Understanding cloud computing
Cloud computing is named as such because the information being accessed is found remotely in the cloud or another virtual environment. Users can store files and apps on faraway servers and then can access the data via the Internet thanks to companies that offer cloud services. This enables the user to access it remotely since they are not obliged to be in a specific location to do so. With the help of cloud computing, users may process data without using computers or carrying around heavy equipment. All of the work can also be transferred to enormous computer clusters located far away in cyberspace. Users’ data, work, and applications are accessible from any device, and users can connect to the Internet from anywhere in the world.

Cloud computing can be both public and private. Public cloud providers offer their services over the Internet for a price. On the other hand, limited numbers of users can access private cloud services. These services consist of a networked infrastructure that offers hosted services. A hybrid option is also available, which incorporates aspects of both public and private services.

Types of cloud services
Regardless of the kind of service, cloud computing services provide users with a series of functions including email, storage, backup, and data retrieval, creating and testing apps, analyzing data, audio and video streaming, and delivering software on demand. Although it is still a relatively new technology, cloud computing is being utilised by a wide range of industries, including large corporations, small businesses, nonprofit organisations, governmental agencies, and even individual consumers.

Deployment models
There are many different kinds of clouds, and each one is unique. Public clouds offer their services on internet-connected servers and storage. These are run by independent firms that manage and take care of all the infrastructure, software, and hardware. Customers use accounts that virtually anybody may use to obtain services. Private clouds are only accessible to a small number of clients, typically just one company or organisation. The cloud computing service could be hosted by the company’s data centre. On a private network, many private cloud computing services are offered. As the name suggests, hybrid clouds combine both public and private services. This kind of architecture gives the user more options and improves the infrastructure and security for the user.

Types of cloud computing
Like a chip or a phone, cloud computing is not a standalone piece of technology. Software-as-a-service (SaaS), infrastructure-as-a-service (IaaS), and platform-as-a-service (PaaS) make up the majority of the system instead.

A software programme is licenced to clients as part of the software-as-a-service (SaaS) model. Usually, licences are made available on-demand or on a pay-as-you-go arrangement. Microsoft Office 365 contains this kind of mechanism.

Infrastructure-as-a-service (IaaS) is a technique for supplying anything through IP-based connectivity as part of an on-demand service, including operating systems, servers, and storage. Clients can obtain software and servers through an on-demand, outsourced service rather than having to buy them outright. Popular examples of the IaaS system include IBM Cloud and Microsoft Azure.

The most complicated of the three cloud computing levels is platform-as-a-service (PaaS). PaaS and SaaS are quite similar, with the main distinction being that PaaS is a platform for developing software that is supplied over the Internet rather than offering software as a service. Platforms like Salesforce.com and Heroku are part of this strategy.

Advantages of cloud computing
Companies from all industries can profit from using cloud-based software, which can be accessed by browsers or native apps on any device. As a result, users can carry their files and settings over to other devices in a completely seamless manner. Using cloud computing for file access is simply the tip of the iceberg. Users may check their email on any computer and store files using services like Dropbox and Google Drive thanks to cloud computing. Users can back up their music, files, and images using cloud computing services, ensuring those files are immediately available in the event of a hard drive crash.

It also offers big companies huge cost-saving potential. Companies had to invest in pricey information management infrastructure and technology purchases, construction, and maintenance before the cloud became a practical substitute. Fast Internet connections can replace expensive server centres and IT staff in businesses, allowing workers to do jobs online by interacting with the cloud. People can conserve storage space on their computers or laptops by using the cloud infrastructure. Software businesses can now sell their wares online rather than through more conventional, tangible ways like discs or flash drives, which allows customers to upgrade software more quickly. Customers of Adobe, for instance, can use an online subscription to access the applications included in its Creative Cloud.

