A data entrepreneur, Phillips comes to Magnetic from leading data analytics provider, Causata, which Phillips founded and led. The company was acquired by NICE Systems Ltd. Phillips also founded Touch Clarity, which specialized in personalization and machine learning. The company was acquired by Omniture, eventually becoming a part of Adobe. "Magnetic is unique in having access to both data from the world of advertising and the world of CRM. The future of marketing will not only demand that we understand what people are in-market for right now, but what every touch may mean to the expected lifetime value of a customer. Magnetic's data assets and technology platform position us well to deliver on that promise," says Phillips.

In the first post of our non-technical ML intro series we discussed some general characteristics of ML tasks. In this post we take a first baby step towards understanding how learning algorithms work. We'll continue the dialog between an ML expert and an ML-curious person. Ok I see that an ML program can improve its performance at some task after being trained on a sufficiently large amount of data, without explicit instructions given by a human. Let's start with an extremely simple example.

"AI ...surely will be a trend at least on the size of big data. It almost certainly will be a trend on the size of mobile. It might be a trend on the size of the internet. And maybe, just maybe, it'll be a trend on the size of software; that the software before machine intelligence and after will be two worlds that are very different from each other." It's undeniable that artificial intelligence (AI) is one of tech's hottest topics and a trend that is permeating every part of our world.

Buying an autonomous car may be in your future, but make sure it has a capable processor installed so the vehicle doesn't get in trouble with traffic police. Autonomous cars could make timely and more accurate decisions with Nvidia's new Tegra chip code-named Parker. The chip has the computing power to allow autonomous cars to recognize a wide range of signs, objects, signals, and lanes. Parker can also deliver 4K video to in-car entertainment systems. Details of the chip were presented for the first time at the Hot Chips conference this week in Cupertino, California.

As a beginner it is easier to get lost in the details and shear overwhelming nature of learning machine learning. More often the materials on blog posts and courses are often targeted at intermediates. But remember it is easier to get started without the math. You would still need the math, but it can come later. Below is a step by step guide to get started, but remember..

The buzz word is around for a few years in the analytic world, with companies investing heavily to fund the research. From understanding human perception to building self-driven cars deep learning comes with a package of great promises. I was thinking to myself as how I could put these concepts in simple terms which led this blog post. The foundations of deep learning has it's inspiration from the ability of the human beings to perceive things as they appear to him. The human perception is a miracle of nature.

There are places in the tech space where we cease to stare in amazement about what the tech can do. Instead we whine that the tech can't do more. Take the case of handwriting recognition, whether it's what we scribble notes onto a tablet or when we scan handwritten text into a PC. We wish that it was smarter, that it recognized more characters and that the text was searchable and shareable. To be honest, I shouldn't say "we".

The rise in consumer usage of ad blockers is leading to a few creative alternatives to try to achieve a'better relationship' between ad tech and web browsers. To wit Russia's Yandex, which has just announced it's adding a complaint button to its Android browser to lets users report ads they find annoying. Filing an ad complaint will send a report to Yandex which will initiate custom ad filtering for that user, using machine learning technology to hone the individual model over time. It will also be feeding intel back to advertisers so they can "create more targeted and effective campaigns that are relevant to users, reducing the need to install ad blocking software". So in theory users making use of the ad complaint button should see ads more pleasing/relevant to them over time, as well as eyeballing fewer ads they find annoying.

The more technology in business, the better – this is the common view. Different developments have so clearly transformed the ways we communicate, shop, share information and learn that there are many good reasons for the enthusiasm. However, what receives far less attention is how these new technologies impact workers and their productivity. Knowledge workers take on many roles – so many in fact that in 2011, Businessweek suggested that everyone is a knowledge worker to a degree. High-level employees who apply theoretical and analytical knowledge, acquired through formal education, to develop new products or services.

In human conversations, we rely on assumptions about how other speakers conduct themselves. This is known as the cooperative principle in the field of pragmatics. This principle breaks down into'maxims' for speech that speakers either follow or flout. In short, we rely on others saying truthful statements, providing as much information as possible, being relevant, and saying things appropriately. When speakers purposefully flout these maxims, it carries meaning that we can understand (e.g.