When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on "big" data to a class of analytics that requires less, or "small" and more varied. Transitioning from big data to small and wide data is one of the Gartner top data and analytics trends for 2021. These trends represent business, market and technology dynamics that data and analytics leaders cannot afford to ignore.

When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on "big" data to a class of analytics that requires less, or "small" and more varied. Transitioning from big data to small and wide data is one of the Gartner top data and analytics trends for 2021. These trends represent business, market and technology dynamics that data and analytics leaders cannot afford to ignore.

As a long-standing function of business, accountancy has been continually refined by changes in technology. As the Greek philosopher Heraclitus claimed over two-and-a-half thousand years ago, "the only constant in this world is change". This is still true today, and it is only becoming increasingly profound thanks to our cultural, societal, technological and physical evolution. So, when it comes to finance and accounting, what are the key drivers of change? Analysis of the business environment has long been a staple of any successful organisation's strategic management – whether it's to understand any possible opportunities and threats, making comparisons to competitors, or to support specific strategic feasibility.

It is hardly "breaking news" that technology is radically changing almost every aspect of our lives and the world around us - but we talk far less about the challenges that come along with this rapid evolution. And we certainly don't know the answer to the important question: what is the ultimate outcome of this Digital Revolution? To understand this issue, we should recognize exactly how fast things are really changing. A good metric for this purpose is the floating-point operation: a single mathematical calculation (like addition or multiplication) on two numbers that have decimal points. In 1954, IBM introduced the first mass-produced computer with dedicated floating-point arithmetic hardware. The IBM 704 was regarded as the only computer that could handle complex math at that time: it could execute up to 12,000 floating-point operations per second, or FLOPS.

We hear a lot about AI and its transformative potential. What that means for the future of humanity, however, is not altogether clear. Some futurists believe life will be improved, while others think it is under serious threat. Here's a range of takes from 11 experts. Join nearly 200,000 subscribers who receive actionable tech insights from Techopedia. That is the first sentence in Yudkowsy's 2002 report entitled "Artificial Intelligence as a Positive and Negative Factor in Global Risk" for the Machine Intelligence Research Institute (MIRI).

Many people worry that "AI" will usher in a new Industrial revolution where machines replace humans. My take is that it will be more like the Printing press revolution that launched the Age of Enlightenment! The effect will be less of soaring productivity but more of better decision-making leading to a SMARTER society. Part of the problem is the misnomer, "AI or artificial intelligence" (which may be great marketing). Instead, if we called it what it is, i.e., "ML or machine learning", things will sound less ominous and convey a more realistic picture.

Our world really is more unpredictable than ever. Even the best-laid strategies are being disrupted, whether they are focused on the workplace's culture, technical environment, market dynamics, customer behavior, or business processes. But central to these uncertainties is one constant: an algorithm guiding every step along the evolutionary trail to digital transformation. "Each company has a predictable algorithm that's driving its business model," said Sathya Narasimhan, senior director for Partner Business Development at SAP, on a live episode of Coffee Break with Game Changers Radio, presented by SAP and produced and moderated by SAP's Bonnie D. Graham. "When we understand how data affects outcomes and bring sensor data online, it's easier for the infrastructure to process this information to create additional insights," she explained.

Marcel Shaw is a Systems Engineer for Ivanti. Artificial Intelligence (AI) promises to dramatically improve technology in our homes and in the workplace. We all know what it's like to lose our keys. One day Alexa will notice we've forgotten our keys, or our wallet, and alert us before we leave the house. How could that be possible? Besides personal applications, AI is beginning to integrate into corporate and government networks.

ITC Infotech, a global scale full service provider of technology solutions and a fully owned subsidiary of ITC Ltd, successfully concluded the third chapter of'iTech 2017', its annual technology innovation & co-creation platform. Microsoft Azure was the official cloud partner for the event. At the Start-up Showcase, innovative start-ups from across the country got an unique opportunity to present their solutions in front of ITC Infotech's global client representatives and senior leadership of ITC Infotech and ITC Ltd.. These solutions, based on Artificial Intelligence, Machine Learning, AR, VR etc., addressed real-world industry challenges crowd sourced from across ITC Infotech's global client base, as well as from ITC Ltd. Two start-ups, inFeedo and Aindra won a grant of Rs. 5 Lacs for a paid POC each, and the chance to co-develop their solution with ITC Infotech as a part of its go-to-market strategy.

The European Telecommunications Standards Institute (ETSI), which wrote the original specification for network functions virtualisation (NFV), has set up its experiential network intelligence industry specification group to handle the task. He sees many parallels between the evolution of cars and where networks can get to. "Years ago, cars were painfully manual, but we've made it much more convenient and 14 years ago we started looking at self-driving cars, which is an absolute disruptive change." In order for self-driving networks to become a reality, vendors and providers must fully collaborate, he says. Interestingly, ETSI's AI initiative, which has an initial two-year work programme, is coming from vendors, ETSI director general Luis Jorge Romero told GTB at Mobile World Congress.