0s and 1s. The bits in today’s computers can only have two states: 0 or 1. Because of its dual character, the system is sometimes referred to as binary.

The situation with quantum computers, on the other hand, is somewhat different.

Quantum computers work in the opposite way that traditional computers do: they rely on process uncertainty and probability. Quantum computers employ qubits instead of bits, which may be in many states at the same time.

Instead of having a distinct location, qubits might be either 0 or 1 or both, a phenomenon known as “superposition.”

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Insights Traditional computers process data in a fundamentally different way than quantum computers.

Prior developments in computer technology, such as integrated circuits, allowed for quicker computation, but they were still dependent on traditional information processing. Quantum computers are capable of manipulating quantum bits (qubits).

Unlike conventional bits, which can only store information like 0 or 1, quantum bits can exhibit unique quantum characteristics like entanglement. Consequently, quantum algorithms that can outperform their classical counterparts that can’t make use of quantum events may now be built.

Quantum computers may be very effective in solving problems involving: – Chemistry, machine learning/artificial intelligence (AI), optimization, and simulation challenges are possible options. In reality, quantum computing has the potential to improve machine learning, and the two are working together to accelerate quantum progress.

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Complex interdependencies and correlations among a large number of highly linked components, such as molecular structures with numerous electrons interacting

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Scaling limitations of applicable classical algorithms are inherent. For example, when modeling the temporal evolution of quantum systems, the resource needs of conventional methods may grow exponentially with issue size.

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Using quantum computers in conjunction with conventional computers in healthcare and other industries is expected to provide significant benefits that classical computing alone cannot provide. As a result, a race to develop quantum applications has begun. Three important quantum use cases that are crucial to the healthcare industry’s continuing transformation are as follows: 1. Appropriate diagnosis: Diagnose patients quickly, correctly, and effectively.

2. Precision medicine: Personalized interventions/treatments keep individuals healthy.

3. Insurance premiums and price optimization

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Appropriate Diagnosis:

Diagnose patients quickly, correctly, and effectively

Diagnoses made early, accurately, and efficiently typically result in better results and lower treatment costs. When colon cancer is detected early, survival chances rise by a factor of nine, and treatment expenses drop by a factor of four. At the same time, existing diagnostics are difficult and expensive for a wide variety of diseases.

Even after a diagnosis has been made, estimates show that it is incorrect 5–20 percent of the time. Over the last century, medical imaging methods such as CT, MRI, and X-ray scans have become critical diagnostic tools for practitioners. Methods for computer-assisted identification and diagnosis of medical pictures are constantly evolving. At the same time, noise, poor resolution, and limited replicability affect many of these pictures.

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The necessity to follow stringent safety standards is one of the causes of these difficulties. Quantum computing has the potential to enhance medical image analysis, as well as processing stages like edge detection and picture matching. These enhancements would vastly improve image-assisted diagnosis. Furthermore, single-cell techniques may be used in current diagnostic procedures. Flow cytometry and single-cell sequencing data, in particular, sometimes necessitate complex analysis approaches, especially when integrating results from multiple techniques.

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Precision Medicine:

Personalized interventions/ treatments keep individuals healthy

Precision medicine attempts to personalize preventative and treatment plans for each patient. Individualized medicine necessitates considering elements that go much beyond traditional medical care due to the complexity of human biology. The interdependencies and correlations among these many components provide daunting computational hurdles in terms of improving treatment efficacy.

As a result of this individual heterogeneity, many current treatments fail to reach their intended benefits. Only a third of patients react to drug-based cancer treatments, for example. Medication treatments can have devastating results in some circumstances; up to 200,000 people die each year in Europe owing to severe drug responses.

Proactivity is an essential component in tailoring medical treatments.

Early treatments and preventative interventions, as previously stated, have a solid tendency to enhance outcomes and save costs. Based on EHRs, traditional machine learning has shown the potential to forecast the risk of future illnesses for various patient categories. However, problems remain due to the characteristics of EHRs and other health-related data, such as the degree of noise, the extent of the relevant feature space, and the intricacy of relationships among the features. This implies that quantum-enhanced machine learning approaches, both supervised and unsupervised, may be able to provide earlier, more accurate, and granular risk forecasts.

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Insurance Premiums and Price Optimization

The method of determining health insurance rates is complicated. In creating a general pricing strategy, a health plan must consider several variables.

area, developing more granular models with reduced uncertainty remains a challenge. Risk analysis is one central area where quantum computing might assist in optimizing pricing.

