Those amazing, lifelike robots, reports Jefferson Graham on #TalkingTech. LAS VEGAS --The one, coolest thing from this year's 2017 CES is an easy pick -- those amazing robots. We saw robots to make your morning coffee, pour candy, fold your clothes, turn on and off your lights, project a movie on the wall, handle your daily chores and most impressively, look just like a human, or in this case, legendary scientist Albert Einstein, with facial expressions and movement. Why did robots dominate CES? You can thank the popularity of Amazon's Echo device for showcasing the technology of a voice-activated personal assistant.

Machine Learning can sound very complicated, but anyone with a will to learn can successfully apply it, if they approach it from first principles. This course, Classification Using Tree Based Models, covers a specific class of Machine Learning problems - classification problems and how to solve these problems using Tree based models. First, you'll learn about building and visualizing decision trees as well as recognizing the serious problem of overfitting and its causes. Next, you'll learn about using ensemble learning to overcome overfitting. Finally, you'll explore 2 specific ensemble learning techniques - Random Forests and Gradient boosted trees By the end of this course, you'll be able to recognize opportunities where you can use Tree based models to solve classification problems and measure how well your solution is doing.

Text mining predictive methods help organizations enhance the value of unstructured information by deploying insight from text analysis in software applications and business processes. Once textual information is transformed into a set of structured data using text mining (or text analytics) it can be combined with traditional data mining algorithms to generate new insight for sentiment analysis and predictive analytics. Whether it is marketing and competitive intelligence, customer relationship management, social media monitoring, operational risk mitigation or threat discovery, big data is a key element for understanding where you are and where you're going. Text mining predictive methods support organizations in staying competitive. It helps them improve the ability to quickly react to customer feedback, market changes, competitive landscape evolutions, etc. This is precisely why enterprises should embed text analytics and predictive analytics into their business processes.

Though we've always assumed certain crafts will forever remain immune to automation, it seems nowadays nobody is safe from the looming artificial intelligence invasion. While a few years back the prospect of robots snatching jobs from humans might have seemed like a hackneyed plot twist from a cheap science fiction flick, this scenario actually turned into reality for the staff of Japanese insurance firm Fukoku Mutual Life. The BBC reports the company has made an executive decision to lay off more than 30 employees and replace them with an artificial intelligence system that can calculate insurance payouts. With this move, Fukoku Mutual estimates it will increase productivity by an impressive 30 percent. To give you some more context, the firm additionally expects to save approximately in $1.2 million (or 140 million yen) in expenses by swapping out its human workers with AI.

The beginning of the new year is a good time to reflect on the events of 2016 and on their forebodings for the coming year and beyond.There has no doubt been a great deal of buzz around artificial intelligence (AI) this year. However, it's difficult to sort through what's hype and what's not to determine where these technologies will actually take us in 2017. While we know the trend will continue in some form, what will be new or different next year? Artificial Intelligence is taking the industry by storm, and not just in "Westworld." This has opened the door to solve computational problems on a scale that no human mind could approach – even in a lifetime. The result is that computers are now able to provide responses that aren't dictated by a collection of "if A, then B" rules, offering results that can only be explained by saying that the computer "understands."

At this year's Consumer Electronics Show (CES), dozens of companies selling all kinds of products and services are touting their use of Artificial Intelligence (AI). AI has been hot for a year or two, and it's only getting hotter as it becomes incorporated into increasingly novel products and services. Jetsons-style robot assistants for the home were on display on the show floor, boasting intelligence that helps discover and adapt to the layout of your home, identify your family's habits, recognize faces, learn from conversations, and even control smart-home devices. LG was the biggest name with a new robot, but smaller companies also unveiled compelling options, including Mayfield Robotics' ultra-cute Kuri and Yumii's Cutii companion for the elderly. AI-powered robots that used to be the province of science fiction may soon be common in our homes.

To remain competitive this year and beyond, they'll need to embrace many new realities. Already, retailers are growing more skilled at providing the right customer with the right message -- and offers -- at the right time to generate the best results across sales and distribution channels. Both stores and online shops are growing more empowered with data and a more personalized understanding of customers, gaining better understanding of customer preferences, and better leveraging tools and technologies to become truly customer-centric organizations. And yet, there are still obstacles to address and new paradigms to understand, as these five retail and ecommerce experts attest. "Digitalization is massively changing all businesses in 2017. Retailers, both B2B and B2C, will have to deal with changes in the way their customers buy, communicate and search for information about products. "When organizations think about digitalization, they consider their marketing and sales processes, develop roles, analyze user journeys and optimize web sites.

Over the past decade, B2B marketing has undergone a massive transformation. According to Forrester Research, the entire B2B sector represents more than $1 trillion in digital commerce every year, more than double the size of the B2C economy. Is artificial intelligence the rocket fuel to take us through the next decade of marketing technology? AI is not about inventing a new task or a new way of being intelligent, but simply mimicking human intelligence. Given that it's a machine doing the work, AI can be done at infinite scale since it can read and process billions of data points with perfect memory.

Recent progress in robotics and artificial intelligence has blurred the line between man and machine. After more than 50 years of research, artificial intelligence (AI) systems haven't quite matched their biological analogues, but they're catching up: Uber's self-driving truck drove 2,000 cases of beer over 120 miles, Google knows almost exactly what we're searching for before we've typed it out in full; and many of us speak naturally to assistants waiting in our pockets or our kitchens. This is only the beginning. As technology improves, our worldview must evolve to keep pace. It's time to start talking seriously about ethics in AI.

It looks like the job automation trend is getting to Japan, bringing the country a step closer to a future of layoffs in favor of intelligent machines. Japanese firm Fukoku Mutual Life Insurance Co. is laying off more than 30 of its employees and is replacing them with artificial intelligence (AI) systems that will perform payout calculations for policyholders. For Fukoku Mutual, the move is seen as a practical and beneficial, with expected increase in productivity at 30 percent and a calculated return on investment in less than two years."The "Meanwhile, it's expected that Fukoku Mutual will save about 140 million yen per year by cutting the 34 staff." Understandably, the 34 employees whose jobs are set to be eliminated by March 2017 aren't going to be so happy.