Disadvantages of the cloud
There are risks, of course, with all the speed, efficiencies, and innovations that come with cloud computing. Security has always been a major concern with the cloud, particularly when it comes to private financial and medical documents. Although regulations require cloud computing firms to strengthen their compliance and security measures, it is still a problem today. Important data is encrypted for protection, but if the encryption key is lost, the data is gone as well. Cloud computing firms’ servers are susceptible to internal errors, power outages, and natural calamities. The geographical reach of cloud computing cuts both ways: A blackout in California could paralyze users in New York, and a firm in Texas could lose its data if something causes its Maine-based provider to crash. As with any technology, there is a learning curve for both employees and managers. But with many individuals accessing and manipulating information through single portal, inadvertent mistakes can transfer across an entire system.

Market value of cloud computing
The market for cloud computing is currently at an all-time high, valued at $371.4 billion, and is projected to reach $832.1 billion by 2025. It is swiftly developing, progressively recognising its commercial significance, and drawing an increasing number of academics, practitioners, researchers, and computer scientists. Cloud computing is not a single subject but rather a collection of many technologies that make up the cloud. The top 10 research areas in the realm of cloud computing are listed below:

Big Data
Big Data is the term used to describe the enormous volumes of data that different programmes produce in a relatively short period of time. In business-run data centres, it is rather laborious to store such massive and copious volumes of data. The cloud is the best option since collecting insights from Big Data also becomes a laborious operation that takes a long time to run and produce results. All the data can be pushed onto the cloud without the need for physical storage devices that are to be managed and secured. Also, some popular public clouds provide comprehensive Big Data platforms to turn data into actionable insights.

DevOps
DevOps is an amalgamation of two terms, Development and Operations. There are now fewer barriers between the development team and the operations team as a result of continuous delivery, integration, and deployment. Heavy applications and software need elaborate and complex tech stacks that demand extensive labor to develop and configure which can easily be eliminated by cloud computing. It offers a wide range of tools and technologies to build, test, and deploy applications within a few minutes and a single click. It provides a variety of tools and technologies that may be used to quickly build, test, and distribute applications. The method is easy and cost-effective for development teams because it may be tailored to the needs of the client and eliminated when not in use.

Cloud Cryptography
It is important to safeguard and secure cloud data against outside intrusions and breaches. To do this, Cloud Cryptography is a frequently used method to secure data that is present in the cloud. Since all data is secured using either encryption methods or the idea of a private key, it enables users and customers to access shared cloud services quickly and reliably. It can limit the view of the data being conveyed and render plain text unintelligible. The best Cloud Cryptography security methods avoid slowing down data transit and offer protection without preventing the sharing of important information.

Cloud Load Balancing
Cloud Load Balancing refers to dividing and dispersing the incoming load from numerous sources to the server. Cloud Load Balancing encompasses holding the circulation of traffic and demands that exist over the Internet. This lessens the issue of unexpected outages, improves overall performance, minimises the likelihood of server failures, and also offers a high level of security. Server load balancing allows cloud-based server farms to achieve more precise scaling and accessibility. As a result, it is simple to allocate and manage workload demands.

Mobile Cloud Computing
In order to offer services like seamless and plentiful computational resources to mobile users, network operators, and cloud computing specialists, Mobile Cloud Computing combines cloud computing, mobile computing, and wireless networks. All processing and data storage happens outside of the actual mobile device, which serves as the console. The lack of expensive hardware, longer battery life, increased data storage and processing power, improved data synchronisation, and high availability owing to “store in one place, accessible from anywhere” are some benefits of using Mobile Cloud Computing. The backend, which offers support for a variety of access ways, handles the integration and security aspects.

Green Cloud Computing
The major challenge in the cloud is the utilization of energy-efficient and hence developing economically friendly cloud computing solutions. Large data centres with numerous computers, cables, air conditioners, networks, etc. use a lot of energy and emit a lot of carbon dioxide into the atmosphere. The goal of Green Cloud Computing is to make virtual servers and data centres more energy- and environmentally friendly. The amount of power and energy that cloud resources frequently use results in a lack of energy and has an impact on the climate worldwide. Green Cloud Computing offers ways to lower operating costs and improve the energy efficiency of such systems. Power management, virtualization of servers and data centres, extensive e-waste recycling, and environmental sustainability are the key axes on which this is based.

