We met up with Jeh Daruvala, CEO of Yactraq, a machine learning company with cutting edge technology that delivers business intelligence using audible or video input. In layman terms, their patent pending technology can be used to accurately search through tens of millions of hours of call center recordings TV shows, movies etc. in a fast and cost effective manner in order to provide actionable insights and intelligence. Here is what he had to say about one of the most coveted spaces in technology. Q: Can you please tell us about your company and the specific challenge that you are addressing? Yactraq empowers SMB & Enterprise clients with machine learning driven insights extracted from any audible media.

Begun by the legendary and often demanding Stanley Kubrick and finished by the equally legendary Steven Spielberg, AI Artificial Intelligence is a futuristic retelling of the classic 1881 Florentine Italian tale Pinocchio by Carlo Collodi. Of course most modern children and adults are only familiar with the Disney animated rendition which can be considered a Readers Digest Condensed version of the original story. Kubrick is often demanding in that if he can't make it happen and appear the way he wants it, he will abandon an idea or even an entire project. For instance, since he could not use the available technology at the time, to recreate Stephen King's topiaries come to life in The Shining, he abandoned the idea to a daunting maze. Similarly, he felt he did not have the creative team necessary to replicate a robot boy so real that it is nearly human, not without using a human child actor, but because of ET and Jurassic Park, he did feel his friend Spielberg was up to the task. The ambitious result is one of the best science fiction films ever made, one which I believe stands shoulders to Kubrick's 2001 A Space Odyssey.

In recent months we've seen investments in artificial intelligence (AI) from all the big players – Google, Salesforce, Amazon, and Microsoft – which suggest that AI everywhere may not be that far off. One area where AI is poised to make a big impact is in sales. Gartner predicts that by 2020, 85 percent of all B2B transactions will take place without human intervention. With that in mind, could your sales team eventually be replaced by robots? The experts suggest that AI could do a lot to help salespeople accomplish their targets and let them focus on what really matters – closing deals.

Responsibility for securing enterprise applications has been moving down the development lifecycle, and for good reason. It not only makes the enterprise more secure, but also saves companies time and money. For example, the average time to fix a vulnerability in IBM's application security solution has dropped from 20 hours to 30 minutes, according to a study Forrester Consulting released last month. Also, finding bugs earlier rather than later in the development process resulted in a 90 percent cost savings, the study indicated. If security at the application creation level is going to gain traction, however, it's going to require a change in the attitude on the part of developers.

Scientists at Stanford University have found a new method in predicting poverty through the use of machine learning and satellite images. The technique could make it easier for organizations to know where across the world their aid is needed most. Also, this could help governments develop a better policy to prevent or fight poverty. Using three data sources namely daytime images, night light images, and survey data, scientists built an algorithm to predict how wealthy or poor an area is. The results of the study have been published in the journal Science. "The idea is that if we train our models right, they help us predict poverty in areas where we don't have the surveys, which will help out aid orgs that are working on this issue," explained Neal Jean, co-author of the study and a doctoral candidate at Stanford.

Organizations often conduct door-to-door surveys to identify people living in poverty, but the downside is that these surveys are often time-consuming and expensive. Indeed, locating impoverished environments is still a challenging process for researchers, and the availability of accurate information is still lacking. Now, in a new study, scientists from Stanford University propose a more reliable method to map poverty in areas previously void of data -- by combining satellite images and making use of machine learning. Led by Stanford computer science doctoral student Neal Jean, researchers sought to determine whether the combination of high-satellite imagery and machine learning -- the science of designing algorithms that learn from data -- could predict estimates of areas where impoverished people lived. Specifically, they extracted information about poverty from these satellite images, and built upon previous machine learning algorithms to detect impoverished areas across five countries in Africa.

Machine Learning sounds like something out of an 1980s movie about a deceiving robot we end up fighting against to defend the existence of the planet. That may explain the distrust people have with it. How understandable is this distrust? Computers monitoring and absorbing information, learning and adapting to become better? Add to this distrust the purported technological singularity: the moment when artificial intelligence surpasses the human in any practical competency.

Scientists have developed a new software that can analyse the handwriting of any individual and accurately replicate it, an advance that may spark the comeback of the handwritten word in a world dominated by the QWERTY keyboard. Researchers at University College London (UCL) created'My Text in Your Handwriting', a programme which examines a sample of a person's handwriting and generates new text saying whatever the user wishes, as if the author had handwritten it themselves. "Our software has lots of valuable applications," said Tom Haines, from UCL. "Stroke victims, for example, may be able to formulate letters without the concern of illegibility, or someone sending flowers as a gift could include a handwritten note without even going into the florist," Haines said. "It could also be used in comic books where a piece of handwritten text can be translated into different languages without losing the author's original style," he said. The machine learning algorithm is built around glyphs – a specific instance of a character.

WEF names robotics as one of the areas of technology that could revolutionise finance in the next few decades. Biometrics, cloud computing, cognitive computing, blockchain technology, machine learning, quantum computing, and robotics are set to transform financial services over the next few decades, according to the World Economic Forum (WEF). WEF made the prediction in its "Future of Financial Infrastructure" report looking at blockchain technology, which was published on Friday. The influential non-profit rates the transformative potential of these new technologies alongside past innovations such as the personal computer, the internet, and smartphones. WEF's report focuses on blockchain technology -- referred to as distributed ledger technology in the above graphic -- so it does not actually give any concrete examples of how technologies other than blockchain might be applied to finance.

Mojtaba Arvin is a computer programmer who's fascinated by artificial intelligence . Right now, he spends his time as an information technology student .