By Ashwini Anand When virtually everyone claims to use "artificial intelligence", "big data" or "machine learning" to "disrupt"/ "revolutionize" one industry or the other, I would not blame you for being sceptical about the much-touted AI revolution in Fintech. But, before you throw the baby out with the bathwater, let us delve a little deeper and understand if there is a real problem in lending and if AI can help solve it. Is there really a problem in the banking system? Banks and financial institutions, with some notable exceptions, are struggling with bad loans. According to India Ratings the average Impaired Asset Ratio - the sum of gross NPAs and restructured advances (a measure of the stress on a lender's balance sheet) stands at 12% of advances and is slated to rise to 12.5%.

"Every aspect of our lives will be transformed. In short, success in creating AI could be the biggest event in the history of our civilization." From self-driving vehicles to virtual assistants, artificial intelligence (AI) is evolving at a rapid pace. It has the potential for tremendous good – IBM's Watson improving cancer treatment with genomic sequencing as an example. Additionally, AI has been used to bring new art into the world – "Symphonologie" is an orchestra piece created with the help of AI.

Leading figures in the field of artificial intelligence discussed its present and potential future impact on individuals and nations at the John F. Kennedy, Jr. Forum Friday. Kennedy School lecturer and national security expert Juliette N. Kayyem introduced the topic by discussing the current prevalence of artificial intelligence and the significant shifts the technology may cause in relations between various groups and industries. She noted the tensions that may arise when trying to find a role for artificial intelligence in everyday life. Panelists then discussed how artificial intelligence has influenced their particular work and society more generally. Edward W. Felten, the deputy chief technology officer of the White House Office of Science and Technology Policy, commented on a recent White House report that explained the challenges faced when trying to incorporate artificial intelligence into the government.

Today, businesses need to be able to predict demand and trends to stay in line with any sudden market changes and economy swings. This is exactly where forecasting tools, powered by Data Science, come into play, enabling organizations to successfully deal with strategic and capacity planning. Smart forecasting techniques can be used to reduce any possible risks and assist in making well-informed decisions. One of our customers, an enterprise from the Middle East, needed to predict their market demand for the upcoming twelve weeks. They required a market forecast to help them set their short-term objectives, such as production strategy, as well as assist in capacity planning and price control.

Machine Learning for Artists ml4a.github.io is an in-development book about machine learning, being written by Gene Kogan (@genekogan) and Francis Tseng (@frnsys). The delays in the release schedule can be attributed to two factors. Changes in scope: initially, ml4a was to be a collection of reading materials for a single class, and now seeks to be more broadly useful, necessitating the development of new features and chapters. Over time, Demos and Guides were elevated from supporting materials to the book into full-fledged sections of their own. The goalposts keep moving: since the initial version of this page went up, we've seen AlphaGo, the announcement of TensorFlow, deep generator nets, synthetic gradients, stacked approximate regression machines, and many other major milestones in the field.

In science fiction, artificial intelligence (AI) systems are often bent on overthrowing human civilization, or they are benevolent caretakers of our species. In reality, machine-learning is already with us, evolving out of search engines like Google and seeping into our everyday lives without much fanfare. To highlight exactly how AI is debuting in a less-than-Hollywood (but still quite impactful) style, Business News Daily spoke with six companies rolling out AI products that will recalibrate and streamline everyday business operations. From conducting marketing research to monitoring for nefarious activity on stock exchanges, these systems can do it all. In stock exchanges around the world, plenty of people are trying to tilt the table in their favor to ensure their investments pay off.

Banking has come a long way from its roots in 2000 BC when merchants were using grain as currency for loans (Davies 1994). During the Italian Renaissance, the banking process became more sophisticated as services such as deposits and withdrawals were added (Varadarajan 2014). With the continued modernization of commerce, the industry progressed at an exponential rate. This progress eventually tapered off when the 2008 Financial Crisis hit, effectively tarnishing consumer trust in financial institutions. In the aftermath, it was apparent that in order for banks to remain profitable, a new model was needed – one that focused specifically on the experience of the customer.

They are planning our days, making our reservations, ordering our cars. We talk to Alexa, Siri, Cortana and Google like we would a human assistant. But how do these AI systems compare? Here's a look at what they do, how they're marketed and what they'll do next. Origins: Siri was perhaps the first virtual personal assistant to enter the mainstream, debuting on the iPhone in 2011. Functions: Siri only widely opened to third-party apps this year with the arrival of iOS 10.

PA's Stefan Knapp, a business transformation expert, shares his view on robotics and artificial intelligence, and whether AI will replace human manpower. The use of AI in the labour market is increasing, and one example is IBM's cognitive agent Watson that is not only able to solve basic work tasks, but also helps diagnose rare diseases. Stefan refers to PA's new benchmark of the 20 leading AI vendors that also identifies trends in the market. The benchmark shows an increase in the use of AI, a development that may concern unions and human employees. "However, nothing indicates that human jobs are in any kind of danger. On the contrary, when cognitive agents take over human routine tasks, we get more time to solve more productive and complex tasks," says Stefan.

Google and Blizzard made a surprise announcement at the recent Blizzcon event in California. Through the machine learning platform DeepMind, the two companies will teach artificial intelligence to play StarCraft II. In doing so, the tech and gaming giants are hoping to teach algorithms to adapt to real-world scenarios and process data much closer to how humans do. AIs have been beating professionals at Chess and its more complex Japanese counterpart Go for some time now, The Verge reports. However, the set rules and rigidity of the patterns when playing both games are no longer enough to help machines learn flexible thinking.