Edge Computing
With the premise that the data is processed closer to the source, Edge Computing is an improvement and a far more effective kind of cloud computing. According to edge computing, all processing will take place at the network’s edge rather than on a platform that is centrally controlled or in data warehouses. Edge computing disperses numerous procedures and data processing approaches among several locations. As a result, the data can be sent to the closest node and processed at the edge. Since the data is closer to the source and there is no longer any latency or delayed response, the security of the data is also increased without reducing productivity.

Containerization
Containerization in cloud computing is a procedure to obtain operating system virtualization. Through the use of remote resource procedures, the user can interact with a programme and its dependencies. Blocks that help produce operational effectiveness, version control, developer productivity, and environmental stability are built using the cloud computing container. The infrastructure has been improved since it offers more control over the specific operations involving the resources. The usage of containers in online services assists storage with cloud computing data security, elasticity, and availability. Containers provide some benefits over virtual machines, including a consistent runtime environment, the flexibility to operate almost anywhere, and lower overhead.

Cloud Deployment Model
There are four main cloud deployment models namely public cloud, private cloud, hybrid cloud, and community cloud. Each deployment type is specified based on where the infrastructure is located. The general public can easily access systems and services thanks to the public cloud. Since it is accessible to all users, like email, public cloud services could also be less dependable. Systems and services can be accessed inside a company using a private cloud without external access. Because of its access limitations, it provides superior security. A hybrid cloud is a combination of private and public clouds, with the private cloud being used for vital tasks and the public cloud for non-critical tasks.

Cloud Security
The security of the cloud is a key concern as the number of businesses and organisations employing cloud computing is growing rapidly. Every physical and logical security issue that arises across all the many service models of code, platform, and infrastructure is detected and addressed by cloud computing security. Although it discusses these services as a whole, the public, private, or hybrid delivery models are how these services are actually provided. The data is safeguarded on the cloud against loss, theft, calamity, and removal. Data can be safeguarded with the aid of firewalls, virtual private networks, and tokenization.

Cloud computing research challenges
There are two major cloud computing research challenges, i.e. Portability and Development of a new architecture. The ability to move an application and its data from one location to another is known as portability. Limiting reliance on the underlying atmosphere could help achieve it. No matter the provider, platform, operating system, location, storage, etc., a portable component (application, data) could be transported and reprocessed. For instance, if the new cloud environment is Linux and the previous cloud environment is Windows, portability would allow an application operating on the old cloud to run on the new cloud without needing to be modified.

On the other hand, nearly all cloud computing services are currently used in sizable commercial data centres and operated in an antiquated centralised manner. This kind of design has some drawbacks, such as low manageability and low economies of scale. The majority of researchers lean towards hosting cloud apps on planned resources. This cloud computing paradigm is highly rational and well-suited for applications like scientific computing since it uses volunteer resources or a combination of volunteer and dedicated resources. However, regardless of its advantages, this architecture has open research challenges as well, which are heterogeneous resources management, and incentive schemes for such architecture.

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New uses for EHRs 

The underlying aspect is that technological revolutions in healthcare have been constrained until more recently. For example, it wasn’t until 2009 when the Health Information Technology for Economic and Clinical Health Act was enacted for the adoption of EHRs in the US—which then led to significant progression from 13.4 percent in 2008 to more than 90 percent of non-federal acute care hospitals by 2017. Despite the dramatic increase, the timeframe has lagged behind in other countries like the UK where EHRs were established in nearly 100 percent of primary care settings by the mid-2000s. This trend is quite similar to Japan and far more advanced than African countries where considerable barriers remain. 

On the global front, uneven distribution of EHR adoption has worsened the disparities between low-income and high-income countries in regard to rapid technological investments. As intimidating as this observation is, today’s EHRs are used for tasks beyond billing and documentation of patients’ diagnosis. By definition, EHRs can be regarded as one of the key factors to improve individual patient outcomes and supply longitudinal data for public health initiatives. Clinical decision support systems can assist in the fundamentals of patient care such as reminders for vaccinations, identifying patients with communicable diseases and alert physicians on potentially hazardous drug interactions when prescribing. Combined with effective modules that integrate evidence-based clinical guidelines to help direct patient care, EHRs can offer one of the biggest returns on investment for a health system. 

