SigmaWay Blog

SigmaWay Blog tries to aggregate original and third party content for the site users. It caters to articles on Process Improvement, Lean Six Sigma, Analytics, Market Intelligence, Training ,IT Services and industries which SigmaWay caters to

Asia gears up to be the global AI hub

AI has made it completely impeccable, from archaic development to cutting-edge technologies, reaching out to every niche possible, bearing the embryo of a heated competition between China and the US to revolutionize; the two major hubs having AI development in boon. Among the others following in this race include Singapore, Vietnam, Indonesia and Thailand. Vietnam has successfully implemented a crop intelligence system named Sero, that enables farmers to identify sick crops. Once enhanced further, Sero would assist in diagnosis and possible future treatments. An Indonesian telecom operator, Telkomsel, employed only chatbots to deal with clients and answer most of their queries. Sooner or later AI is digging deep roots in the industry although it takes some time for AI developers to present the desired results to the companies.

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Benefits of Big Data in Fintech Services

The ways in which financial enterprises operate today have changed fundamentally due to technological evolutions. Titanic amount of data gathered from individuals’ electronic devices can be analyzed and used by the Fintech sector to deliver reliable services to its clients. Big data have been offering numerous benefits to this industry in areas of fraud detection, customer segmentation, risk management etc. Big data helps financial enterprises understand the transaction pattern of clients and can inform them about suspicious transactions. Big data also partially, if not fully, rules out the potential threats from bad investments and bad payers. Fintech companies aim at creating personalized financial services and big data assists in doing so by meeting the specific demands of the final customers. Big data also leads to better compliance capabilities ultimately translating into better services for both B2C and B2B consumers.

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Artificial Intelligence in Religion

With machine learning making a huge leap of progress, it is being debated whether Artificial Intelligence and religion are compatible or not. Humans have been worshipping non-human entities from time immemorial and man-made robots would be superior to their creators. Religious modules have been entwined with technology to bear daily prayer apps and robot priest as the fruits. For example, the human robot named Peppa, an invention of Japan, could perform funeral entailing a cheaper cost than a human priest. Research at Faraday Institute of Science and Technology reported a strong correlation to exist between technology and religion which basically involved three stages-rejection, adoption and adaption. Down the lane, technology would become a ubiquitous part of all religion.  With a more objective analysis, AI provides a consolidated nutshell of all religious dialects.

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Expanding the scope of data access across the organization

We are aware of stepping up standards of AI and its importance for data scientists. But, we cannot resist AI to limit its scope till technology only. With the advances, AI is setting its root in business organizations too. AI as a business tool comes up with many advantages to expand data access.

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How big data is capable of predicting future online threats?

With the rapid rise of cyber crimes and online scams, people are getting insecure to share their sensitive data online. To encounter this appalling rise big data comes up with certain plans. So, how big data is used as a shield against online threats:

Network vulnerabilities

Detect irregularities

Detect irregularities in online behavior

Detect irregularities in device use

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TOPAZ: A worth gem news for enterprise data

Fast and high-valued data has become an urgent concern for business enterprises. Topaz for Enterprise Data encourages these ignited minds to:

 Understand the data even when they get diverted from the specific application, it also ensures data integrity and the quality of resulting code.

 Fast production of data for testing, training or business analytics that is capable of representing the actual data.

 Ensures security of sensitive business and personal data for relationships and characteristics.

 Easy conversion into required file type.

Topaz users can easily access all these competences from within a familiar Eclipse development environment.

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Making use of Chatbots in healthcare sector

Ever heard of Molly, Eva, Ginger, Replika, Florence and Izzy? NO?

So, welcome to the world of algorithm powered, voice based interfaces that has come up fantastic advances in medical and healthcare field. The Chatbots are being used as assist physicians and nurses. Chatbots ensures perfect medication management and assistance in the case of emergency. 

Top health chatbots includes:

i. Safedrugbot

ii. Izzy

iii. Babylon health

iv. Florence

v. Your.MD

vi. Ada health

vii. Sensely

viii. Buoy health


x. infermedica

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Can AI and ML foresee the problem of Autism in children?

