Artificial Intelligence development doesn't have to be overly technical or complex, and this post is to show a cool way it is adding color to our lives…literally. Below are eleven handpicked examples (more available) of various black & white videos which were colorized automatically thanks to an AI algorithm created by Richard Zhang and co, now available as a web app used to colorize B&W photos. Of course, these videos aren't individual photographs and required a trained network to colorize an entire scene. These were selected as to show a variety of capabilities, and how it is not an exact science, rather work in progress with great progress. The Lukas Graham video was created by Ron Zohar, who done the same to a Charlie Chaplin scene (video removed).

Artificial intelligence is game-changing technology. This doesn't just apply to the workforce, but the economy too. Before we delve deeper into how AI can contribute to a better economy, let's get the terms straight first. There's capital, which is used to measure the value of production and man-made goods. Then there's labor, which refers to the work that has been done by people, as well as the skills possessed by the workers. The economy grows when labor or capital increases, as well as when they are used with improved efficiency.

There are still so many unanswered questions when it comes to the age of AI and how we can live with Artificially Intelligent machines and robots that may become more intelligent than us. How can we coexist comfortably and conveniently if one day, the machines we have created, decide to think for themselves? Do you believe in technological singularity and is it near? Here are some common ethical dilemmas we will have in the age of AI. An AI machine can be a computer or smart device and can also be known as a robot with or without appendages and can emulate human life physically.

I was invited to give a keynote lecture at the XV International Conference on University Libraries in Mexico City last month. The conference debated the changes occurring or need to occur in university libraries towards the United Nations' "Agenda 2030" horizon. My lecture, titled "Libraries and Knowledge in the Age of Information Overload", took a close look at the impact of the rampant Info Overload that is affecting the entire knowledge landscape on the academic library, and vice versa. The main thing is that where in centuries past knowledge – carried in books – was scarce and precious, today the internet has created a huge overload of information, dubious information and fake information; we are all struggling to survive this info tsunami. As a result, if the libraries of the past were like serene shrines where people would come to bask in the glow of accumulated knowledge, today libraries must serve as sanctuaries where users can get help to survive the aforementioned tsunami, and gain the skills and support to allow them to find insight yet discriminate against the fake and the useless.

Computers are advancing in leaps and bounds and are increasingly displaying attributes of practical Artificial Intelligence: they may not yet clash with astronauts, but they definitely take over many daily tasks that used to depend entirely on human brainpower. One area where this is felt is knowledge work tools: just look at Google's uncanny ability to figure what search results you really need despite your ill-formed and misspelled query… and as this trend continues to accelerate, you can't help but think: what capabilities would we want to surrender to this AI? What should it do for us – and what would we rather it didn't? Because if we don't discuss this, the software vendors will push at us whatever they think of, whether we like it or not! I'm not talking about better spell checking, mind you; that is happening. But we can expect far more powerful stuff.

Muggles and fans alike would be so excited to celebrate Harry Potter's birthday, July 31st, by reading a new Harry Potter chapter that was written strictly by artificial intelligence; it isn't per the new book – Harry Potter and the cursed child, nor is it an addition to the seventh in the series. While the muggle world will go crazy today, and the Internet may likely break due to the new Harry Potter release, we thought it would be a great added birthday gift to have a new chapter that fits after the fourth book, Harry Potter and the Goblet of Fire. So here is a little info on this new artificial intelligence Harry Potter chapter, which even JK Rowling couldn't have written: I trained an LSTM Recurrent Neural Network (a deep learning algorithm) on the first four Harry Potter books. I then asked it to produce a chapter based on what it learned. Don't expect this new machine created Harry Potter text to reveal untold secrets, a vision into the future, or what is planned for the wizarding world.

Thirty years ago, artificial intelligence was still seen as something only found in science fiction novels. As the world continues to move rapidly towards AI machines, there is one group of individuals who believe that AI can provide more opportunities for the human race, while others believe artificially intelligent machines would destroy the human race if not handled appropriately. It may be a while before this concern is a reality. For now, there are many companies who are creating products based on AI technology and television shows that are giving us a glimpse of what artificial intelligence could look like. While some shows failed to show this in a realistic way, others are almost indistinguishable from actual humans.

If you've heard of the phrase that email is dead, you're not alone. Email is 46 years old now, making it the oldest form of online communication. It was developed by engineer Ray Tomlinson on June 1971 although it wasn't until the early 1990's that it became frequently used, when commercial internet service providers went mainstream. The earliest widely used email services including Hotmail came around in the mid-1990's, and ever since then, millions of people around the world have relied on email for personal and professional communication in real time. However, many people think that in this day and age, email is dead.

I remember when email first arrived in the workplace. For years we had been sending memos (and actual carbon copies) in brown inter-office envelopes; then in 1994 all of a sudden everyone in my global company (Intel) could communicate by email at the click of a mouse. You could write a coworker on the other side of the planet and a reply would be waiting for you the next morning. Looking back, it is a marvel just how fast this heaven had turned into hell. In less than a year people were seeing their inbox as a major enemy.

In practice, machine learning deals with supervised and unsupervised learning problems where one can compare, in some metric, the obtained results with real values of goal variable in test sample, or some set of benchmarks. Latent goal variables that are unobservable or unavailable for a researcher introduce an interesting challenge for data scientists. This problem may arise in several Artificial Intelligence domains, such as prediction of personal reaction on events, subjective assessments etc. There are two main challenges coming up in these cases: (a) to build an appropriate machine learning algorithm; (b) to provide reliable performance indices. Several approaches have been suggested to overcome the above challenges.