But a more relevant question is: What makes EHRs part of the new data frontier in healthcare? Health systems are starting to monetise the vast amount of patient data in their EHRs for further drug discovery or repurposing and clinical research. This can amount to millions of dollars to hospitals and healthcare organisations from pharmaceuticals to technology companies. In fact, the more robust a hospital or health system’s EHR is, the move valuable it can be—both financially and clinically. 

Connected devices for clinical trials 

The global connected health and wellness devices market is poised to grow exponentially. For example, smartphone adoption has become virtually ubiquitous over the past two decades despite its global location—be it Kentucky, Kenya or South Korea. Data from these devices could be fed into EHRs with the decision to support algorithms to help physicians identify patients who are at risk of complications from procedures or with poor control of their health conditions before the symptoms are clear. The value from EHRs and connected devices takes on significant importance when they are combined. 

More importantly, new applications of connected devices can be found with clinical trials. A significant challenge is that patient enrollment in some trails can falter causing them to stop prematurely and limiting the data from the study. “Digital” clinical trials utilising wearable devices such as smart watches or fitness trackers are offering pharmaceuticals and device companies a way to increase enrollment and run their trials more efficiently—as they can yield essential post-market evidence in realistic patient populations.  

Optimisation: The creation of  SuperDoctor

Radiologists are able to diagnose breast cancer before it becomes obvious on a mammogram or a simple eye scan can identify diabetic retinopathy which can be performed at home using a smartphone determining which family members will suffer from a hereditary disease while their relatives are unscathed.  This is not a futuristic fantasy of the medical world but an emerging reality using data analytics and machine learning to optimise patient care and research. Such examples are the reason behind big data becoming the next frontier in patient care. The more data is available to clinicians and researchers, better AI algorithms can be developed for long-term predictions. 

Data analytics like this are currently expensive, but what we have seen with most technologies is that the cost decreases and the value for money increases over time. To further explain this progression, it is weighed against the benefits of previous disease detection with improved prognosis, lower treatment costs, elimination of low-value care, increased efficiency in drug development and declining costs of technical investments in comprehensive EHRs. In fact, the incredible progress made in genomics should drive this point home. 

Interestingly, for each advancement affecting patient care, new companies are emerging with an intent to invest in advanced technologies and national healthcare policies are favourably changing. It is important to continue the current momentum of scientific and healthcare collaboration across borders to build a truly global healthcare industry where all stakeholders can make smart decisions based on evidence rather than status quo.

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“The positions are available in Japan and Korea. However, as we already have engineers from 28 countries working at LINE, we look forward to accepting applicants from a diversity of backgrounds,” LINE’s spokesperson told International Finance. 

LINE is expected to hire machine learning engineers, data scientists, researchers, data platform engineers and other AI experts to build a sustainable foundation that will support its services in the long run. It also improves service value using big data. 

In fact, AI being one of the company’s strategic pillars is indispensable to LINE’s long-term business plan. “We believe that AI technology has the potential to update all of society and industry,” according to the spokesperson. 

LINE’s teams in charge of data platform development, data analysis, machine learning, AI technology development, and fundamental research will be consolidated into a single organisation. 

Last June, LINE’s proprietary AI technology was offered to external partners through a new business called LINE BRAIN to streamline work and improve user convenience. It is currently under proof of concept with select partners. LINE BRAIN is also set to launch in Taiwan in the second half of 2020. 

LINE BRAIN is a B2B AI-driven business offering corporate clients AI technologies developed by the company, such as chatbot, optical character recognition, voice recognition, voice synthesis and image recognition. “It aims to not just help other companies improve the productivity and convenience of their services, but also to make everyday life more convenient for the users of these services,” the spokesperson said. 

