Qubit is a start-up which helps online retailers collect, analyse and act on data about the way their customers behave. We're looking for a Data Scientist to join our Research team, to help us develop intelligent products around this data, and conduct cutting-edge research into consumer behaviour on the web. This is a great opportunity to conduct real R&D around human behaviour. Our data collection tools store more than 1 billion data points every day. Overall, Qubit technology tracks consumer journeys leading to billions of pounds of online spending worldwide every year, for some of the largest names in online retail.

Amazon's virtual assistant was already hard at work helping with tasks via its Echo speakers and Fire TV, but now Alexa is getting more control of your television. The online retailer announced today that Alexa can handle more requests on its streaming gadgets, including launching apps, playing selections from Amazon video and add-on subscriptions (HBO Go, Starz, Showtime, SeeSo) and browsing local movie times. Fire TV already offered voice search and Alexa has been available on those devices as well, but this update expands the virtual assistant's workload.

Machine-learning is all the rage in fraud detection, with industry analysts, academics, businesses and technology media examining the advantages of algorithms and big data in the fight against e-commerce fraud. Especially for fraud analysts working in companies with small budgets, machine-learning tools are seen as a cost-effective way to tighten fraud controls while maintaining fast decision times, as Forrester noted in its 2015 cross-channel fraud report. There's no question that machine-learning tools can be an effective component of fraud reduction program, but relying on them to save staffing costs may not be cost-effective in the long run. That's because while machine learning is an invaluable tool in the fight against fraud, it relies on human input and insight to create a comprehensive solution that yields the best results. Algorithms are useful for identifying potential fraud quickly, but due to variability in consumer behavior – such as making online purchases while traveling abroad -- some transactions will be falsely flagged for decline.

Chinese online retailer JD.com has teamed up with robot maker Siasun to automate its logistic network, the company said on Friday. JD said it will work with Siasun to develop logistics robots to increase automation from order to delivery. JD has already invested heavily in making its warehouses and deliveries more efficient. "Logistics in the future will go beyond basic infrastructure," said JD's technology chief Zhang Chen, "Technology ranging from the Internet of Things, cloud computing, big data to artificial intelligence are making our service smarter." JD said it will work with other companies on automation similar to that at Amazon's distribution centers.

Thanks to machine learning, the page you see when you log-on to Amazon.com is likely very different from the one I see. Advertising, product recommendations, and special deals are all tailored to our unique customer profiles based on historical browsing trends and buying behavior. Online retailers like Amazon were among the first users of customer data collection and analysis for improving services and personalizing the shopping experience, and they've become so skilled some sites might even be able to predict what we will purchase before we even know what we're looking for. Advancements in digital technologies have driven a paradigm shift in the way businesses interact with their customers, with touchpoints increasingly moving to digital mediums. Because of the limited opportunities to satisfy customers on a person-to-person level, machine learning is now in widespread use by a variety of modern enterprises as a way to enrich customer experiences, create more personalized and customer-centric interactions, and offer seamless omnichannel communications. Machine learning goes a step beyond Big Data analytics, where machines employ advanced algorithms to autonomously adapt and learn from previous experiences, and therefore emulate the thought process behind human decision-making.

JD.com founder and CEO Richard Liu attends a launching ceremony of the "U.S. Mall" of JD.com in New York, the United States, July 20, 2015. BEIJING, May 15 (Xinhua) -- Chinese online retailer JD.com has teamed up with robot maker Siasun to automate its logistic network, the company said on Friday. JD said it will work with Siasun to develop logistics robots to increase automation from order to delivery. JD has already invested heavily in making its warehouses and deliveries more efficient. "Logistics in the future will go beyond basic infrastructure," said JD's technology chief Zhang Chen, "Technology ranging from the Internet of Things, cloud computing, big data to artificial intelligence are making our service smarter."

So how could scalable retail artificial intelligence in the cloud – Brand AI – potentially turn these challenges into unique opportunities for competitive advantage during the next five years? But unlike today's arguably bland, soulless smartphone versions that focus on delivering simple functionality, Brand AI would have a unique, human character that reflects the retailer's values to inform its interactions and maturing relationship with an individual customer. Intended to be more than another'digital novelty', this disruptive form of customer engagement builds on and enhances a B&M's traditional brand as a trusted long-term friend throughout the entire customer journey by offering compelling, timely presale insights, instant payment processing and effective after sales support and care. A customer is empowered to select what personal data they choose to share (or keep private) with the Brand AI to enrich their relationship. Social, location, wearable or browsing and buying behaviour data from complementary or even competing retailers could, potentially, be shared via its cloud platform.

Technology is the future of retail. Digital data, machine learning, cloud-powered analytics and the Internet of Things (IoT) will separate the wheat from the chaff in tomorrow's retail industry.

For all of Amazon's grand plans regarding delivery drones, it still needs to figure out concepts we take for granted with traditional courier methods. Namely, figuring out how to drop off your latest order without destroying anything (including the UAV itself) during transit and landing. That's where advanced computer vision comes in from Jeff Bezos' new team of Austria-based engineers, according to The Verge. The group invented methods for reconstructing geometry from images and contextually recognizing environmental objects, giving the drones the ability to differentiate between, say, a swimming pool and your back patio. Both are flat surfaces, but one won't leave your PlayStation VR headset waterlogged after drop-off.

CEO and co-founder of Viv Dag Kittlaus speaks onstage during TechCrunch Disrupt NY 2016 at Brooklyn Cruise Terminal on May 9, 2016 in New York City. Apple's Siri co-creators, Dag Kittlaus and Adam Cheyer, introduced their newly designed virtual assistant AI Viv, dubbed "The Global Brain." Kittlaus and Cheyer's latest venture in artificial intelligence research proved a rewarding call as AI Viv impressed the public. AI Viv goes beyond Siri's boundaries and performs various tasks that involve third-party exchange and transactions. While Apple's virtual assistant provided reliable in referencing information from the world wide web, users hoped to eventually see more.