A new app promises to let people take selfies with anyone they like – including dead people or celebrities. ELROIS, a South Korean company, only needs a 3D scan of any person's face for its "With Me" app. Once it has one, it can'resurrect' that person – allowing them to react to what you say and move around, as well as letting you take pictures with them. The app has been explicitly created to allow people to recreate the image and personality of someone who has passed away, according to its creators. They said that it is a way of overcoming a broken heart by interacting with a virtual recreation of their deceased loved ones.

Without a doubt, 2016 was an amazing year for Machine Learning (ML) and Artificial Intelligence (AI) awareness in the press. But most people probably can't name 3 applications for machine learning, other than self-driving cars and perhaps their voice activated assistant hiding in their phone. There's also a lot of confusion about where the Artificial Intelligence program actually exists. When you ask Siri to play a song or tell you what the weather will be like tomorrow, does "she" live in your phone or in the Apple cloud? And while you ponder those obscure question, many investors and technology recommenders are trying to determine whether,,, or will provide the best underlying hardware chips, for which application and why.

From Netflix recommendations to credit card fraud detection, artificial intelligence (AI) is already part of our daily lives. But as AI expands, where do we draw the line on how intimate we become with this new technology?

I recently spoke with Michael Finley, Head of Machine Learning at BI software company AnswerRocket, who helped elaborate. Before machine learning, most software "ran the way it was programmed: people turned instructions into computer code, and the computer did what that code told it to do." A very simple example would be a calculator: you fed the calculator numbers, told it what to do (add, subtract), and the calculator gave you results. With machine learning, however, the software can adapt. Finley continues: "Software with machine learning doesn't do the same thing the day you install it as it does the tenth or hundredth day you run it."

We did this for decades. There are better methods now. How well can this be done? What are the risks involved? Predicting Marketing Campaign Response Using Amazon Machine Learning by Chris Mohritz Today, marketers are challenged with higher expectations and thinner budgets.

AI/Robotics-focused venture capital firm and research lab COMET LABS' co-founder Liu Wei has been hired by BAIDU VENTURES as its new CEO. Baidu Ventures is the independent investment arm of the Chinese technology conglomerate, Baidu. As the new CEO of Baidu Ventures, Wei will be leading investments and strategic partnerships for the firm with a strong focus on developing new artificial intelligence technologies. Additionally, Wei and Baidu Ventures will be strengthening their partnership with Comet Labs both in the United States and in China. Baidu Ventures has committed resources and talent to enhance Comet Labs' industry-focused accelerator programs, beginning with the Transportation Lab that was recently opened for startup applications.

The use of artificial intelligence (AI) could add a whopping £654bn to the UK economy, according to a report published by Accenture. Perhaps this is why the government announced late last week that it would pump approximately £20m into developing and researching AI and robotics as part of its long-awaited Digital Strategy. The technology, which could potentially render almost half a million public sector workers unemployed over the next 15 years, has been credited with helping organisations save time and money – both attractive propositions for governments across the globe. With this in mind, here are four examples of how the UK public sector has delved into the world of AI in recent times. The Serious Fraud Office used AI for the first time in its landmark investigation of Rolls Royce, which saw the car manufacturer found guilty of bribery and corruption in January this year.

With performance falling, investors fleeing and offices closing, hedge funds had a rough 2016. But San Francisco-based Numerai was just getting started. Instead of relying on the genius of a single person or small team, the firm uses encrypted data sets to crowdsource stock market prediction models built with artificial intelligence from 12,000 anonymous data scientists worldwide who compete to win bitcoin. And if that flew over your head, the main takeaways are that this hedge fund has orders of magnitude more data scientists trying to improve its investing strategy than the biggest name hedge funds today, and what makes the firm possible is a confluence of technologies that didn't even exist a few years ago -- primarily in cryptography and artificial intelligence. Now the one-year-old company, founded by 29-year-old South African Richard Craib (a Forbes 30 Under 30 designee) and funded by the likes of Union Square Ventures, is launching its own cryptocurrency, the Numeraire. It is the first virtual currency issued by a hedge fund and one of the first released by a company (rather than a group of developers or a non-profit).

I'm a big Star Wars fan, so when "Rogue One: A Star Wars Story" descended on theaters late last year, I braved the crowds to see it -- twice in the first 18 hours. And just like all the other Star Wars movies, "Rogue One" stoked our geeky imaginations with all the technological possibilities of a galaxy far, far away, like holographic displays and all sorts of strange devices. And did you notice the Imperial server farm? Of course, advanced artificial intelligence (AI) was well-represented too: Like C-3P0, R2-D2 and BB-8 in earlier movies, Rogue One's K-2SO displayed uncanny humanness. The futuristic Star Wars-esque world is still mostly the stuff of Hollywood movies, but technology visionaries are hard at work bringing us ever closer.

It is no mystery why poker is such a popular pastime: the dynamic card game produces drama in spades as players are locked in a complicated tango of acting and reacting that becomes increasingly tense with each escalating bet. The same elements that make poker so entertaining have also created a complex problem for artificial intelligence (AI). A study published today in Science describes an AI system called DeepStack that recently defeated professional human players in heads-up, no-limit Texas hold'em poker, an achievement that represents a leap forward in the types of problems AI systems can solve. DeepStack, developed by researchers at the University of Alberta, relies on the use of artificial neural networks that researchers trained ahead of time to develop poker intuition. During play, DeepStack uses its poker smarts to break down a complicated game into smaller, more manageable pieces that it can then work through on the fly.