LINE’s internal restructuring will shorten the time from research and development to production, enabling the company to hasten commercialisation of its AI-based services through LINE BRAIN. In addition, the restructuring will help the company to promote data use across businesses and departments. It can utilise its massive database to its full potential and further improve its existing services.

In 2016, LINE established LINE Data Labs — a dedicated development department that analyzes and researches data for the company and its related services. The LINE Data Labs’ work supports a wide range of products and services including content displayed in Smart Channel.

In the following year, the company launched the Clova AI assistant powering  LINE’s AI speakers such as Clova Friends and Clova Desk. The company is working on LINE AiCall, an AI phone call service to be launched this year. 

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The challenge of efficiently making the best use of unstructured data coming from a variety of channels remain a key one in the years ahead. Data can turn into competitive advantage for businesses and the ability to make the best use of them result in big digital payoffs for organisations, enhancing decision-making and reinventing fully or partly business models. However, the risks for companies is to amass an enormous set of data that are not clean, which makes them worthless when it comes to making good and solid business decisions. Therefore, companies can either decide to streamline data internally or they can rely on the external support of startups which focus on acquiring, and building innovative products around big data. In most cases, the second option is the most effective.

The trend of companies buying startups with the specific objective of coping with ‘the big data revolution’ doesn’t seem to be fading anytime soon. When a new startup comes up with technological advancement in big data and machine learning, usual catches the eye of bigger companies, and this has also been the case for Southeast Asia startups.

Here are three Thai big data startups collaborating with multinational companies in various sectors either through direct partnerships or separate deals.

1. TranspoTech – DRVR, making Asia’s vehicle fleets smarter

DRVR, a Bangkok-based startup and fleet management application provider, works with a number of major corporations, including Tata Communications, was selected as its global internet of Things (IoT) connectivity partner to achieve its goal of making Asia’s vehicle fleets the smartest and most cost efficient in the world.

Failing to keep up pace with the proliferation of Big Data and the increased power of machine learning could prevent companies from achieving a substantial shift from stand-alone things to more intelligent collaborative environments, through greater connectivity delivered by Internet of Things (IoT). As sensors spread across almost every industry, IoT is going to trigger a massive influx of big data also in the transportation sector, which has been considered for quite some time one of the next industries in line to get disrupted by the use of new technologies such as Big Data, IoT and, Artificial Intelligence (AI).

Most transpo-tech companies promise to automate process, providing real-time solutions for customers, through much faster search options and the digitalisation of the whole application process. Mr Henderson, Co-Founder & CEO of DRVR, says: “much of the problems are with manual processes and opaque paper trails. Through the automation of processes and by giving visibility through IoT Sensors and using technology such as Distributed Ledgers, DRVR promises to solve them”.

DRVR can deploy its own sensors and devices and in more advanced markets can use the existing infrastructure to help customers improve their supply chain. GPS tracking and Fleet Management has been around for decades, but many companies offer simple solutions with no understanding of the environment and customers’ business needs. Mr Henderson notes ‘we understand the culture of ASEAN, so we have developed unique solutions which address some of this region’s most pressing problems’.

Thailand lies at the centre of Southeast Asia; it is the East-West and North-South crossroad of the region, and there is an increase in integration across the region. “Just few months ago no trucks could legally crossed the Thai-Myanmar border, while now hundreds do each day and we expect this volume to grow significantly once regulations get up to speed with reality’, Mr Henderson adds.

2. TalentTech – Get Links, using AI and Big Data to disrupt the recruitment industry

As aforementioned with the ramping growth of data and channels or touch points, multiple data streams make it difficult for organisations to gain a single view of the ecosystem and their customers.

Breaking down data streams and utilising analytics enables service providers to better understand their customer behaviours, while also improving customer verification, accuracy, and speed. This also applies to the recruitment sector, where the streamlining of the process through algorithms helps to match candidates with companies in a quicker and more refined way.

