The insurance sector is one of the most old-fashioned and resistant to change -- so artificial intelligence will have an even greater effect. The insurance sector is one of the most old-fashioned and resistant-to-change space, and this is why AI will have a greater impact on that with respect to more receptive industries. The collection of data of new types (i.e., unstructured data such as reports, images, contracts, etc.) and the use of new algorithms are disrupting the sector in several ways. This is a really simplistic representation of the insurance business in the last fifty years, and I am aware that insurance experts might disagree with me in many different ways. There are a couple of further features to be pointed out: first of all, insurance has historically been sold not bought, which means that brokers and agents were essential to tracking new customers and to even retain old ones. In addition, it is an industry which is by definition rich of data because they collected anything they could, but is also one of the less advanced because either many of those data are unstructured or semi-structured, or the model used are quite old and simple.

Cyrus Radfar is a founding engineer of AddThis, which was acquired by Oracle. Mankind has a complex relationship with the notion of Artificial Intelligence. Tinged with both fear and fascination; the timeline for AI development is punctuated by cultural and historical events that have brought with them new speculation and theories. Mechanical men and artificial beings were a prevalent feature of Greek myth, including the golden robots of Hephaestus and Pygmalion's Galatea; Mary Shelley's Frankenstein introduced generations of readers to a terrifying idea of non-human intelligence; and, in more recent times, the dialogue has included the idea of computerized tech becoming a threat to the existence of our species. These recent concerns culminated in the 2015 "Open Letter on Artificial Intelligence", signed by over 150 people including Professor Stephen Hawking, and have been perpetuated by Elon Musk's occasional ominous remarks.

Artificial Intelligence (AI), machine learning and automation are technology trends dominating discussions in many different industries at the moment and cyber security is no exception. As cyber criminals become more advanced and the threat landscape continues to develop, businesses are looking to new technologies that can help secure their organisation in a more proactive way. According to Dave Palmer, director of technology at Darktrace, this move to the so-called "age of automation" is an inevitable and much needed one: "When you think about networks getting faster and big data, it's been just as useful for the bad guys as it has for the good guys, but machine learning changes that. This whole era of automation and machine learning is going to be about handing complex problems off to the machines to do some of that solving for us and bringing humans out. "Not that the attackers won't benefit in some ways from that, but on balance, overwhelmingly this is an area of science that is much more of benefit to defenders than attackers and that is really the first time we've seen that." What's clear is that the traditional model of endpoint protection through the likes of antivirus software is no longer enough, as Palmer explained: "People are falling out of love with the idea that year on year generation of improved perimeter defenses is making a difference.

The insurance sector has entered a phase of profound transformation. Numerous Insurtech startups--around 1,000 according to Venture Scanner map--have popped up to challenge the traditional model by generating more than 16 billion dollars in the last years from insurance companies. I believe that we will see a completely changed insurance sector in the medium term. But I consider it a joke for an industry conference to show a picture of a newborn and sell it as the last intermediary or the last client to have purchased an insurance policy. I'm convinced that insurance companies will still be relevant in the future, or will become even more relevant than they are now, but these companies will have to be insurtechs, or players who use technology as the main enablers for reaching their own strategic objectives.

CES 2017 is all wrapped up but there's still plenty of buzz around the latest and greatest gadgets and gear that debuted at the annual tech mecca in Las Vegas. There were thousands of new products to digest, between wallpaper TVs, next-gen wearables and drones, and "smart" versions of pretty much every appliance and tool we use in our everyday lives. As expected, AI took center stage at this year's event. Most products were AI-powered, "smart" or "intelligent." It's already part of the lives of millions of people, and most customers at CES expected to see sufficiently mature and useful applications of AI.

Many technology commentators got all excited a few months ago when Microsoft launched how-old.net, a website where users could upload a photo and the site would guess the age of the person in the picture. The service was a great way to showcase the opportunity that applying artificial intelligence to a problem set introduces. Insilico hopes to deliver a similar sort of an offering, but with a far more important purpose. Insilico Medicine is an organization focused on aging research. Headquartered at the Emerging Technology Centers at the Johns Hopkins University Eastern campus in Baltimore, it has R&D resources in Belgium, Poland, Russia and China employing 39 scientists worldwide.

As stated in my previous article, I want to show next where AI is taking us in the future. However, I need to describe first how AI has evolved during its short life. I have written three articles that develop this theme. In this first article, I briefly outline the background context with what has been achieved up until the start of the millennium. In the next article, I describe the impact that machine learning paradigms such as genetic algorithms and neural networks have made in the last 20 years. Finally, in the third article, I outline our future in a world dominated by AI.

Hosts, BootstrapLabs, launched the Applied Artificial Intelligence Conference in 2016. The event was decent and, with about 400 registered attendees, was reasonably well-attended. Last year's speakers included representatives from IBM Watson, FaceBook, Uber, and Accenture. The conference intends to gather researchers and scientist as well as A.I. practitioners. It felt like a first time event last year for sure, but we can see this event growing in stature in 2017 given the location (San Francisco) and the fact that the theme is becoming more popular.

It's been an interesting day. The 45th President of the United States of America took office just two hours ago, and he is clearly unlike any other President that has gone before him. So just for fun, I thought I might feed his inauguration speech into Watson in real-time, in order to see what the smartest computer in the world had to say about it. Would he notice any anomalies, or insights that the professional political commentators might have missed? Might we some people respect Trump a little more if they looked at his speech more analytically than emotionally?

Plentiful high-quality data is the key to great machine learning models. But good data doesn't grow on trees, and that scarcity can impede the development of a model. One way to get around a lack of data is to augment your dataset. Smart approaches to programmatic data augmentation can increase the size of your training set 10-fold or more. Even better, your model will often be more robust (and prevent overfitting) and can even be simpler due to a better training set.