A team out of Waseda University in Japan has unveiled some pretty cool images from the first half of the 20th century, given new depth with full colorization thanks to an artificial intelligence. Unlike colorizing black and white photos using software, which can be a lengthy process of repeated cleaning and coloring – this AI samples similar photos and applies those colors and tones to the photo at hand. So, for example, if you have an old black and white photo of your grandparent's house – and that house is still standing today – you can take a photo of it and the AI will learn how to color the old photo based on the tones and levels from the modern day one. Similarly, if you have an old photo of an area or people that don't exist, the program can still learn and adapt those colors from similarly colored images. The more photos and images it has to pull from, the greater detail and true to color matching it will be able to provide.

That obsession you have with '80s-era vintage Transformers? AI and predictive learning will be critical to allowing eBay to set up a truly personalized experience for each consumer, according to CEO Devin Wenig, who spoke Thursday at Recode's Code conference in Rancho Palos Verdes, California. He said the company has been working on taking advantage of demographic data and sophisticated algorithms to offer more relevant products. Wenig is just the latest executive to talk up the promise of AI at the Code conference, with high-profile figures such as Google CEO Sundar Pichai, IBM CEO Ginni Rometty and Microsoft co-founder Bill Gates all talking up its potential. "It's all about customer relevance," he said.

At Criteo, machine learning lies at the core of our business. We use machine learning for choosing when we want to display ads as well as for personalized product recommendations and for optimizing the look & feel of our banners (as we automatically generate our own banners for each partner using our catalog of products). Our motto at Criteo is "Performance is everything" and to deliver the best performance we can, we've built a large scale distributed machine learning framework, called Irma, that we use in production and for running experiments when we search for improvements on our models. In the past, performance advertising was all about predicting clicks. That was a while ago.

This could help you in building your first project! Be it a fresher or an experienced professional in data science, doing voluntary projects always adds to one's candidature. My sole reason behind writing this article is to get your started with recommendation systems so that you can build one. If you struggle to get open data, write to me in comments. Recommendation engines are nothing but an automated form of a "shop counter guy". You ask him for a product.

Lee Se-dol, the 33-year-old South Korean who is the 18 time world champion of Go, finally beat Google's artificial intelligence program. It marks his first win in the ongoing challenge. Since the AI already won three games in the five-game series, a series which is taking place in Seoul, the victory is already secured; however, the final matches are still being played out. It is hoped that these games will help the Google team get some valuable insights into how well the program functions. And it seems that people like knowing that humanity can put up a good show in the face of artificial intelligence. Indeed, Lee's win was met with uncharacteristically enthusiastic applause.

What does Artificial Intelligence (AI) mean to you? Will it enslave us or set us free? Do you fear it, hate it, love it or just accept it? The nature of AI and what it means for humanity has become one of the big philosophical issues of our time. Computer processing speeds have been accelerating since the development of the microchip.

A US prison was recently able to detect and prevent inmates from carrying out illegal business by using artificial intelligence to analyse calls made into and out of the prison for unusual patterns. All calls that connect on prison phone lines in the US are recorded and monitored, but it is a very time-consuming and boring job to listen endlessly to thousands of hours of conversations between inmates and their families in order to try to work out if anything nefarious is going on. To speed the job up, one prison in the American mid-west is using a machine learning system designed by London-based firm Intelligent Voice to listen to all the audio files and detect odd patterns for humans to take a closer look at, according to New Scientist. When the prison wardens looked at the analysis report created by the software, they discovered that one of the most popular non-trivial phrases being used by inmates was the phrase "three way". Initially the wardens thought that the phrase was some sort of sexual reference, but because the word was used so often in phone calls they investigated further, and realised that the phrase was actually a secret code word.

Glaser continues, "Although scholars and policymakers agree that Washington has a role to play here, it isn't clear what the path to that policy looks like--even as pressing questions accumulate. They include deciding when and how Google's self-driving cars take to American highways and examining how bias permeates algorithms. 'One thing we know for sure is that AI is making policy challenges already, such as how to make sure the technology remains safe, controllable, and predictable, even as it gets much more complex and smarter,' said Ed Felten, the deputy US chief of science and technology policy leading the White House's summer of AI research. 'Some of these issues will become more challenging over time as the technology progresses, so we'll need to keep upping our game'."

If someone asked you to define'intelligence,' how would you respond? The question elicits significantly different answers based on whom you ask. Ask people to define'artificial intelligence' and the conflicting answers only multiply. Not only are there multiple schools of thought within the field of AI, but the term itself stands on a word that we're still only beginning to understand. This was the elephant in the room at the Applied Artificial Intelligence Conference last week in San Francisco.

Blade Runner is the perfect film for experimentation with artificial intelligence. In Ridley Scott's sci-fi classic, Rick Deckard (played by Harrison Ford) hunts down and "retires" humanoid robots called replicants. A new class of replicants called "Nexus-6" are capable of yielding human-like emotional responses, further blurring the line between who is human and who is machine. This journey eventually leads Deckard to question his own humanity. So it's all too fitting that a reconstruction of the film created by an AI could be mistaken for the real thing.