Pichaya Srifar, Co-founder & Chief Technology Officer at GetLinks, a Bangkok-based startup focused on helping tech companies find and hire top talent, says: “the recruitment industry operates on a long tail effect. The demand may not be met immediately even on a streamlined platform like ours”. However, through analytics, this startup can track the funnels in the process, and find solutions to individual problems. Having a self-service marketplace that places candidates in less than 48 hours, as opposed to the average three to six weeks, it is one of the ways GetLinks aims to disrupt the traditional recruitment model

GetLinks takes a different approach to building its users database. The startup relies on Big Data to create a scalable, self-service service, and with the data collected it is able to gain invaluable insights into how to create a platform unlike any other. Through its A/B testing and machine learning, it continuously build a more personalised experience. The more data is collected, processed, and fed into a machine-learning algorithm which learns how to process, the more likely is to reproduce the right match.

Traditional recruitment processes carries the problem of human bias and subjectivity that reduces diversity and leads to suboptimal selection decisions, However, collecting data is far faster than trying to understand and provide for every single eventuality. Despite systems and algorithms working 24/7 in real time, they are not yet sufficiently sophisticated to replicate human empathy and decision-making. Mr Srifar stresses: “That’s why, though the GetLinks marketplace is entirely automated, from screening to making of job offers, we still strongly believe in the power of human touch to build genuine human relationships”.

3. MarTech – Zanroo, fastest growing startup in Southeast Asia

Zanroo enables real-time big data analytics to help companies find actionable insights that enhance campaign activation and crisis management. It delivers social insights through listening, monitoring, and engagement because of its software and innovative tools, which empower companies by giving them a clear and consolidated view on their Return on Investment (ROI) .

Zanroo places great importance on the clients’ confidentiality: It does not work with companies’ internal data, but uses data from the company’s social media channels and other external data sources from blogs, forums, news sites to analyse the data and categorise it to provide companies with powerful insights.

In less than five years, Zanroo has been able to put together more than 300 leading brands among its clients, which span vertically from e-commerce to banking. Zanroo works with both large multinational companies and small-medium enterprises (SMEs). Chief Marketing Officer, Daud Charles, notes: “Both big companies and SMEs come with their respective challenges which is where positioning is critical. Larger companies are more mature in terms of social listening and digital marketing and they are more likely to be familiar with tools and deliverables, while SMEs are less savvy and resource constrained and require relatively more hand holding”.

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Designed for new and existing SAP customers, industry experts will weigh in on how to transform finance data and drive your business in an innovative direction.

The event will kick off with two simultaneous half-day, pre-conference workshops:

⦁ Faster Time to Value with SAP Central Finance
⦁ Central Finance Functional Deep Dive – A Stepping Stone to SAP S/4HANA

At these workshops, attendees will review product functionality, dive deeper into topics, get practical examples, take part in discussions, go through online demonstrations, and determine the business benefits of each solution. Each workshop allows attendees to address challenges, discuss them with your peers, and gain valuable guidance from some of the most knowledgeable experts on SAP applications.

At the conference itself, whether you are looking to simplify a complex financial landscape, lead with numbers, establish a single source of reporting truth or unite transactions and analysis, this event offers you the chance to achieve your goals. Attendees can tune in to customer reference stories from international organizations including Asahi Beverages, Enel, Generali Italia and more.

The event will largely cover:

⦁ Digital Transformation
⦁ Implementation Considerations
⦁ Central Account Payables and Account Receivables
⦁ SAP S/4HANA
⦁ Exploring the Advantages of the Universal Journal
⦁ The Cloud

Moreover, attendees can experience the SAP Partner exhibition, live demonstrations and interactive sessions and make valuable connections at the networking evening event.

This year’s event is also co-located with the International SAP Conference for Management Controlling. Register for one event and move freely across both agendas. Benefit from combined industry learning and multiple networking opportunities with the wider finance community.

Visit www.tacook.com/sapcentralfinance for more details, or contact the event team at info@tacook.com, +44 (0)121 200 3810.

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The initiative comes with an effort to facilitate better data analytics in the country and improve the aptitude. According to Jakarta Globe, students of the Faculty of Economics and Business can sign up for the course, which will take place for the next five years by IBM Indonesia.

