NIIT digiNxt

The AI learning adventure explores intelligence and its connection to engineering and technology.  Using ideas about human intelligence and intelligence more broadly, engineers can create “artificial intelligence,”; that is, impart “human” intelligence into machines or technology (Classical AI) or design technology that can itself “create” intelligence (future AI).  In fact, understanding how the brain works—”reverse-engineering the brain”—and understanding how engineers design intelligent machines—machines that replicate human intelligence—is one of the “Grand Challenges of Engineering” as set forth by The National Academy of Engineering (NAE). The implications and benefits of understanding the brain are many.  In addition to advances in the treatment of brain injuries and diseases and advancements in communications technology and computer simulations, understanding the brain will allow the design of intelligent machines with even more signicant societal impacts....

You've likely heard of conscious thought and subconscious thought, but humans may in fact possess three levels of consciousness, a new review suggests — and this concept could help scientists develop truly conscious artificial intelligence (AI) someday. Though AI technology has been advancing at a rapid clip, in many ways, computers still fall short of human performance. "Human consciousness is not just about recognizing patterns and crunching numbers quickly," said review co-author Hakwan Lau, a neuroscientist at the University of California, Los Angeles. "Figuring out how to bridge the gap between human and artificial intelligence would be the holy grail." [Super-Intelligent Machines: 7 Robotic Futures] To address the controversial question of whether computers may ever develop consciousness, the researchers first sought to explore how consciousness arises in the human brain. In doing so, they outlined three key levels of consciousness. Th...

More and more we are having discussions with businesses about a different way of approaching business challenges, from digital marketing to analytics and insight. A way of working which allows the business to inform their longer-term strategic decision making whilst seeing positive business benefits in the short-term. An approach which excites customers and empowers employees, whilst being cost-effective and flexible enough in today’s ever-changing digital world. More and more we are talking to them about a Test & Learn approach. Test & Learn, simply put, is a set of practices that allows a business to try out new ideas and concepts, either with a small subset of customers or in a limited number of locations (e.g. in only a handful of stores) in order to understand the impact it has on factors such as customer experience, employee productivity and sales. There are many reasons why a Test & Learn approach should be considered as part of any business strategy, but...

According to the prediction of  two-thirds of Global 2000 Enterprises CEOs will center their corporate strategy on digital transformation. A major part of the strategy should include machine learning (ML) solutions. The implementation of these solutions could change how these enterprises view customer value and internal operating model today. If you want to stay ahead of the game, then you cannot afford to wait for that to happen. Your digital business needs to move towards automation now while ML technology is developing rapidly. Machine learning algorithms learn from huge amounts of structured and unstructured data, e.g. text, images, video, voice, body language, and facial expressions. By that it opens a new dimension for machines with limitless applications from healthcare systems to video games and self-driving cars. In short, ML will connect intelligently people, business and things. It will enable completely new interaction scenarios between customers and compan...

Test automation has always been attractive because it reduces the mundane testing efforts and accelerates the process of testing. Almost every organization is automating test cases, but the return on investment is not always as expected. Often one asks if the tools good enough to deliver the ROI? The answer may not lie in the capability of the tool, but somewhere else. The issues typically associated with failed test automation “experiments” are the long time to create the test automation suite, difficulty of scripting and maintenance, the need for specialized development resources, and a lack of involvement of the product owners or the subject matter experts. One solution to maximize the scalability of the test automation is to approach this through scriptless test automation. Scriptless test automation is like choosing the best and leaving the worst. It empowers the testers and business users to automate test cases without worrying about the coding. The problem of coding ...

Who is a data analyst? Data Analysts deliver value to their companies by taking data, using it to answer questions, and communicating the results to help make business decisions. Common tasks done by data analysts include data cleaning, performing analysis and creating data visualizations. Depending on the industry, the data analyst could go by a different title (e.g. Business Analyst, Business Intelligence Analyst, Operations Analyst, Database Analyst). Regardless of title, the data analyst is a generalist who can fit into many roles and teams to help others make better data-driven decisions. The data analyst in depth The data analyst has the potential to turn a traditional business into a data-driven one. While often data analyst positions are ‘entry level’ jobs in the wider field of data, not all analysts are junior level. As effective communicators with a mastery over technical tools, data analysts are critical for companies that have segregated technical and busines...

We live in a world increasingly driven by data. The term 'big data' refers to extremely large sets of digital data that may be analysed to reveal patterns, trends and associations relating to human behaviour and interactions. Companies can use this information to their  advantage; automating processes, gaining insight into their target market and improving overall performance using the feedback readily available. Here we look at some of the businesses integrating big data and how they are using it to boost their brand success. 1. Amazon The online retail giant has access to a massive amount of data on its customers; names, addresses, payments and search histories are all filed away in its data bank. While this information is obviously put to use in advertising algorithms, Amazon also uses the information to improve customer relations, an area that many big data users overlook. The next time you contact the Amazon help desk with a query, do...