Complex interdependencies such as population health levels and disease risks, treatment appropriateness and costs, and the risk exposure a health plan is willing and able to tolerate based on business strategy and laws are among them. While traditional data science approaches have helped health plans make significant progress in this

Quantum computing might aid in determining a patient’s risk of developing a specific medical ailment. Health plans may enhance risk and pricing models by integrating these insights about illness risk at the population level with quantum risk models that can compute financial risk more effectively.

Potential Applications: In the era of quantum computing, healthcare companies are projected to gain significant commercial and scientific benefits. Aside from the advantages listed above, this powerful technology may also provide other benefits, such as recruiting people interested in working with next-generation technology.

Early movers are expected to profit from quantum advantage, which is likely to be proprietary. Healthcare businesses can have the following potential applications: Enlist the help of quantum champions.

Identify, empower, and employ quantum advocates in your business, including IT and healthcare experts. They can act as a focal point for bridging the gap between quantum knowledge and healthcare needs. These quantum champions remain current with

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quantum advancements and push quantum initiatives inside the company.

Investigate and prioritize. Examine possible quantum use cases and rank the ones that will have the most impact on your company. This includes figuring out where quantum computing fits into your business and technological plans. Update your prioritized use cases over time based on the most recent company strategy and quantum computing advancements.

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Experiment with actual quantum computers and implement critical quantum applications. This will help you to get a quantum advantage while also providing hands-on enablement to your staff. These actions should be taken in a step-by-step

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manner. Joining a quantum ecosystem, a community of industrial and technology participants that share risks and profits in pursuing similar quantum computing goals can help you achieve them faster.

Conclusion Overall, quantum computing’s processing capacity opens the door to a goal that the healthcare and pharmaceutical sectors have long coveted. Instead of being reactive and delayed, the objective is to be proactive and preventative. While today’s most advanced technology enables the treatment of a wide range of ailments, quantum computing and its tremendous capability may one day allow for the prediction and successful removal of such conditions. The volume of data created daily and the quantity of particular patient data currently accessible will provide fertile ground for quantum machines to work and offer important and in-depth analyses that will aid in curing and avoiding illnesses.

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Quantum Computing’s

DISRUPTION IN Finance Industry

by Vibha Soni

Did you know that global quantum computing is expected to reach $411.4 million by 2026? Global Industry Analyst Inc. (GIA)’s study shows that quantum computing has already brought changes in the market post-COVID-19.

The drastic transformation demanded by the pandemic in banking & finance, healthcare, transporting, space, defence, and other sectors has given an edge to the quantum computing market. Google has already got a quantum computer that can perform a calculation in 200 seconds only, while a traditional supercomputer would need 10000 years to solve the same problem.

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Two main characteristics of quantum computers,

SUPERPOSITION, AND ENTANGLEMENT do things simultaneously and can transform anything.

Because of high performance and speed, quantum computers can run complex algorithms and simulations. This feature is rising the quantum computing usages in various industries, especially finance.

Various Aspects Related to Quantum Computing and Finance Let’s discuss what problems took the attention of experts to initiate uses of quantum computing, how quantum computers are assisting the industries in solving their complex issues, how the industry is benefitted after adopting quantum computing, and if any banks are using and benefitting from it.

Why does finance/banking need high power quantum computers?

Do you know, a quantum computer needs 1.3 hours (10 12 steps) to run a million operations per second using a quantum walk algorithm, whereas a classical computer needs 5 billion years (10 29 steps) to run trillion operations per second using a best classical computer or a cluster computer.

Globalization within finance industry has tremendously increased the number of daily business operations. Banks are expanding their networks and services around the world. Ordinary people become dependent on mobile banking, internet banking, and digital transactions. More than 50% of financial transactions occur over the internet today.

The applications of big data, artificial intelligence, and the cloud in finance have been improving with time. It is not only bringing transformation but also bringing challenges in different applications: investment banking, asset management, corporate banking, and retail banking.

Classical computer features provide ordinary business solutions. It’s one main limitation: “Doing one operation at one time” has been decreasing its usages. Solving real-world banking problems need high power and time. Classical computers can’t solve this intractable problem, but quantum computers can do that more accurately and faster.

Simulation, Machine Learning (ML), and optimization are the three most common concepts used in finance to implement various financial services and operations.