The faculty’s Accounting Chairman Ancella A. Hermawan said, “We feel it is important to equip students with the knowledge of data analytics and big data, so we decided to work with IT industry leaders such as IBM.” As part of the course, guest lectures will be presented by the company’s technology and industry experts.

The company, said in a statement, “Cognitive computing is a new era of computing, and we have seen a rising demand for it across industries. Our partnership with University of Indonesia to run the first class in this subject is part of our commitment to prepare the younger generations for a new era of technology.”

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The Summit will be held in Atlantis, The Palm in Dubai. Dubai takes pride in being the world’s smartest city, and is now embracing data to establish itself as a data-driven economy.

The event offers great insights into the importance of data management solutions to improve business performance for private and public firms.

Some of the well-known establishments in the digital space such as Ekimetrics, Actifio, RBBI, Knowledge Lens and Knowledge Foundry are sponsors and partners at the event.

The key speakers include:

• Younus Al Nasser

Assistant Director General, Smart Dubai Office

• Alejandro Carbon

CEO, Beam

• Sebastian Samuel

Chief Information Officer, AW Rostamani Group

• Maha Muraish

Vice-President for Data Monetization, Etisalat

• Louise Blake

Head of Data, Tajawal

• Alessandro Casuccio

Head of Business Intelligence & Analytics, Careem

• Joel Farvault

Head of Data, AXA Insurance

• Mohamed Tahoon

BI Developer and Visualization Lead, Dubizzle

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Science and Technology Daily newspaper stated that with the aid of Skynet, the eyeglasses will capture, evaluate and compare suspected faces merely in two seconds. Skynet in China has a nationwide record of blacklisted individuals.

Apart from facial recognition, the country is trying to adopt latest and advanced technologies like artificial intelligence (AI) and big data technology to augment its national security measures.

LLVision manufactured the glasses that are powered by AI. The glasses will scan individuals, and upon finding a match, it will flag them with a red box and the wearer of the smartglasseswill be notified.

In response to growing concerns among the citizens, LLVision Chief Executive Wu Fei assured that nationals should not be anxious about their privacy being breached because the country is implementing the technology for ‘noble causes’, which is to identify and locate the law-breakers.

David Bandurski, co-director of the China Media Projectsaid: “(China’s) leadership once felt a degree of trepidation over the advancement of the internet and communication technologies.”

“It now sees them as absolutely indispensable tools of social and political control.”

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The conference calls for personnel dealing in retail banking, private investment management, credit cards, insurance and loans to  gain insights into how to improve competitiveness and drive business growth.

It will also cater to industry-leading outlook with proven case studies. The key speakers to address the conference are:

 Jonathan Mansley

Head of Data, Analytics and Insight at Aviva, Norwich, UK

•        Michael McMorrow

Principal at MMM Data Perspectives, Ireland

•        Mark Whitehorn

Professor at the University of Dundee, Dundee, UK

•        Jean Panagamuwa

Senior Manager at Capital One, Nottingham, UK

•        Philippe Tromp

Member of the Senior Advisory Board at Solum Financial Ltd., London, Canada

•        Gary Nuttall MBCS CITP

Head of Business Intelligence at Chaucer Syndicates Ltd

•        Vinita Ramtri

Head of Conduct Risk, Wealth at Barclays Wealth and Investment Management

•        Kristjan Novitski

CEO and Founder at Cash On Go Ltd, Manchester, UK

•        Neil Carden

Director of Insight and Planning at The Co-operative Group, Edinburgh, UK

•        Paul Nicholas

Programme Manager at Zurich Personal Lines & Endsleigh, Gloucester, UK

•        Rick Avis

Head of Information and Integration Architecture at UBS, London, Canada

•        Keith Holmes

Head of Digital Analytics and Data at RSA, Redhill, UK

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The World Economic Forum’s Global Future Council on Cities and Urbanization today publishes Data-Driven Cities: 20 Stories of Innovation, a collection of 20 of the most creative ways cities worldwide are drawing on big data to improve services and quality of life.

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