Working in the field of big data and AI means that I see the leading edge advances that come with it. It also means routinely getting freaked out when you think too closely about the possibilities and implications of those advances and where they might be taking us. Robots and AIs Will Take Our Jobs This isn't just science fiction, it's happening now. Manufacturing are the first places we see robots and automation eliminating human jobs, but it's hard to think of an industry that will be left unaffected as robots and AI become more affordable and widespread. It's estimated that between 35 and 50 percent of jobs that exist today are at risk of being lost to automation.

Millions of jobs could be lost to robots and automation by the year 2020 as part of the so-called "fourth industrial revolution," according to a World Economic Forum report from January. Jobs such as manufacturing and production are expected to be affected by the rise of the machines, while a whole new line of jobs will also be created, including I.T. and data analysis. However, the net loss is expected to be around five million jobs within the next three years. There may be a smidgen of hyperbole in that statement, but you only have to look at some of the developments of the past twelve months to realize that robots are here to stay and they will start adversely affecting employment. Here, we take a look back at some of the landmark moments and trends from across the robot realm in 2016.

How do you register your child for primary school? Somewhere, in the millions of pages of your local government website, there are instructions, but how do you find them? She's a "chatbot," a conversational application written by Singapore's government to help citizens navigate its many sites. Jamie's smart, too: Even though our intrepid user (me) was browsing a government tech site, Jamie knew the question was better answered by the Ministry of Education. Jamie's an example of how new conversational interfaces, backed by huge cloud-based knowledge bases and inferencing, promise to change forever how we relate to computers.

Google's AlphaGo beats Lee Sedol at the game of Go In 2016, major automakers like Tesla and Ford announced timelines for releasing fully-autonomous vehicles. DeepMind's AlphaGo, Google's AI system, beat the world champ Lee Sedol at one of the most complex board games in history. And other major advancements in AI have had big implications in healthcare, with some systems proving more effective in detecting cancer than human doctors. Want to learn what other cool things AI did in 2016? Here are TechRepublic's top picks.

California's DMV cracked down on the company's testing program Discovered the vehicles did not have the correct permits for the autonomous vehicles to be operated on the streets Uber maintains it does not need a permit because the cars are not sophisticated enough to continuously drive themselves California's DMV cracked down on the company's testing program Uber's self-driving program was up and running in San Francisco for just a week, and all the while the company was embroiled in a dispute with the state DMV and attorney general. Uber now lets you set a friend as your destination - and... Don't have sex with your driver, smoke or ask overly... Philadelphia woman is charged $28,639 for an Uber ride... Uber now lets you set a friend as your destination - and... Don't have sex with your driver, smoke or ask overly... Philadelphia woman is charged $28,639 for an Uber ride... The regulator demanded the firm get a permit to test its self-driving cars on public roads - but Uber didn't believe they needed one as their cars are not yet able to fully drive on their own. Uber Technologies Inc. has removed its self-driving cars from San Francisco streets after California regulators cracked down on the program because the company had not obtained a permit to test autonomous vehicles. The California Department of Motor Vehicles said on Wednesday it revoked the registration of 16 Uber self-driving cars after a weeklong battle with the ride-services company.

IMAGE: This is the Architecture of the Adversarial Autoencoder (AAE). The study was published in Oncotarget on 22nd of December, 2016. The study represents the proof of concept for applying Generative Adversarial Networks (GANs) to drug discovery. The authors significantly extended this model to generate new leads according to multiple requested characteristics and plan to launch a comprehensive GAN-based drug discovery engine producing promising therapeutic treatments to significantly accelerate pharmaceutical R&D and improve the success rates in clinical trials. Since 2010 deep learning systems demonstrated unprecedented results in image, voice and text recognition, in many cases surpassing human accuracy and enabling autonomous driving, automated creation of pleasant art and even composition of pleasant music.

Uber takes its self driving cars to Arizona: Firm abandons... How a long SONG can make you late: Researchers find... Pokemon Go's last gasp? Apple Watch version of hit game... Pandora up close: Nasa releases stunning image from... Uber takes its self driving cars to Arizona: Firm abandons... How a long SONG can make you late: Researchers find... Pokemon Go's last gasp? Apple Watch version of hit game... Pandora up close: Nasa releases stunning image from... The world of Hyrule has come a long way since The Legend of Zelda was first released 30 years ago. Nintendo has revealed a series of sketches from the development of the original game, and they're sure to get the nostalgia flowing Along with the individual illustrations, Nintendo also released a video showing a look at a sketch of the entire map from the iconic game to celebrate its 30th anniversary this year.

More cities are adding smart city features so that Internet of Things (IoT) sensors and other connected technologies can improve the lives of citizens and visitors. As everyone knows, technology moves fast and finding out what's in store next is crucial to stay in the game. Diabetics have been waiting for years for better technology to manage their condition. Some got tired of waiting and hacked together an open source hardware and software solution. The concept of a smart city has been around for more than a decade, but it was only recently that the phrase "smart city" became part of the modern lexicon.

Two cucumber farmers in Japan have received an unusual boost to their business after their son adapted Google's powerful artificial intelligence software to carry out the arduous task of sorting vegetables. Makoto Koike returned to his parent's cucumber farm in 2015 after working as a computer systems designer in the automobile industry. While helping out on the farm, Koike realized that one of the most time-consuming processes could be overcome through automation. Taking inspiration from Google's powerful artificial intelligence computer program AlphaGo, Koike set about designing a sorting system using a $35 Raspberry Pi 3 computer and Google's open source deep-learning platform TensorFlow. "Each cucumber has different color, shape, quality and freshness," Koike said.

The historic match demonstrated the growing power of artificial intelligence and helped connect the ancient game with a mainstream audience. Go is loved and studied by computer scientists, business leaders, and politicians because the game balances elegance with complexity. Diabetics have been waiting for years for better technology to manage their condition. Some got tired of waiting and hacked together an open source hardware and software solution. Much of Go's appeal is in the game's' ability to provoke thought that inspires and guides action outside the game.