When a given task becomes enjoyable, people tend to work harder and perform better. Schools and teachers have been using this principle to heighten the interest of young students in early childhood care and pedagogy. Integrating games into traditional teaching methods have been significant in enhancing their understanding and preparing them better for the next grade. Companies across the world too have started seeing a lot of potential in the similar application of game-design elements in non-game contexts. This becomes extremely relevant in a time when millennials make for nearly half of the workforce.

As I had always been in love with technology, I have a habit of exploring new technologies. I like to read about what's happening in the tech world and how these new technologies can disrupt the current industries. In the recent past, as I was exploring and reading extensively on what impact can recent technologies have over our lives, I quickly noticed that there were a few terms that were thrown around almost all over the place: AI, Data Science, Machine Learning, Deep Learning. Although, technically wrong, let's refer to these technologies as AI (Artificial Intelligence) in general. I was kinda hooked and I started to casually read about them as these technologies naturally appeared to have the potential to disrupt any industry imaginable.

NEW DELHI: Researchers at the Indian Institute of Technology (IIT) Madras are working on two projects that use artificial intelligence and data analytics to improve learning outcomes for students. They are analysing data from open-access learning portal NPTEL (National Programme on Technology Enhanced Learning) in order to reduce dropouts and improve understanding. NPTEL is a platform where teachers from the IITs put up videos on subjects generally related to engineering and science. Students can view them and get certifications for the courses they complete, at a nominal fee of Rs 1,000. In fact, engineering colleges have been mandated by AICTE (All India Council for Technical Education), the apex body for technical education in India, to cover 15-20% of their undergraduate syllabus through NPTEL.

This op-ed was originally published in Newsweek on November 20, 2019. At least to some extent in last Wednesday's Democratic debate, and more so in the earlier ones, candidates have offered soundbites touting crowd-pleasing "silver bullet" proposals to raise earnings and reduce inequality among US workers. To improve workers' skills, Bernie Sanders and Elizabeth Warren call for free college for all. To raise wages, many call for a rapid increase in the federal minimum wage to $15 an hour as well as resurgent unionism. And Andrew Yang continues to call for "universal basic income" in response to potentially large-scale job displacement from automation.

WBS Training Ltd organizes workshops and conferences for the capital markets and treasury divisions of investment companies worldwide, with all our efforts centered solely on the education of our clients. WBS Training does not operate to present dozens of events every year. Instead we select only the most innovative, pertinent and dynamic subjects, thus bridging the gap between the latest theoretical developments through to proven practical trading floor requirements. Therefore, we aim to ensure that such requirements can be effectively implemented in the real financial world. Our depth of experience within the training environment provides us with a greater knowledge and understanding of what our clients require from financial business training.

An education system has an embedded responsibility to absorb, internalize, equip and sometimes orchestrate change. Change that is inevitable and necessary. The world as we experience today is on a perpetual continuum of redefinition, deconstruction and invention. Classroom management and pedagogy have been kept under close radars primarily to incorporate methodologies which brew conducive environments where the already shifted focus to student centered learning gains further profundity in synthesizing knowledge. Future advancement will invariably lead to Artificial Intelligence being an integral thread of the teaching and learning process.

Advanced, graduate-level book for data scientists who wish to move into deep learning.

As I've been focusing more and more on the Big Data and Machine Learning ecosystem, I've found Azure Databricks to be an elegant, powerful and intuitive part of the Azure Data offerings. Over my last 12 months at Slalom, I have had the incredible opportunity to travel across Canada and work hand in hand with the brilliant folks at Microsoft's Data & AI practice and Databricks experts to lead project engagements, deliver technical hands-on workshops, listen to the industry experts - the folks doing Data Science for a full time living - and absorb everything in between. There's a common theme across the industry verticals that's going to be our point of discussion today. The hot topic of 21st century tech is Machine Learning - some flavor of AI/ML is thrown into almost everything we find these days (I'm pretty sure I spotted a "genius" AI/ML toothbrush at Shoppers Drug Mart today). The reality is, the mathematical techniques that power Machine Learning models have been around for almost a century.

Machine learning technology has the capacity to autonomously identify malignant tumors, pilot Teslas and subtitle videos in real time. The term "autonomous" is tricky here, because machine learning still requires a lot of human ingenuity to get these jobs done. It works like this: An algorithm scans a massive dataset. Engineers don't tell it exactly what to look for in this initial dataset, which could consist of images, audio clips, emails and more. Instead, the algorithm conducts a freeform analysis.

AI analysis may identify certain emotional traits, without providing a more holistic perspective on the person exhibiting those traits. Should AI-driven systems measure and mimic human empathy? There are two sides to this question: AI is being employed to deliver human-like responses, and is also capturing and analyzing human responses to address their states of mind. The frontline of many of today's enterprise AI systems is customer service -- chatbots and online response systems that attempt to deliver friendly, informed services on demand. Some systems come close, but AI may not be ready to deliver the kind of empathy that a live human agent can provide – such as going the extra mile to help a customer.