Autism spectrum disorder refers to a condition in which a child is not able to communicate and form relationship with other people. Earlier for the diagnosis of Autism and examiner inspects the child and video record the behavior for further analysis. Legally for diagnosing Autism, the child should be older than 2 years. But with the early diagnosis of autism in children can help them to get out of their shells and face the socio affairs with confidence. A wunderkind algorithm of machine learning is capable of predicting Autism in a 6 month infant. 

Want to know, how this genius study is able to get such results? Go to:


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Expectations with AI

The AI industry is blooming at a very rapid rate. AI has start to appear in almost every sector and industry. But the results of AI may vary depending upon the data fed to it,  the techniques used, the scope of its usage, the expertise level of its users and builders, and the expectations set with that AI. The quality of data fed to the system vastly affects the AI decision making. 

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ERP moving to cloud

The ERP giants like SAP and Oracle have their roots in the garden for a really long time that it will take at least two years for any new competitor to give them a dent. Also, let’s not forget that the technology is flying at a rapid rate, so two years is really long time for a technology to go outdated. Recently, it has been noticed that these giants are trying to move their on-premises systems to cloud based systems. This is not an easy task to move tons of data without much affecting the pricing and retaining the customers. 

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Chatbots in Beauty Industry

Advanced technology has certainly come a long way in managing our lives and guiding our buying processes. When it comes to beauty industry, applications of artificial intelligence are giving brands the power to create an intelligent, sophisticated and authentic ‘robot’ which would enable the customers to find a product that not only feels good on their skin but also doesn’t cost them much. These chatbots will improve a particular company’s customer service and overall customer experience. They can be trained to answer specific questions and give the customers a personalized experience according to their skin type, needs and price range, and certainly reduce all the hurdles that customers have to face when trying to buy products online. Innovative beauty brands, with the help of augmented reality have shown their customers how easy it can be by asking the right questions, showing them the results and even incorporating suggestions into their bots. With the advancements cropping in more, chatbots will no longer be required to be trained by the employees and would become more intelligent from the information they will learn gradually.

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Potentiality of Government-Tech Startups

In countries where legacy systems, paper-based processes and outdated transparency are disarming both governments and citizens alike, Government-Tech, a $400 billion market is a promising take which is slowly giving attention to new age startups and venture capitalist for bringing in efficiency and transparency into the age-old problems. It has the potentiality to disrupt the age old delivery system of the government and provide much better and faster services at reduced costs. Coming to the Indian context, Government-Tech is still at a nascent stage and involves lot of risks but it can provide solutions to the problems involving obsolete technology, lack of information of processes and slow delivery due to bureaucracy which mostly happen to curb the government and the public sectors. For example, a solar powered IoT Air-Quality monitor called, “Polludron” is a low cost, eco-friendly and compact Oizom Instruments Solution which solves the problem of increasing commercialization. Despite the bright potentiality of the Government-Tech Start-Ups in India, there are also many challenges and problems that are rooted in the procurement processes of the government and bureaucratic mind set. Although technology continues to evolve, the unskilled and untrained workforce in the government/public sector results in sub optimal solutions as consultants have no practical exposure to the actual problems thus compromising the expected overall efficiency.

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Radioactive Traces in California Wine

Traces of radioactive waste from 2011 Fukushima nuclear power plant accident has been recently spotted in a California wine by a group of French nuclear physicists. On testing 18 bottles of California’s rosé and cabernet sauvignon produced in 2009 and onwards, it was found that wines produced after the disaster had increased levels of man-made radioactive particles. Two methods have been used by researchers to look for traces of a radioactive isotope called cesium-137. While the first method detects the particles through the wine bottles without having to open or destroy them, the second and the more accurate method for detection is to destroy the wines through heating and reducing them to ashes.Cesium-137 is then tested in those ashes. Inspite of the detection, the experts, according to the New York Times, have assured that there is nothing to worry about health because of the increased levels of radioactive waste in wines.

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Machine Learning: A blessing for organisations

Proper implementation of Machine Learning(ML) techniques in the organisation can turn out to be a blessing for the organisation. Leaders should consider that implementation of ML can be beneficial not only for them but for the whole organisation as well. Machine Learning can do the repetitive and mindless tasks, providing time for employees to focus on more important tasks. Out of the box solutions can be tempting but at the same time they should put some effort and investment in outlining the best usage of this blooming technology.

