SigmaWay Blog

Nowadays, Artificial Intelligence is not new to this world. AI is used in almost every field, especially in the field of business. To make business related decisions, you need data. This data is analysed and then plans and actions are decided. From identifying the problem to discover actionable business insights, right analysis of data can transform business operations and take it to higher level. 

However, with the power of AI you can automate this task of data analysing, transforming raw data into actionable business intelligence. One thing for which Artificial intelligence is hungry for is data! The more data you feed it, the better results it gives to you. But with the vast amount of data that AI requires, it also follows the concept of “Garbage in, Garbage out.” Feeding the right thing to AI should be the up-most priority to get results. For this reason, many companies are making changes in their data management space.

Read more at : https://www.technotification.com/2018/05/ai-changing-enterprise-data.html

Machine Learning is one of those technologies which have invaded in our lives to make it better. Without any doubt one can say that even though machine learning is in its initial phase, it has already become a part in our 24/7 running lives. Set of algorithms to use data, learn from it and then forecast future trends for that topic is expanding day by day.

Machine Learning and Data Sciences are often used together in order to predict future from varied data results available with us. One of the famous algorithm used in this field is SVM or Support Vector Machine which can be used for both regression and classification task. It uses the concept of hyperplanes and other mathematical functions in order to produce significant accuracy with less computation power. SVM has already proved itself in text categorization, image recognition, and in bioinformatics and now working in other.

To know more about how SVM works visit : https://towardsdatascience.com/support-vector-machine-introduction-to-machine-learning-algorithms-934a444fca47

Artificial Intelligence, Machine Learning and Deep Learning are now the most exploring topics for any techie. In spite of enough differentiation between these terms, they are often used interchangeably. To put an end to this confusion one could say that ML and DL are nothing but cousins of AI. 

Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Many applications of AI are being seen and used today. From voice-powered personal assistants like Siri and Alexa to self-driving cars and many more are applications of AI.

On the other hand, Machine learning is an artificial intelligence (AI) that is discipline geared toward the technological development of human knowledge. Machine learning allows computers to handle new situations via analysis, self-training, observation and experience.

Whereas, deep learning is a subset of machine learning which is a collection of algorithms used in ML to build and train neutral networks and act as decision making nodes.

So, though AL, ML and DL are interrelated but in this vast field of technology they all stand on their own and using them interchangeably would not be justice.

Read more at: https://towardsdatascience.com/cousins-of-artificial-intelligence-dda4edc27b55

It is said that with the future of technology another thing that is coming nearer to us is the risk of human extinction. Raymond Kurzweil, Google’s Director of Engineering and Futurist, published a book, The Singularity is Near, in which he welcomes a future in which AI will overcome human intelligence. Though we are still know that as super intelligence, but for now we do encounter AI in almost every aspect of our lives. Though in his book, the author welcomes AI as positive, most people fear job loss and the worst as human extinction. History indicates that any advancement in technology not always turns out to be bad. But, one could not ignore that with current technologies almost 45% of the jobs for which we are paid are now automated. This has become a topic of debate and no one knows what stands for us in advent of future. To know more visit: https://medium.com/@tjajal/automation-and-the-rise-of-meaningful-work-d1c7d596fee6

Now a day’s evolution and invention can be seen in every field. One thing common in these fields is the need of management. Any project is successful only if a proper management plan is adapted. Here, one evolution turned out to be a mirror of legacy. Agile approach is significantly opposite of the traditional waterfall approach. 

Waterfall Approach, also known as Liner Sequential Life Cycle, is highly structured and sequential in nature whereas Agile methodology is a practice that helps continuous iteration of development and testing in the software development process. 

Both of these approaches have their own strengths and flaws. Thus, it becomes important for a business to identify and select most appropriate approach.

To know more visit: https://www.itbusinessedge.com/articles/choosing-between-the-two-approaches-to-project-management.html

Blockchain has reached new heights for Big Data. It has strengthen cyber security and has been trying to create a  much more efficient world. There are numerous benefits of blockchain for Big Data. Improved data quality and security are the most important of all of them. It has also made data access easier. But there still are some challenges in the implementation. Find out more at: 

https://www.smartdatacollective.com/rise-of-blockchain-technology-mean-for-big-data/

Big data has started to play a vital role in gaming industries nowadays. Providing individual experience and maximizing the advertising of its products, gaming industry is far beyond ready to take big data to its peak. They have implemented techniques to collect data directly from online sources. They have data for marketing like never before. Big data has a new definition, a new meaning to everyone in the gaming industry, big data means a better consumer experience. Read more at: 

https://www.smartdatacollective.com/online-gaming-industry-uses-big-data-analytics-grow/

Hadoop has helped in shaping the future of weather forecasting in a much better way than the analyst could have ever predicted.  More factors can now be evaluated in the models. Also, the advancement in big data has allowed meteorologists to highly depend on the digital models. How exactly will Hadoop affect the future of meteorology? Find out at:

https://www.smartdatacollective.com/hadoop-predictive-analytics-improves-weather-forecasting-models/