All these support banks in different aspects

including, risk management, economical pricing instruments, finding the best investment strategy, managing cash in ATM networks, capital management, credit scores, and fraud detections.

A recent paper, “Quantum Computing for Finance: State of the Art and Future Prospects” published in 2020 has highlighted problems, benefits, and various challenges.

The authors of the paper have also pointed out the issues in these three categories.

The following table shows multiple problems during the stage of the customer life cycle:

Customer life cycle

Simulation problems

Optimization problems

Machine learning problems

Customer identification

How to obtain new revenue sources?

How to improve supply chain efficiency, minimize risks, avoid late payment, and enhance liquidity?

Refining customer ratings, KYC, and how to avoid noncompliance annual penalties.

Financial products

Better management of value at risk, balance sheets, etc.

How to reduce operation costs, capital requirements, and systematic risks?

How to perform non-performing loan, improve recommendations systems, and customer retention?

Monitor transactions

How to optimize risk using a more precise calculation process?

How to keep relevancy in the portfolio based on market changes?

How to assess false alerts and suspicious notifications?

Customer retentions

How to improve risks analysis?

How to avoid customer churns?

How to maximize customer engagement?

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In short, dependency on classical computers for the execution of operations linked with optimization, prediction, and simulation is not a good idea. Because it needs high power and high performance, and classical computers are unable to provide both. Finance industry needs supercomputers like quantum computers to process accurate data within seconds.

Various algorithms and methods have been used to provide specific solutions based on each problem. For instance, sampling methods are the best way to resolve the simulation problems as quantum computers need fewer samples than classical samples.

Similarly, other algorithms have been used along with quantum computers to solve problems related to optimization, simulation, and machine learning.

In a recent live discussion, a panel of experts discussed the value of quantum computing, quantum strategies, and the industry’s quantum readiness to adopt it. SGInnovate had initiated the session with the support of the High Commission of Canada.

Quantum computers have the potential to solve real and complex problems by offering better solutions.

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Positive Impacts of Quantum Computing After discussing the problems and understanding that quantum-based solutions can solve these real-world banking problems, you can measure the benefits of quantum computing in finance.

Here are some of the benefits quantum computing could offer the finance industry: Reducing regulatory penalty costs Avoiding human labour Improving customer retention, interaction, and satisfaction

Increasing financial activities so fast

Improving cash flow

Reducing capital needs

Offering new investment methods Effective risk identification and management IBM has also pointed out these benefits after adopting quantum computing. The company has classified the use cases for finance industries into three areas: targeting and prediction, trading optimization, and risk profiling. We can consider these benefits, a positive impact of quantum computing, which lowers the risks in finance industry because of uncertainties.

Side Effects of Quantum Computing in Finance Cryptography is a well-known security method in finance. Symmetric keys, asymmetric keys (public keys), and hashing cryptography algorithms have protected sensitive banking data and provided integrity security checks.

All these are unbreakable and secured if it is used through conventional computers and advanced hardware systems. Although, the same security algorithms become vulnerable and risky if superpower quantum machines would use them.

The quantum computer’s one characteristic: solving mathematical problems exponentially faster than the conventional computer, makes the standard cryptographic algorithms outdated and reduces the strength of public keys and hashes. In other words, a quantum computer is threatening the most regulated industry and asking to compromise in all aspects: client data, software/websites used for transaction and interaction with clients, and hardware that perform authentications during the payment process.

post-quantum cryptography program has been chosen as the first standard to counter quantum decryption threat. This global effort would support overcoming the challenge of quantum threats.

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The leading magazine, Global Banking and Finance Review has pointed that quantum computing threat to cybersecurity. The National Security Agency had already warned of this quantum computing threat in 2016.

After this, the agency has started researching new encryption algorithms and data protection methods to defeat the quantum threat. After spending four years, the National Institute of Standards and Technology’s

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How Are Real Banks Leveraging Quantum Computing You have already seen how diverse segments in banking & finance have increased not only data & operations but also realistic problems.

When realistic banks found that investment in quantum computers and technologies could solve the intractable problems, they started making decisions. To date, many banks have already leveraged quantum computing to make their complex computing easy.

