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. Get the low-down on the latest and most insane tech being showcased in Las Vegas. 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.

Clara Lu is the marketing manager at ViSenze, an artificial intelligence company that makes search by images possible without keywords. With so many articles proliferating the media space on how humans are at the cusp of full AI (artificial intelligence), it's no wonder that we believe that the future -- which is full of robots and drones and self-driven vehicles, as well as diminishing human control over these machines -- is right on our doorstep. But are we really approaching the singularity as fast as we think we are? It's not hard to have that impression with the likes of Elon Musk, Stephen Hawking, leading university departments and research centers around the world and more being highly concerned with the potential risks brought about by AI and taking action now to avoid a doomsday scenario in the near future. They predict that by the year 2030 machines will develop consciousness through the application of human intelligence. In fact, Dr. Hawking told the BBC, "The development of full artificial intelligence could spell the end of the human race."

For more on the future of AI and design, check out Mike Haley's session, The future will see you now: Machine learning transforms design, at the O'Reilly Design Conference, March 19-22, 2017, in San Francisco. Artefact's co-founder, Rob Girling, explores the impact of artificial intelligence on design in this three-part series of articles. His first piece, Will machines take your job?, outlines the unprecedented changes AI and automation will bring to jobs in general. In the second installment, What skills do we need to compete against the machines, he outlines criteria that will make some professions more vulnerable to AI automation. For anyone doubting that AI is here, the New York Times recently reported that Carnegie Mellon University plans to create a research center that focuses on the ethics of artificial intelligence.

As human-like machines begin to perform more advanced tasks, we fear that they will replace us, take our jobs even. But the truth is, machines are making our lives easier and allowing us to focus more on what humans do best, such as making subjective decisions and using our emotional intelligence. Robots and machines, in effect, remove the clutter that often causes our productivity to wane and our attention to waver. Rather than fear technology, we should embrace it because it takes care of repetitive--and often mundane--tasks like data collection and processing. In the workplace, machine learning has the capacity to change how managers spot an employee's talent, how employees share their knowledge and how employers decide whom to promote.

We're barely into the new year, which means it's time for the planet (or the developed world, at least) to get its collective geek on and marvel at the latest electronics at CES. If you've been living in a cave for the past decade or so, CES is the Consumer Electronics Show. It's where newfangled gadgets debut, TV manufacturers try to convince us all that we need to upgrade from our hi-def sets, and techno-hucksters attempt to convince us, yet again, that virtual reality and smartwatches have truly, finally arrived, for real this time. Well, only the cutest little robot you ever did see! His name is Kuri, and you can find him on heykuri.com.

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."