Chatbots and AI are being reshaped everyday for a better outcome. They are available 24/7 for specialized customer service. They are better at engaging with customers. They are intelligent and hence can provide support to customers. Chatbots provide many advantages with their highly-capable functionalities. Find out all of them at: 

https://www.smartdatacollective.com/ways-chatbots-changing-customer-service-cycle/

In the current scenario, AI is a big game changer in customer service, interaction and transitions. It uses data to effectively target the right audience with right content for best consumer experience. It has made Customer Relationship Management smarter then ever. AI-enabled chatbots render an ideal customer success paradigm. AI uses knowledge-base for customer success team. It improves customer success automation. Read more at: 

https://www.smartdatacollective.com/how-ai-play-crucial-role-in-customer-success/

The union of artificial intelligence and big data analytics had awaken lots of business ideas in creative minds. Many of the start-ups are planning to come up with some innovative business ideas. As per the survey of 2018 around 97.2% of the companies are at the verge of implementing and launching AI and Big data initiatives. The executives of the companies now can visualise the potential. Large enterprises now can directly access the essential volumes and sources of data. These were used to understand the AI algorithm to resolve the patterns and its behaviours. Many companies like American Express and Morgan Stanley have publicly shared their success stories.

For more information, visit:

https://sloanreview.mit.edu/article/how-big-data-and-ai-are-driving-business-innovation-in-2018/

Heard of “PokemonGo” before? This can be one of the best elucidated examples of augmented reality. So, augmented reality is basically an interactive technology that superimposes an image generated by computer on the user’s view of the real world. Virtual reality is different as it displays the computer generated environment to the user but AR instead of replacing, adds image or element to the display.

In this fast pacing technological world AR is also presenting itself. There are many examples of AR such as Google glass, Google lens (for blind people), AR coloring books etc. To level up the standards of AR, researchers are developing holograms. 

Want to know more about augmented reality? Visit:

https://www.livescience.com/34843-augmented-reality.html

A number of trends lately has helped in shaping the Big Data. But, digital transformation is one of the key ones of all. It is being predicted that it might change the ways of data science profession in the years to come. Key features like flexibility, access to expertise, data security, etc. has helped it overcome most of the challenges. Many are saying that data transformation is the next major phase of Big Data. Find out more at: 

https://www.smartdatacollective.com/digital-transformation-unexpected-renaissance-age-of-big-data/

Artificial Intelligence has played a major role in video marketing since always, and it always will. Producing numerous new algorithms to find the related videos for the customer is one of the key features of AI in video marketing. Increasing the reach of video, making more people engage to it, and many more advantages of AI makes it one of the key components in video marketing. Read more at: 

https://www.smartdatacollective.com/fascinating-ways-ai-intersecting-video-marketing/

Cloud computing has helped in evolving the robot technology to greater heights. More information and data are being delivered in real time. Robots have started to learn much quicker. Robot movies have started to become reality. They have started helping us with healthcare. Read more at: 

https://www.smartdatacollective.com/merging-big-data-cloud-computing-future-robotics/

With 5G on its way, talks about 6G has already started. 5G itself is about to bring a lot of changes for the users around the world, but what about 6G, how drastic its birth would be? They will process data better than ever before. There will be changes, far too significant than when the wireless technology introduced. They may have a great impact on the future of wireless technology. Read more at: 

https://www.smartdatacollective.com/will-6g-force-cell-phone-providers-redesign-data-servers/

Driver-less cars are here. But do we have the key things to get it done right? What about the data, Big Data, do we have enough of it? AI isn’t only about software, it is also the integrated hardware that does the job, the right sensors are very much needed to make a car move on its own without a driver. Can the show still go on? Find out at: 

https://www.smartdatacollective.com/automated-car-tech-data/

Artificial Intelligence has always been an integral part of the gaming world. When we play a single player game, against computer, who actually is playing against us, it is the artificial intelligence. But the role of AI may extend further, it may be used for mitigating the risk of fraud. They may help in building better relationships with the long-time gaming customer. So, have you ever wondered about  the future of AI in gaming industry? Find out at: 

https://www.smartdatacollective.com/gaming-platforms-adopt-ai-customer-risk-profiling/

A number of times, users tend to fill in false demographic inputs in different surveys to earn rewards and enjoy premium benefits. But, visual data may change that for these organisations. Facial Recognition can help authenticate those inputs and reduce the rate of response errors in the survey, making it way more valid than before. Read more:

https://www.smartdatacollective.com/big-data-facial-recognition-tools-launch-consumer-research/

Deep Learning, the subset of AI which helps in Image Recognition, Speech Recognition and much more. Now, it may also be useful in analyzing images of the galaxy and help us find out how they were evolving. Recently, a group of researchers, trained a deep learning program using galaxy simulations that helped in analyzing the images of the galaxy from the Hubble Space Telescope. Read more at: 

https://www.sciencedaily.com/releases/2018/04/180423125115.htm