The leading global resource about quantum technology, The Quantum Daily, has revealed how 11 global banks have adopted quantum technologies. The list covered banks in US, UK, and Japan. JPMorgan Chase & Co., HSBC, Citi group, Barclay, Goldman Sachs are some names of those financial services firms. Some of them are in the initial stage of quantum programs, whereas some banks have completely adopted to quantum computing methods. According to their study, quantum technologies can solve problems like portfolio volatility optimization and value at risk calculation.

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The Royal Bank of Canada (RBC) announced a $1.78 million investment for developing advanced cybersecurity systems and privacy tools in 2018. www.techfastly.com

Group have already declared this company a world leader in quantum computing service offering.

The company brought Singularity, the first quantum & quantum-inspired toolbox for this industry. Recently, the company has resolved a real-world problem, dynamic portfolio optimization, faced by Bankia using D-Wave quantum computers. We can say the problem was known as quantitative finance in simple language, and classical computers could not resolve it. The experts find an optimal trading trajectory for an investment portfolio of assets over time by considering constraints and account transactions.

Final Thought

The study is taking place at the University of Waterloo. An enhanced education program, CrypotWorks21, is a part of this research to bring post-quantum cryptosystems to their bank.

Multiple companies and working groups are developing quantum computing systems to support the finance industry. The working group, Multiverse Computing, is one of those companies that has already acquired working experience with various banks like Bankia, BBVA. The big names like Forbes, McKinsey, IBM, The Economist, and Boston Consulting

Various experts have declared that the era needs quantum computing to solve intractable problems faster. The director of the Quantum Alliance Initiative, Arthur Herman, has also highlighted that Q-Day is on a threshold, and it is taking place of classical computers in his recent article. Here, Q-day refers to a term when large-scale quantum computers can easily calculate prime numbers used in public encryption systems to protect sensitive data of banking, finance, and other significant sectors. Implementing quantum-based solutions is a time-taking and complex process. Multiple software and interfaces are available in the market, which might confuse experts; thus, experts must understand the specific problems first.

And then decide the appropriate quantum application to solve the problem. They must be ready to handle challenges as soon as quantum-based solutions would take place at a high level.

Google’s Time Crystal Venture

Using Quantum Computers

by Toulika Das

Scientists at Google has claimed to have discovered a ‘Time Crystal’, something that could be a breakthrough in the realm of quantum computing.

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Imagine sitting inside a cafe,

waiting for your order. As you proceed to enjoy your coffee, you suddenly notice that the milk and cream that you asked for, aren’t mixing. The cream just sits on top. You might stare at it in wonder, thinking what was happening. Some of you may even begin to process this fact as a contradiction to the second law of thermodynamics - the inevitable tendency of matter towards achieving thermal equilibrium.

Something similar has been claimed by scientists at Google as they claim to have discovered a ‘time crystal’, something that could be a breakthrough in the realm of quantum computing. In this article, you’ll get to know about the concept of a time crystal in quantum computing and what exactly the Google scientists are claiming.

What Do Scientists at Google Claim to Have Discovered?

As per sources at ZDNet.com, Google scientists claim to have utilized a quantum processor for a beneficial scientific application:

Seeing a real-time crystal.

This news was published in Google’s latest pre-publication research paper, which is yet to be peer reviewed.

Google researchers claim to have demonstrated a real “time crystal” using Google’s quantum computer in conjunction with scientists from Stanford, Princeton, and other universities. In addition, earlier in July 2021, a different scientific group claimed to have produced a time crystal in a diamond.

First, let us get a clear picture of quantum computing and understand what a ‘time crystal’ is.

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A Brief Description of Quantum Computing Quantum computing is the study of using quantum physics events to create new computational methods. ‘Qubits’ are the building blocks of quantum computing. Unlike a regular computer bit, a qubit can be either 0 or 1, or a superposition of both 0 and 1.

Quantum properties such as superposition and entanglement are utilized to perform quantum computation.

Quantum computers can be really beneficial whenever we need to discover anything in a vast amount of data. Most scientists describe the uses of quantum computing as “finding a needle in a haystack”, whether it’s the correct mobile number or something else. Another example would be finding two equal integers in a vast quantity of data.

What is a Time Crystal?

Now that we have a general understanding of quantum computing, let’s get down to the nitty-gritty of time crystals. What does this strangely sci-fi-sounding term mean? A time crystal is a quantum arrangement of particles in condensed matter physics whose lowestenergy state is one where the elements or particles are in repeated motion.

