The annual exercise of looking forward to all the exciting innovations the next year can reasonably be expected to bring is here once again. Last year at Telegraph tech we predicted 2016 would witness the rise of mobile payments, the creation of smart cities that can think and function autonomously, and the premiere of virtual reality in people's living rooms. Trials have proven artificial intelligence to be effective in suggesting treatments by analysing patients' genomes This year we've expanded our horizons somewhat to include moonshot projects, the social ramifications of technology and one disaster scenario. Here are our predictions of the technology events to come in 2017. Self-driving vehicles have arrived more swiftly than anybody thought: Google and Apple have been experimenting with the technology for years, the Autopilot mode on Tesla cars has clocked up over 200 million miles, and every carmaker is scrambling to get self-driving software into their vehicles.

Security is the gift that keeps on giving. There's always one more vulnerability to be exploited, one more household-name company that's about to be breached. So, it shouldn't be surprising that 2016 offered up some new lessons -- or, in some cases, things the industry already knew but needed a reminder about. It isn't exactly the rise of the robots, but the Mirai botnet proved that the Internet of Things (IoT) is easily exploitable. This is a possibility that's been lurking all along, but in 2016, it became real.

David Eden from Tata Communications asks what technologies will shape the way people live, work and experience the world around us in 2017 and beyond. The article will also examine what barriers are standing in the way of some of most exciting and talked-about innovations today. While the hype might suggest otherwise, virtual reality (VR) won't become mainstream in 2017. However, its industrialisation will start to gather momentum. VR has already been used as a training tool in medicine, and next year there will be more innovative VR-enabled medical applications.

Bumping a prospect's talk-time from 22% to 33% delivers a sharp increase in win-rates If pricing comes up 3–4x in a call, consider it a buying signal Top sales professionals typically discuss pricing late in the call (40–49 minutes in on average) When your prospect responds to your timeline question with the word "probably," consider it a good thing When prospects respond to your timeline question with the phrase "We need to figure out X," you've got your work cut out for you When you sooth your prospect's fears with risk-reversal language (such as "you can cancel at any time"), win-rates on average increase 32% Conversation-level sales coaching leads to higher win-rates, more revenue, and shorter sales cycles Bumping a prospect's talk-time from 22% to 33% delivers a sharp increase in win-rates

For the 100-year-plus history of the automobile, cars have generated plenty of emotions. But those feelings have occurred in humans. Honda is looking to change that dynamic, and is ready to showcase how at the Consumer Electronics Show in Las Vegas next month. It's called the "NeuV," and according to Honda it's "a concept automated EV commuter vehicle equipped with artificial intelligence (AI) called'emotion engine' that creates new possibilities for human interaction and new value for customers." "Harnessing the power of artificial intelligence, robotics, and big data to transform the mobility experience, Honda today announced that'Cooperative Mobility Ecosystem' will be the theme for its participation at the 2017 [CES]," the automaker said in a statement.

In some ways, tech in 2017 will be a steady progression from what came before it. Time marches on, and so too does the advance of technology. In other ways, though, it will be just as upended as the rest of the world by the unprecedented disruption that 2016 has left in its wake. The artificial intelligence revolution is well and truly upon us, but so far, the biggest players are venerable Silicon Valley titans such as Google, Amazon and Apple. That's partially because they have the money to hire teams full of PhDs at seven-figure salaries, but it's also because they have the data.

Scientists and engineers normally create AI that can learn via deep learning, and training them usually takes up weeks. However, it seems Microsoft and scientists from the Swiss National Computing Centre have taken this one step further and trained AI via deep learning within minutes! This is an astonishing feat in the realm of robotics and artificial intelligence, one that could easily generate results within hours or minutes. This, coupled with the introduction of supercomputing technology, customers will now have the ability to solve problems such as image, video and speech recognition, as well as natural language processing. This can enable future researchers to be able to make technologies that could only previously been seen in science fiction.

Hearing that Bob Dylan just won the Nobel Prize for Literature, how could I not begin this talk with his famous line, "Something is happening here, but you don't know what it is, do you, Mr. Jones?" The future is full of amazing things. On my way here, I spoke out loud to a $200 device in my kitchen, and asked it to call a Lyft to take me to the airport. And in a few years, that car might well be driving itself. Someone seeing this for the first time would have every excuse to say "WTF?"

Subscribe to the O'Reilly Data Show Podcast to explore the opportunities and techniques driving big data, data science, and AI. Find us on Stitcher, TuneIn, iTunes, SoundCloud, RSS. In this episode I spoke with Ion Stoica, cofounder and chairman of Databricks. Stoica is also a professor of computer science at UC Berkeley, where he serves as director of the new RISE Lab (the successor to AMPLab). Fresh off the incredible success of AMPLab, RISE seeks to build tools and platforms that enable sophisticated real-time applications on live data, while maintaining strong security.

Data driven recruitment has a significant, positive impact on talent management strategies and business performance. As technology becomes more sophisticated, AI is playing an increasingly essential role in decisions made around hiring and is used by brands such as Facebook as an integral part of the screening and assessment of candidates. This article examines its ongoing effect on the jobs market and the ways in which HR can harness its advantages to better understand, improve and predict hiring needs and potential problems. AI is broadly defined as'machines which perform tasks which humans are capable of performing'. It has been traditionally been regarded as a threat to jobs, with the most drastic predictions suggesting that unemployment rates will reach 50% within 30 years, but perceptions and predictions are changing.