Imagine a future where the CEO of a manufacturing firm turns to his Chief Innovation Officer and asks: "Bob, how can we innovate on our product and save 10 per cent of production cost to stay competitive against low-cost firms?" So far this seems to be a normal conversation that occurs daily across organisations around the world. Except that'Bob' is really an AI computer program on the CEO's iPhone. A study from Oxford University says that A.I. will replace up to 45 per cent of jobs within 20 years. There is a lot of talk about how such intelligent systems and chatbots will eliminate low level jobs, customer service and repetitive tasks.

A North-East fintech company is using artificial intelligence (AI) and speech recognition software to allow users to discuss their financial accounts with their phone. Darlington-based MyFirmsApp creates custom app platforms for accountants and has recently secured the right to use next generation AI platform, Amazon Lex. The software will allow the company to build apps with'human-like intelligence' that can see, hear, speak, understand and interact with the world around them. The new tech will allow accountants and their customers to have a conversational experience when using their app. CEO Joel Oliver believes that being able to create chat bots using Amazon Lex will help accountants carry out simple tasks and allow them to become more productive.

Juniper defined six specific categories of consumer robotics. Based on the amount of venture capital investments, autonomous vehicles lead the way, followed by social.

Google doesn't do a lot of paid advertising, so when it does we've got a good clue that Google management is really committed to the product or service, at least for now (remember Google?). Google is currently running a "Talk to Google" campaign on TV and Radio in multiple European countries to promote voice driven searches using their "mobile" search app. I've heard a similar "Spricht mit Google" ad on Berlin's Radio Eins.

For people who play the video game Counter Strike online, it's hard enough watching your back at the best of times. In the fast-paced first-person shooter, there are always players with quicker reflexes or a sharper eye. But at the height of its popularity a few years ago, people started to come up against other players with skills that were too good to be true. Games like Counter Strike and Half Life – another shooter that was very popular online – had a problem with players who used software cheats that steadied their aim or let them see through walls. So in 2006, when the stakes were raised by an online competition with cash prizes, an unusual pair of referees were called in.

We study an online multi-task learning setting, in which instances of related tasks arrive sequentially, and are handled by task-specific online learners. We consider an algorithmic framework to model the relationship of these tasks via a set of convex constraints. To exploit this relationship, we design a novel algorithm -- COOL -- for coordinating the individual online learners: Our key idea is to coordinate their parameters via weighted projections onto a convex set. By adjusting the rate and accuracy of the projection, the COOL algorithm allows for a trade-off between the benefit of coordination and the required computation/communication. We derive regret bounds for our approach and analyze how they are influenced by these trade-off factors. We apply our results on the application of learning users' preferences on the Airbnb marketplace with the goal of incentivizing users to explore under-reviewed apartments.

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.

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

February 8, 2017 --Someday soon, you will ask a robot to fetch a slice of pizza from your refrigerator. On that day, you'll trust that the robot won't tear through your walls and rip the fridge door off its hinges to get at your leftovers. Getting robots to do the things humans do in the ways that humans do them (or better) without human intervention is an immensely wicked problem of autonomy. With as many as half of American jobs at risk of automation according to one study, and with an expected 10 million self driving cars on the road by 2020, robots are going to be everywhere, forever, and they won't go away. The enormous scope and scale of how autonomous robots will begin changing our lives requires the public and technologists alike to consider the challenges of autonomy.

Sophos (LSE: SOPH), a global leader in network and endpoint security, today announced it has entered into an agreement to acquire Invincea, a visionary provider of next-generation malware protection. Invincea's endpoint security portfolio is designed to detect and prevent unknown malware and sophisticated attacks via its patented deep learning neural-network algorithms. It has been consistently ranked as among the best performing machine learning, signature-less next-generation endpoint technologies in third-party testing and rated highly both for high detection and low false-positive rates. Headquartered in Fairfax, Va., Invincea was founded by chief executive officer Anup Ghosh to address the rapidly growing zero-day security threat from nation states, cyber criminals and rogue actors. Invincea's flagship product X by Invincea uses deep learning neural networks and behavioral monitoring to detect previously unseen malware and stops attacks before damage occurs.