Nicola Mendelsohn: "[Brands should be] starting to test [virtual reality] but it's very early days and not many people have these devices yet. It depends what your objective is. If your objective is testing innovation and being seen as an innovative company then try it because that would fulfil the objective. We only started shifting [the Samsung VR] in November, the Rift is only going out now, so is it actually in the hands of consumers? Matt Brittin: "I encourage people in the UK, which is one of the most creatively advanced countries globally, to be experimenting with new stuff all the time. People will want more immersive experiences… try to experiment with new technology, how does it help people to tell stories in new ways?

When I'm usually speaking about Artificial Intelligence, I'm involved in ethical conversations ranging from self-driving cars programmed to kill you in a crash for the bigger benefit of others – like school kids running front of your vehicle – to a robot world domination and human slavery. But today I wanted to write about chat bots. Yes, those little bots that will be appearing on your messenger apps in no time. Chat bot is an artificially intelligent bot, which allows you to have a pre-programmed conversation with a company or a media in your messenger app. It works just like you'd have a chat with your friends – except that you're speaking with a machine. Quite handy if you want to order for example a burger or a taxi via messenger app instead of browsing through different apps and sites.

According to experts, 2016 may finally be the year that artificial intelligence comes into its own -- not in the science fiction "robots will take over humanity" sense, but in a much more practical and useful way. AI is already excellent at problem-solving -- when it comes to finding patterns, it can usually solve a problem much faster than its human counterpart. For the most part, though, AI still very limited in scope, and the dreams of a general intelligence are still far off. To some, AI being able to execute nearly any task that humans can perform today may sound like a worst-case scenario. But, in actuality, this future will bring about a new era of creativity and innovation.

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Note that this is so potentially powerful because it's such a starkly different approach from the historical experiments that led us to this point. In the past, researchers basically worked in the opposite direction: some observable characteristic of the cell is tracked to the protein causing the observation, to the gene encoding the protein, to the specific pattern of activity that allows that gene to have that effect. In this case, researchers observe the activity patterns without context, then brute-analyze them to find other genes, with known effects. This allows them to work forwards toward practical effects on the cell, rather than backward from them.

There has been an upsurge in machine learning methods in recent years. Growing evidence suggests that machine learning is what a lot of people do with the big data they have accumulated. Like any complex undertaking, it is worthwhile to break it down into component parts. That is the objective of this episode of the Talking Data podcast, in which TechTarget reporters Jack Vaughan and Ed Burns discuss the evolution of machine learning through the lens of technologies employed and end-use applications. Among use cases cited are risk estimation in insurance, credit scoring and digital ad placement.

VC Chris Dixon of Andreessen Horowitz thinks it's a lot harder to predict financial cycles than it is to see a new computing platform coming down the pike. As he noted in a recent post, new cycles tend to begin every 10 to 15 years; assuming the 2007 introduction of the iPhone kicked off the last wave, we're fast heading toward the Next New Thing. Or things, technically, according to Dixon, who we caught up with yesterday. Among the trends that Dixon is watching closely, he says, are virtual reality, augmented reality, IoT, wearables, drones and cars. Not that it'll be easy to make money off these newer technologies. In fact, Dixon suggests it could be ridiculously challenging, given how quickly Facebook, Google, and Amazon are bringing aboard related talent.

When Hollywood actress Angelina Jolie found out she carried a faulty variant of the BRCA1 gene, her doctors told her she had an 87% chance of developing breast cancer. Armed with this knowledge, she chose to undergo a double mastectomy in 2013 to reduce the risk to around 5%. This kind of genetic testing can now be done much faster and at lower cost, giving clinicians the ability to target treatments more effectively. And combining this technological breakthrough with cloud computing and artificial intelligence is giving pharmaceutical companies the tools to develop drugs faster and with greater chance of success. One beneficiary of this new approach is Eric Dishman, founder of tech giant Intel's first health research and innovation laboratory in 1999 and a founding member of its digital health group in 2005.

In recent years, we've become used to the fact that retail PCs are cheaper, more functional, lighter and better looking than the ones most organisations provide for work. Many of us find it more productive to work at home or in a coffee shop, or anywhere there is Wi-Fi. Consumer email, instant messaging, file sharing and other free services are often demonstrably more capable and easier to use than the services that most large organisations provide. As long ago as April 2004, the Leading Edge Forum (LEF) coined the term consumerisation, and published a report on The Consumerization of Information Technology. The paper was our response to the intriguing developments popping up all around us.

Over the course of five seasons, Game of Thrones has killed off over 61 characters, including fan favorites such as Ned Stark, Oberyn Martell and (supposedly) Jon Snow. Now, a computer science class at Germany's Technical University of Munich has created a website dubbed "A Song of Ice and Data" to determine the fate of the HBO drama's remaining key players in the upcoming sixth season. Using a series of machine learning algorithms, the students have figured out the likelihood of each character meeting their end in the next 10 episodes. According to the site, Tommen Baratheon has the worst odds of survival--with a 97 percent chance of death--while Sansa Stark is the most likely to make it to next year at 3 percent. The group also applied the formula to both the show's previous seasons and George R.R. Martin's A Song of Ice and Fire series, and found it accurately predicted 74 percent of deaths.