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.

According to media reports, the acquisition reportedly happened earlier but was not publicly announced yet. An Apple spokesperson has now responded, saying: "Apple buys smaller technology companies from time to time, and we generally do not discuss our purpose or plans." Founded in 2013 by Anil Sethi and Karthik Hariharan, Gliimpse provides a secure platform where consumers can manage and share their medical records and info. According to Sethi's LinkedIn page, Gliimpse -- like many startups -- was born of a personal need. In recent months, Apple has acquired HealthKit, CareKit and ResearchKit startups that allow patients, doctors and researchers to access important health and wellness data via a range of mobile devices.

The AuctionBytes Blog has been giving a voice to online merchants since its launch in 2005. Named one of the world's top 30 blogs in 2008 by "Blogging Heroes." Everyone is buzzing about Artificial Intelligence and machine learning these days, and eBay is no exception. Now comes the revelation that eBay data scientists are using the technology in its Best Match search algorithm. In a post on Monday, eBay wrote, "The largest scale application of machine learning technology at eBay is currently Best Match, the algorithm used to optimize relevance for buyers during their shopping experiences."

IP Cores Designed for HSA Historically GPT has developed IP specifically for the China market. The company recently announced a range of new IP licensing offerings along with an enhanced geographical licensing program. With the company-wide adoption of HSA standards, GPT now licenses IP worldwide. All GPT processors include HSA support and the company is now offering world-class HSA-enabled processors to its customers. The HSA enabled IP core which is sampling now in silicon is a first implementation of GPT's 3-in-1 Unity architecture designed for multidimensional signal processing including image and video processing.

Stephanie Hay is the head of content strategy at Capital One and led the design team that created Capital One's Amazon Alexa skill earlier this year. People say them every day -- after the waiter delivers food, when finishing a customer service call or before launching a rocket into space. These two words are just fine in the context of real life, human-to-human interactions. They're also covered as a feedback loop in traditional UI design, where we can create a button that says "Done" or "Save" and know exactly to which touch point people are referring when they tap it. In human-to-robot interactions, however, that's where things get tricky.

One of the biggest problems in solving poverty worldwide is the scarcity of reliable data in developing countries. Researchers have sought to address this by combining satellite imagery with artificial intelligence to identify impoverished areas from space, the BBC reports. A team from Stanford University trained a computer system and surveyed information in five African countries. Researchers Neal Jean, Marshall Burke, and their colleagues say this method could go a long way in tracking and targeting poverty in specific countries. Burke, an assistant professor of Earth system science at Stanford, says, "The World Bank, which keeps the poverty data, has for a long time considered anyone who is poor to be someone who lives on below 1 a day."

Machine learning is a top priority, but there's also space for the system to be applied in the field of planning and scheduling -- perhaps not the most … Mojtaba Arvin is a computer programmer who's fascinated by artificial intelligence . Right now, he spends his time as an information technology student .

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.