Google and other tech companies have been building artificial intelligence for some time and recently Google Deep Mind research teams believe they have developed the first version of a General Artificial Intelligence that is capable of learning on its own without assistance in different situations. The term'general' in this case means that the AI can adapt to learning different situations and problems without additional training. In Google's case, the team used an algorithm and sensors to detect play on the game board of the ancient game Go. In the game of Go, black and white stones are placed successively on a grid. When you surround another players stones, you take the stones as prisoners.

Artificial Intelligence proved to be a very unstable field, its 60 year history is a chain of periods filled with excitement and anticipation of the singularity, taking turns with times of total ignorance known as AI winters, when donors lose hope in replacing people by machines, when the general public is satiated with chat- and chess- and fridge-bots. But this time* everything is different. The decade started with a lavish AI spring, flourished with Big Data and the Internet of Things, doped the world with an almost forgotten scent of smart homes and smart cities. This set the stage for something bigger, a new AI summer, a hot and deep summer of Neural Networks: NN based AI, or ANN, also referred today as "real" and "strong" AI: manufactured systems are imitating a network of brain neurons, algorithms are rewriting themselves, computers learning from their mistakes, and showing off with the first successes in science, business, security ... and art. In July 2015 Google released their Deep Dream, a restless algorithm that learned to stare at an image until it sees the dog inside.

Instant messaging apps have taken over. WhatsApp, iMessage, WeChat, Signal, Slack, Facebook Messenger, Snapchat -- billions of users exchange information in bite-sized chunks on any or all of these platforms on a daily basis. In fact, as of mid-2015, people were spending more time on messaging apps than on social networks, and as messaging apps become increasingly more sophisticated, this trend shows no sign of reversing. Messaging platforms have expanded far beyond simply enabling users to send and receive text messages, photos, and videos. Many of them allow users to exchange documents and files, voice memos, location information, and sometimes even cash.

A Northwestern University team developed a new computational model that performs at human levels on a standard intelligence test. This work is an important step toward making artificial intelligence systems that see and understand the world as humans do. "The model performs in the 75th percentile for American adults, making it better than average," said Northwestern Engineering's Ken Forbus. "The problems that are hard for people are also hard for the model, providing additional evidence that its operation is capturing some important properties of human cognition." The new computational model is built on CogSketch, an artificial intelligence platform previously developed in Forbus' laboratory.

Join Entrepreneur's The Goal Standard Challenge and make 2017 yours. Artificial intelligence (AI) gets more advanced every year, but there are still some major limitations keeping us from seeing a futuristic reality that includes robot butlers and near-complete societal automation. Fortunately, some of these limitations are on the verge of being overcome, and if you watch and plan carefully, you'll be able to take advantage of those improvements for your business. Right now, most AI systems "learn" new information through a kind of structured force-feeding, relying on information given to those systems by humans. However, this form of "supervised learning" isn't scalable, and doesn't mimic the way that human beings naturally learn.

In yet another episode of man versus machine, an artificial intelligence developed by Carnegie Melon University has been absolutely dismantling a team of professional poker players, accumulating a staggering lead of almost $800,000. The showdown takes place as part of the "Brains vs. Artificial Intelligence" competition which pits a group of four poker pros against the crafty supercomputer Libratus in a heads-up game of No-Limit Texas Hold'em slated to continue for 120,000 hands. TNW Conference won best European Event 2016 for our festival vibe. See what's in store for 2017. Since January 11 when the contest initially kicked off, the players have now passed the midway point of the the race, having completed almost 65,000 hands in total.

Theresa May is due to announce details of the "Modern Industrial Strategy" at a regional meeting of the cabinet in the North West. The new plan will center on ten key strategic pillars, according to the release unveiled by the Prime Minister on Sunday. "We must become a more innovative economy and do more to commercialize our world-leading science base to drive growth across the UK," reads the first point, called "Investing in science, research, and innovation." The government is going to spend £4.7 billion ($5.85 billion) on the new strategy with the money steered to such areas as AI, "smart" energy technology, robotics, and 5G wireless. The project will improve living standards and drive economic growth across the whole country, according to Business and Energy Secretary Greg Clark.

In early August, IBM announced that it will acquire Merge Healthcare Inc., a company that sells systems that help medical professionals access and store medical images. This move is a critical step in IBM's plan to put AI to work medically by training its Watson software to identify maladies like heart disease and cancer. Merge is valuable to IBM because it owns 30 billion images, including computerized tomography, X-rays, and magnetic-resonance-imaging scans. The company can use these images in its deep learning training program. IBM is hoping that the same kind of software that lets Flickr recognize your face or a dog in your photos can help Watson identify symptoms of diseases.

As we head into 2017, artificial intelligence (AI) is an emerging technology trend that is generating increasing buzz among business leaders of both start-ups and well-established companies. From virtual assistants to image recognition to self-driving cars, we're only just beginning to scratch the surface of how AI-related technology will impact our daily lives and transform how businesses operate. IBM's Chief Innovation Officer Bernie Meyerson optimistically predicts 2017 will be "the year of the solution as opposed to the year of the experiment." The worlds of artificial intelligence and Internet of Things (IoT) are poised to collide. This year's CES conference in Las Vegas was packed with all kinds of smart devices touting new AI capabilities.

This is the first article in a series "quick guide to digital tech", where I will cover some of the most discussed topics in digital technology. With the series I aim to give a simple understandable overview, with examples most readers can relate to or have heard of. In the end, I will give a short comment on where I think the technology is today and where I see it heading in a near and far future. Artificial Intelligence may be the most disruptive technology the world has seen since the Industrial Revolution. It describes every aspect of learning or any other feature of intelligence that can be described so precisely that a machine can simulate it.