Since the system is already in its quantum ground state, it cannot lose energy to the environment and come to a halt. As a result, the motion of the particles does not reflect kinetic energy in the same way that ordinary motion does. Instead, it possesses “motion without energy.”

The person who first suggested the concept of time crystals is Frank Wilczek in 2012. He proposed that time crystals are a time-based counterpart to ordinary crystals, whose atoms are organized regularly in space.

Several groups of scientists have proven the existence of matter with a stable periodic

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development in systems that are pushed on a regular basis.

In time, however, it was proved that this theory proposed by Wilczek does not hold true in a practical environment. Wilczek imagined a diamond-like multi-part entity in equilibrium. This item, however, contradicts time-translation symmetry: It moves in a regular pattern, returning to its original state at regular intervals. Because the system is in its ultra-stable equilibrium condition, a Wilczekian time crystal needed no input and can run endlessly. In 2014, this theory was proved to be a failure.

Google’s Time Crystal Venture Using Quantum Computing Time crystals, as one might expect, are quite rare in nature. But according to ZDNet.com, Google’s experts now claim that their findings provide a “scalable strategy” to studying time crystals on existing quantum computers.

Time crystals are a new “phase of matter,” as experts describe it. The concept of time crystals has been hypothesized for years as a new form that may possibly join the list of solids, liquids, gases, crystals, and other states of matter.

Time crystals are quite fascinating when you have a basic knowledge of physics. This is the second law of thermodynamics, which explains that systems naturally seek to remain in a condition known as “maximum entropy.”

Time crystals are also the first items to defy the concept of “timetranslation symmetry,” which states that a steady object should remain the same throughout eternity.

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What Do Scientists Have to Say About Google’s Time Crystal Discovery?

Roderich Moessner, the director of the Max Planck Institute for the Physics of Complex Systems in Dresden, Germany, stated, “The result is amazing: You completely evade the second rule of thermodynamics.” Moessner is also a co-author of the Google article. The second law of thermodynamics elucidates the law of chaos, which states that disorder will constantly increase.

those earlier experiments,” said John Chalker.

John is also a condensed matter physicist at the University of Oxford. However, he wasn’t involved in the new research. “The focus shifted from examining what nature provides us to imagining novel kinds of stuff that quantum mechanics allows,” Chalker added.

Time crystals are also the first items to defy the concept of “time-translation symmetry,” which states that a steady object should remain the same throughout eternity. A time crystal is both steady and dynamic, with exceptional moments occurring at regular intervals.

“This is simply this entirely new and fascinating region that we’re working in right now,” said Vedika Khemani. Vedika is a Stanford-based condensed matter physicist.

She founded the unique phase as a graduate student and co-authored the new study with the team of Google scientists.

“There are good reasons to believe that none of those experimental studies succeeded completely, and a quantum computer like [Google’s] would be particularly wellpositioned to perform much better than

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How Will Time Crystals Possibly Benefit Google’s Quantum Computing Field?

According to experts, time crystals do not reach thermal equilibrium at any point in time. Rather than progressively devolving into chaos, they become trapped in two high-energy configurations that they alternate between - and this back-and-forth process can carry on indefinitely. As the system is disturbed, it forgets what its initial configuration was and becomes increasingly random and chaotic.

According to ZDNet.com,

Google’s quantum processor, Sycamore, is well-known for its accomplishments and is now seeking a practical use for quantum computing.

In the opinion of Von Keyserlingk, a quantum processor is a great instrument for replicating a quantum mechanical system by definition.

There are, of course, certain limitations to time crystals. Google’s processor, like other quantum computers, suffers from decoherence. This may end up causing the quantum states of the qubits to deteriorate.

There’s also the fact that time crystals are exceedingly uncommon in nature and don’t appear out of anywhere.

Final Thoughts The revelation that time crystals can only break discrete time-translation symmetry in the case of time sheds fresh light on the difference between time and space.

These discussions will continue, fueled by the prospect of quantum computer exploration. Condensed matter physicists used to be concerned with the natural world’s components. If Google’s quantum computer can be recreated, time crystals will not only be real, but they may also be put to practical use in the actual world.

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Does

Quantum Cryptography Ensure

Cyber Security?

by Simmy Mohanan

Have you ever wondered if the payments, contacts, and data transfers that take place over the internet are secure? Is it possible to hack them? How is all this data protected? Well, cryptography answers it all.

The system that has secured our web activity and interactions for years is on the verge of being wiped out.