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Convenience in using Chatbots for Customer Service

The ultimate goal of any customer-facing department is to provide an advanced, instant and trouble free customer support. This real time customer support wasn’t as possible as it is today. With the advent of innovative chatbots, businesses can now offer their clienteles a convenient and self service solution. They have not only cut down on the long periods of time when customers had to wait both physically and virtually to have their queries addressed but also have cut down on the necessity of speaking with humans for the same. The question that arises in this context is that whether buyers are really comfortable in interacting with chatbots. Yes, it is true that many people found it pretty strange to speak to a bot initially, but as more people learned about the benefits of the artificial tools, the more convenient it appeared to them to communicate with chatbots. Chatbots can collect data based on recent interactions and respond to a message or a solution that directly suits the needs and preferences of the customers. The combination of humans and chatbots have always been successful in providing a results driven and around-the-clock hassle free service thus enabling them to increase productivity and customer satisfaction.

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Using Business Intelligence for Betterment

Data is very valuable for any business. It can help in decision making, planning, and more. Here, Business Intelligence comes into action. BI uses various softwares, applications, tools and services that enables access to and analysis of data. This improves and optimizes decisions and performances. Using Business Intelligence can help you to get more value by improving customer service, employee productivity, and more.

Following are the few ways one could get more value from Business Intelligence:

  1. Build real-time BI into your customer-facing services
  2. Improve employee performance through BI
  3. Improve Customer Service
  4. Predict new revenue streams
  5. Automate budgeting and forecasting
  6. Shift the emphasis to analysis
  7. Embed BI into other platforms
  8. Cut time wasted on data gruntwork
  9. Bring unstructured data on board

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Bridging the Gap Between IT & Business

Business and IT are two completely different fields. Yet there is always a need to mix them for the betterment of both fields. However, there is a huge gap between these two and to bridge them a Business Analysts is comes into role. A business analyst is responsible to take IT and Business together by using data analytics to analyse the ongoing processes and methods, determine plans and requirements and recommend future plans on the basis of current studies. Now days, data is very important for a business. It can help in planning, decision making etc and thus business analysts are a need for an organization. It is important for a business analyst to be good in both hard skills and soft skills. He must be good at sharing the information he was able to figure out with the team. Similarly, he must have a strong IT background.

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Technology In Business

Slowly and steadily we are moving towards digital transformation and its has become one of the important tasks for businesses. With the evolving technology, businesses are also growing and evolving. Here are the top 12 tech trends that we need to look for in year 2018 :

    1. Computer Vision
    2. Deep Learning
    3. Natural Language Generation
    4. Businesswide Networking Fabric
    5. Distributed Ledger Technology
    6. Edge Computing
    7. Quantum Computing
    8. Serverless Computing
    9. Augmented, Virtual and Mixed Reality
    10. Digital Twin
    11. Additive Manufacturing
    12. Nanotechnology

It is believed that to stay in the competition of business, one should welcome new forms of technology and implement them helping business to grow. This will bring the needed digital transformation and help in decision making and planning strategies. 



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Briefing Data Science

After Artificial Intelligence and Machine Learning, the next most emerging field in todays world is the field of Data Science. It is said to be the cousins of AI and ML and mainly deals with data. It intakes data, uses processes, algorithms and scientific methods to extract knowledge and valuable data from large data sets. This field is need of each and every type of organization. Whether it be business or an IT firm, every organization needs data for improvement. Thus, outcomes from the processing of data are further used for decision making and for improving current functioning.

People often gets confused between Data Science, Data Analytics and Big Data. The key difference between them is that Data Analytics and Big Data are components of Data Science. Data Science extract values from the output of Data Analytics and Big Data to solve problems.
The goal of Data Science is to extract business-focused insights from business. This could help organizations in many ways.

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Myths About Machine Learning

Every day a new problem statements emerges in the field of technology and machine learning proves to be a solution in most cases. These days, we tend to find smart solutions for our problems and machine learning is the backbone for the same. Thus, we can correctly state that Machine Learning has already invaded in our lives in some way or another.

However, with the emergence of machine learning, misunderstanding and misconceptions associated with it enters the field. There are few common myths about what and what not machine learning can do. Few of them are mentioned below:

  1. Machine Learning is AI
  2. All data is useful
  3. Anyone can build machine learning system
  4. Reinforcement learning is ready to use
  5. Machine learning will replace people

One could achieve better results if he avoids these common myths.

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