IBM on Wednesday announced it was teaming with General Motors to put Watson artificial intelligence to work to personalize the driving experience for motorists. OnStar software built into GM cars will be imbued with Watson smarts, enabling them to get to know their drivers, IBM chief executive Ginni Rometty told the WSJD Live technology conference in California. "It learns from how you behave and what you do," Rometty said. "It knows how you like your coffee and orders it for you; it reminds you to pick up your children." The resulting OnStar Go system will be the auto industry's first "cognitive mobility platform," according to the companies.

It has been less than two weeks since a White House report warned that automation has the potential to disrupt millions of jobs, and this week a Japanese insurance firm proved how close that future might be. According to Japanese news publication Mainichi Shinbun (via Quartz), Fukoku Mutual Life Insurance Co. will be replacing roughly 30 percent of the employees in its payment assessment department with an artificial intelligence system powered by IBM Watson. Fukoku Mutual plans to lay off 34 employees by the end of March, and the company will not renew contracts for an additional 13 employees once they expire. The new AI will determine how much insurance should be paid out for each claim based on a number of factors, including the insured's medical history, the procedures they have undergone, the doctor's diagnosis and so on. According to Mainichi Shinbun, the types of cases the AI would handled totaled around 132,000 in 2015.

Snapchat debuted its camera-equipped Spectacles this fall. Snapchat is adding ways to optimize campaign performance with the help of machine learning. Earlier this month, Snap Inc. began rolling out what it calls Goal-Based Bidding (GBB). The option, available to marketers buying ads through Snapchat's API, uses machine learning to know which users are most likely to swipe a certain type of ad. Here's how it works: With goal-based bidding, advertisers can inform Snapchat of when their main goal is increasing swipe-ups--perhaps for app installs, web views or movie trailers--instead of focusing solely on impressions.

The age of artificial intelligence (AI) is upon us. In the past few years, vast improvements have been made in how well computers can recognise objects in images and understand human voices. Progress in these areas has been made due to increased computing power and the availability of large stores of data, which, when combined, have made AI systems dramatically more effective. These same forces are also being used in marketing. AI, or'cognitive', marketing systems use industrial computing power, big data, and machine learning to improve marketing performance.

As someone who will become a future Software Engineer (Embedded / Cyber Security / AI most likely), my concern is this: lets say we increase the wages of undesirable jobs so as to compensate, then how do we handle other types of jobs? Certainly, one could argue my profession will have more'relevance' in this robotically automated world, so from my stand point it would seem unfair that wages increase for, say, the grass-cutter or dishwasher, while my job stays where its at. I suppose one could argue that "all jobs are equally important" but this simply isn't how our world works. Engineers make more money than teachers because we build the things that private / government entities need, and teachers make more money than grass-cutters because the future generations need to learn. The follow-up concern with this is that we're right back where we started in a sense: we have a hierarchical system of what is and is not important.

Agriculture is the industry that accompanied the evolution of humanity from pre-historic times to modern days and fulfilled faithfully one of its most basic needs: food supply. Today this still remains its core mission, but it's integrated in a more complex than ever mechanism driven by multiple sociological, economic and environmental forces. This $5 trillion industry representing 10 percent of global consumer spending, 40 percent of employment and 30 percent of greenhouse gas emissions continues to keep pace with world's evolution, changing tremendously over the past years. Digital and technological advancements are taking over the industry, enhancing food production while adding value to the entire farm-to-fork supply chain and helping it make use of natural resources more efficiently. Data generated by sensors or agricultural drones collected at farms, on the field or during transportation offer a wealth of information about soil, seeds, livestock, crops, costs, farm equipment or the use of water and fertilizer.

Today's consumers seek brands that create seamless experiences that feel less automated and more human, less generic and more personal, and less about the brand and more about them. With IBM Watson, Invoca is helping marketers across industries live up to and exceed these consumer expectations. By transforming phone conversations into a source of actionable data, Invoca is using IBM Watson to provide marketers the insights they need to deliver more personalized customer experiences. According to an IBM survey of over 700 CMOs, one of the top four priorities this year is to "inject data-driven insights into every marketing decision." When effectively applied to the customer experience, data has the potential to improve the customer experience, and this applies well beyond workflow automation and customer service bots – it applies to every single customer interaction.

Hi Mimi Yes, but I'm very concerned about the usage of private AI-blackbox as IBM Watson, in medicine, healthcare and any analytics and decisions regarding people-privacy/private citizens life. Generally speaking there is a huge concern, now underrated, about incoming pervasive presence of artificial intelligence systems in our societies (IBM is along with Google, Amazon and few others big players). Specifically, the problem I see with IBM Watson is that it is a closed product of a private company. There is nothing bad in a pure commercial product approach, but problems arise if this product become spread in public domains, public services (universities, hospitals, etc.). Technically speaking, is not clear to me (and some scientists I interviewed) Watson inside algorithms/mechanics, because it's fully closed; I call this AI-blackbox.

A large radiology practice in the Miami area is the test bed for the first real-world application of IBM Watson interpreting medical images. Radiology Associates of South Florida, which has more than 75 physicians and handles about 1 million studies per year, is teaming with Baptist Hospital of Miami to apply Watson-powered "cognitive peer review" to medical imaging in an effort to diagnose aortic stenosis earlier. "We want to identify patients at high risk who may have been missed," said Dr. Ricardo Cury, director of cardiac imaging at Baptist Hospital of Miami and chairman and CEO of Radiology Associates. Watson speeds up the peer review process by assisting cardiologists and sonographers in spotting stenosis cases that otherwise might fall through the cracks, Cury explained at the annual meeting of the Radiological Society of North America in Chicago late last month. Watson looks for variations in practice, based on quality metrics and image analytics, explained Jon DeVries, global offering manager for IBM Watson Health Imaging.

At the end of June and beginning of July, I attended Viva Tech's international summit in Paris. Although the event was centred around Fintech and Insurtech, there were humanoid robots, flying drones, VR play stations… One could learn about the latest trends in retail and hospitality, media and medical industries, smart cities… But, the key idea of the organisers was to physically bring together top companies, investors and startups to boost innovation. There was a series of open innovation challenges designed to hack strategic business problems… In one word, a paradise for a guy like me! I learned a lot, met so many interesting people and interviewed some. One of them was David Kenny, General Manager of IBM Watson tasked to build Watson into "artificial intelligence as a service".