Businesses and organizations should be aware of this today and prepare for cryptography in the quantum era.

Before we go further, let us understand Quantum Cryptography.

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What is Quantum Cryptography?

Cryptography is the technique of encrypting data or altering plain text so that only those with the correct “key” can access it. By application, quantum cryptography encrypts data and sends it in an extremely secure manner using quantum mechanics techniques. The basic principles of quantum mechanics behind quantum cryptography are: Cryptographic techniques that are expected to be safe against a quantum computer hack are known as post-quantum cryptography. It is based on difficult mathematical equations.

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2 Photons

are generated in one of the two quantum states at random.

1 The particles that form the universe are unpredictable, and they can exist in multiple states simultaneously.

It is impossible to measure a quantum feature without allowing it to change.

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It is possible to clone some properties of the quantum particle but not the entire particle.

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Traditional computer systems take months, if not years, to solve these complicated mathematical calculations. Quantum computers executing Shor’s algorithm, on the other hand, will be able to crack logic systems in a matter of seconds. Quantum cryptography, on the other hand, employs quantum mechanics to convey private messages and is fully secure, unlike mathematical encrypt. Quantum key distribution makes use of these quantum mechanical features to generate and distribute a shared key while ensuring that no third parties have intruded.

Quantum computers executing Shor’s algorithm and will be able to crack logic systems in a matter of seconds.

How Does Quantum Encryption Work?

Quantum cryptography or quantum key distribution (QKD) uses a series of photon or light particles to transmit data over a fibre optic from one location to another. It’s a method of spreading and distributing the secret keys required by data encryption. In addition, the method must ensure that they remain secret between the sender and receiver. Information is often stored on single photons, and after both sides’ keys have been safely generated, their interactions are secure. Quantum communication systems are expected to offer virtually unbreakable encryption.

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Let’s understand the process of this encryption model:

STEP 1:

The sender transmits photons through a polarizer or filter, which randomly allots them bit designations and polarization. The four possible polarizations and bit designations are Horizontal (Zero bit), Vertical (One bit), 45 degrees left (Zero bit), or 45 degrees right (One bit).

STEP 2:

The receiver needs to use two beam splitters (horizontal/vertical and diagonal) to “read” the polarization of each photon.

STEP 3:

After sending the photons, the receiver must inform the sender of the beam splitter used for each photon of the stream. The sender compares the sequence before sending the key. If the photons are read with the wrong beam splitter, they are discarded, and the resulting sequence of bits becomes the key. If the photon is read or copied in by any eavesdropper, the photon’s state will change, which will be detected by the endpoints.

Example of how quantum encryption works: Mark (the sender) Plaintext

ENCRYPTION ALGORITHM

Eve (the eavesdropper)

PUBLIC CHANNEL (i.e. Telephone or Internet)

Key Quantum state generator

Jacob (the receiver) Plaintext

DECRYPTION ALGORITHM Key

QUANTUM CHANNEL (i.e. optical fiber or free space)

Quantum state detector

Say you have two individuals, Mark and Jacob, who want to send each other a hidden message that no one else can read. Over a fibre optic line, Mark sends Jacob a sequence of polarised photons. Because photons have a unique quantum state, this optic cable does not need to be secured.If any unauthorized person, Eve, tries to listen in on the discussion, she will have to read each photon to figure out what is being said. She must then send that photon to Bob. Eve 91

changes the quantum state of the photon by viewing it, creating faults into the quantum key. This informs Mark and Jacob that somebody is monitoring them and the key has been leaked. Mark can then send a new key to Jacob so he can read the secret message.

The Era of Quantum Cryptographic Cyber Security To enable safe data transmissions, encryption technologies use mathematical equations that are nearly impossible to calculate. They secure the data using various algorithms.

The standard techniques for encryptions are:

1 Symmetric Encryption In this type of encryption, only one key is used to both encrypt and decrypt the data. Using symmetric encryption algorithms, data is converted to a form that can be understood only by someone who possess the secret key to decrypt it. The algorithm reverses its action, and the message is returned to its original and understandable form once it reaches the intended recipient who possesses the key.

The secret key that the sender and recipient both use could be a specific password/code or a random string of letters or numbers generated by a secure random number generator (RNG).

