The movie you choose to watch may be heavily influenced by Netflix's sophisticated algorithms. Similarly, decisions like where you choose to dine and what you choose to wear are increasingly facilitated by predictive technologies powered by deep learning. Here are five ways that popular consumer tech companies Netflix, Yelp, Yahoo, StitchFix and Google improve your online experience with artificial intelligence. Historically, watching television is a uni-directional communication channel. You receive the content, but give no feedback to the content producers.

A single conversation can be interpreted in a variety of ways. A new AI system emulates the human ability to identify emotions and the tone of speech to establish whether conversations are sad, happy or neutral. This brings scientists closer to developing a potential solution. The AI system was developed by a team of researchers at the Computer Science and Artificial Intelligence Laboratory (CSAIL) and the Institute of Medical Engineering and Sciences (IMES) at Massachusetts Institute of Technology in Boston. In a news release, published Feb.1, the researchers explain the main functions of the system, which takes the form of an application that can be loaded into a smartwatch or wearable device.

"Artificial Intelligence": this term has become so popular/hyped/*add an adjective of your choice* in this decade, that we're talking about it more than ever. So much so that anything about AI becomes front page news. Tech media must be having a crush on AI for sure. Popular voices in the ecosystem, are so polarizing that you're left scared or excited. Mr. Singularity Ray Kurzweil says: But wait, even before we get started on what's missing in the whole picture, let me show you counter arguments too.

Stunning advancements in an array of the elements of robotics has seen quantum computing become a reality, AI's pass the Turing test and the advent of neural networks with dazzling sophistication. However, the holy grail is to create a real quasi-human intelligence - to simulate consciousness; the Self. However, there's a problem here, how can we simulate intelligent consciousness when we aren't able to answer this question; what does it mean to be conscious? This is arguably still humankind's greatest unanswered question. We must look past the philosophical and metaphysical definitions, such a discussion is more suited to a paper on philosophy and reasoning than a blog on artificial intelligence.

Loom Systems Ltd. is joining the growing ranks of companies applying artificial intelligence to the task of making sense out of the mass of data that overwhelms security professionals. The company today is announcing an operational analytics platform for real-time detection and resolution that reads log files and looks for anomalies. The Tel Aviv-based company says it does this by mathematically modeling the ways in which humans analyze such data, and then simulating the process via machine learning. It correlates each metric to baseline patterns in order to detect anomalies and predict future trends. The result is what the company claims is a 45 percent reduction in mean-time-to-resolution and a 93 percent reduction in log file clutter.

In many ways I think 2016 was the year that analytics hit the mainstream. At cocktail parties and in coffee shops, 2016 has been the year that we data scientists suddenly felt a bit like – dare I say it? Suffice it to say that in 2017, I believe that analytics, and the many domains it influences, will be a non-stop hit machine in terms of generating news headlines and ideas that fascinate us. In light of the recent Dyn attack, will 2017 be the year that your IoT device will turn on you? (Think Westworld, Humans, Terminator.) I think the answer is "yes."

Artificial intelligence (AI) is already infiltrating all industry verticals (and business processes) – as well as the home. Amazon's Alexa can order you an Uber, tell you the weather, pull up your dinner recipe – and even turn on your oven to begin your meal preparation. This is just the beginning. In fact, AI is projected to grow to become over a $5 billion market by 2020. So, what is the force behind this unavoidable AI phenomenon and momentum?

Over the few past years, the demand for real-time interpretation services has increased considerably. The globalisation of business can be considered a huge contributing factor for this phenomenon, as it has increased the opportunities for international trade and opened new markets for businesses all around the world. In order to be competitive and keep up with this increase in demand for interpreting services, developers have been working on technological solutions to meet the requirements for high-quality simultaneous interpretations, but can tech really replace humans when it comes to interpreting? Real-time translation systems include applications that can be installed on smartphones, computers, or other gadgets linked to the Internet. The words of the speaker are transcribed by a computer server, which analyses the content and selects the closest translation from a vast collection of phrase pairs in its database.

I first came across a real application of Machine Learning at work. We were supposed to prepare an application that will recognize frauds in the Zooplus shop. After months of trying different solutions: external providers, additional if statements in the code, fire-fighting scripts and such, we ended up with a conclusion that Machine Learning is the best tool for the job. Since then, we were trying to convince everyone around to invest in our education and pursue the Machine Learning path, but without any spectacular successes. Yet I had a chance to make my first step by playing a bit with Amazon's Machine Learning capabilities, so I consider myself a level 2 dummy.

Welcome to the second edition of D/SRUPTION Magazine addressing the key questions around disruption, innovation and digital transformation. A big thank you to all of our expert contributors for sharing their thoughts on the technologies and business models transforming the business world. Signing In – Is the world about to finally shake off its reliance on high cost oil? Day In The Life – Accenture's Chief Analytics Officer Narendra Mulani gives a glimpse into the life of an innovator AI Versus Skill Sets – How your future depends on whether you have a'proficiency' or a'pivotal' role in your business Innovation – Europe's largest innovation ecosystem is in. . . If you are interested in writing an article for D/SRUPTION magazine or the disruptionhub.com