2 Asymmetric Encryption This encryption technique encrypts and decrypts the data using two separate cryptographic keys: a ‘Public Key’ and a ‘Private Key.’ The most exciting feature of this new strategy is that while a public key can be used to encrypt text, it cannot be used to decrypt it. The text will not be decrypted by any other user’s private or public keys. The data flow is extremely safe using this technology.

3 Hashing It is the process of using a mathematical function to turn input of any length into a fixed-size text string. The method of storing and processing data using hash tables is known as hashing. Hashing is also used in data encryption. Passwords can be stored in the form of their hashes. In case there is a breach in database, plaintext passwords will not be accessible.

Shor’s Algorithm in Quantum Computing Peter Shor, in 1994, created Shor’s algorithm for integer factorization on quantum computers. The procedure identifies the prime factors of a positive integer P. Shor’s algorithm runs in polynomial time, which is polynomial in log N order.

The algorithm is important because it means that, with a sufficiently big quantum computer, public-key cryptography may be easily destroyed. The public key N in RSA, for example, is the product of two large prime numbers. Factoring N is one approach to defeat RSA encryption, however, factoring gets increasingly time-consuming as N goes larger; more particular, no classical algorithm exists that can factor in time O((log N)k) for any k.

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Shor’s algorithm, on the other hand, can break RSA in polynomial time. It also gets into a variety of different public-key cryptosystems.

Shor’s technique is predictable like all quantum algorithms; it provides the correct answer with a high probability. But, finding a practical quantum crypto algorithms security solution may take some time. There are already two decent options, and studies have been continuing for quite some time. The first method is known as post-quantum cryptography, and it is based on different mathematical equations than those presently in use. The second method makes use of quantum physics to find new cryptographic answers.

Why Don’t We Utilise Quantum Cryptography?

If quantum cryptography is so safe, why don’t we just use it?

Quantum cryptography involves the use of specialised hardware. To make it work, you’ll need photon detectors, beam splitters, and other components. As a result, we won’t be able to fit it into a small device like your phone.

Even though quantum encryption is secure, it doesn’t mean it is shielded from all threats.

Side-channel cyberattacks are a possibility.

These occur as a result of a flaw in the cryptosystem’s design rather than a flaw in the algorithm itself. Although no one has effectively received photons during the creation of the key in quantum key distribution protocols; side-channel threats do occur in quantum cryptography.

Will Cyber Security be Ensured?

Even though data transfer over the internet is now assumed to be secure, it is still prone to hacking through which malicious people steal and copy encrypted messages to decipher them. For data with a long-term risk, companies may wish to add an extra level of security.

Quantum cryptography, however, not only generates the threat but also offers a remedy.

When sharing the encryption key through a method known as quantum key distribution (QKD), quantum-based technologies can be used to identify the presence of hackers on a link. When combined with the one-time-pad cypher, the protocol provides unbeatable encryption security.

It is mainly aimed at those who want to protect their secret links for extended periods and with the highest amount of safety, such as public organizations and military people.

Conclusion The necessity for quantum cryptography is right in front of our eyes. The safety of encrypted data is now in danger, with the advancement of quantum computers.

Thankfully, Quantum Cryptography provides the solution we need to protect our data for the near future - all based on the rules of quantum physics.

Quantum Cryptography is the answer that will protect confidential matters as the need for encryption technology grows in networks that are connected.

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Quantum Computing:

Challenges & Opportunities Ahead by Ragini Agarwal

W

hen scientist Richard Feynman predicted 40 years ago that quantum computers would be a game-changer in the near future, no one could have foreseen that these computers would come this far. Complex jobs are becoming considerably easier because

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of these quantum computers. Even the most powerful conventional computers have been outperformed by them.

While fully functional quantum computers look to be on the horizon and will be simple to use for businesses, there are still a number of quantum computing problems to solve, such as accuracy and fault tolerance, which may take at least four to five years to assure its credibility.

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Influence of Quantum Technology

on Security Quantum computing is having a significant impact on the workplace, and IT industry leads must be up to date to keep pace with the fastchanging technology.

Let’s examine the problems and opportunities that Quantum Computing will face in the years to come.

Quantum computers are devices that are used for data storage and processing purposes and work on the principle of quantum physics. This might be incredibly beneficial in some cases as they can significantly surpass even the most powerful supercomputers.

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Quantum computing puts traditional encryption methods to the test, as they are incapable of coping with quantum capabilities.

As a result, quantum-safe algorithms must be put in place right away.

Quantum will fundamentally change the architecture of computer security, rendering much present encryption and digital signature approaches essentially useless,” says Chris Hickman, chief security manager of digital identity security firm Key Factor. “IT leaders must develop a strategy to protect their businesses as well as a realistic plan to deal with quantum computing’s impending arrival.”

Business Value Quantum computing is still in its early stages, with many unresolved issues, but it is an area that will have a significant impact on sectors such as banking, health, automobiles, and artificial intelligence in the next years.

Businesses must stay updated in order to maintain a competitive advantage.

“For the time being, IT executives should concentrate on quantum computing,” said Nir Minerbi, the CEO of Classiq, the first Israeli quantum computing software business.

“Rivals have already arrived, amassing quantum algorithms and private data that will give them a significant competitive edge in the years ahead.”

According to Christopher Savoie, president, and chairman of Zapata Computing, which provides quantum computing software,

Current encrypted assets, according to Hickman, need to be re-evaluated and secured in a quantum-resistant manner.

Many opportunities will be lost if it is not done now, and it will be too late or too expensive to preserve them later.

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organizations that are not quantum-ready will struggle to stay afloat.

Quantum computing advances, he believes, will have a disruptive effect on all major industries.Quantum computing’s capacity to do computations in ways that go beyond existing capabilities, for example, would assist financial services firms and other industries that rely significantly on statistical forecasting of future events.

Pharmacological and information science companies will be able to simulate quantum encounters that are difficult to simulate precisely on traditional computers or use quantum-enhanced artificial intelligence to extract correlations in data to increase the

rate at which new organic compounds and molecules are discovered.

The rate of acceleration implies that IT leaders should start thinking about quantum expenditures now if quantum computing is likely to have an impact on your industry,” Savoie added.

Apart from the rate of acceleration, quantum algorithms are advantageous for another reason, according to Minerbi: “Fault-tolerant quantum computers are undoubtedly 10 years

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away, however, good quantum algorithms that can be run on noisy quantum computers exist, and now is an excellent moment to develop them.”

Quantum Computing Current Scenario Quantum technology is now being employed in a variety of initiatives. The dipole moment of three lithium-containing molecules was modeled using a quantum computer by IBM and Daimler in 2020, putting us one step ahead of next-generation lithium-sulfur batteries, which will be more powerful, last longer, and be less expensive than current lithium batteries. IBM and JPMorgan have worked on quantum computing in finance, including research on the use of quantum computing in valuation models. Quantum technology, on the other hand, isn’t simply for computers.

Many technologies on the market today, including mobile phones, incorporate quantum phenomena, according to Deborah Golden, Deloitte’s U.S. cyber and strategic risk director. “While quantum use cases are now limited,” she continued, “they are growing.”

Quantum communications, for example, offer a high level of surveillance protection.

Importance of Quantum Computing While quantum computing has the potential to transform how real-world problems are addressed, it must first overcome a number of severe engineering obstacles, leaving businesses without a timeline for when it will be helpful in the workplace.

While quantum use cases are now limited, they are growing.

- Deborah Golden

Getting Ready for Quantum Future Comprehending the quantum computing problems is just half the battle; quantum is a world apart from what most organizations are used to.

“Unlike regular computers, quantum computers only offer a likely response,” Vaclav Vincalek, a business consultant who assists firms in integrating cutting-edge technology, said.

They aren’t meant to provide definitive answers; instead, they give the most likely solution, which may need to be verified by a regular computer. A quantum computer, for example, may calculate the most likely method for cracking an encryption system, but a classical computer will need to test the answer to determine whether it begins to break.

As a result, quantum coding is an entirely new challenge. Before there was a genuine quantum operating system, there was no easy way to migrate or reuse code between platforms.

Conclusion Quantum computing has the ability to transform how real-world problems are solved, there are still a number of challenging engineering obstacles to overcome first, leaving businesses without a timeline for when they will be employed in the workplace. Because of its potential to tackle incomprehensibly complex issues, the quantum computing industry is expected to reach $65 billion by 2030, making it a popular topic for investors and academics alike.

Between 2021 and 2030, the global quantum computing market is expected to expand at a CAGR of 25.40 percent, from USD 487.4 million in 2021 to USD 3728.4 million in 2030.

Quantum computing will not be widely used for decades, but research teams in universities and private businesses throughout the world are working on various aspects of the technology.

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