While assisting customers through their digital transformation is the current priority for SAP, CEO Bill McDermott has predicted over the next five to 10 years the hype will be around machine learning, artificial intelligence, and augmented reality. "I think very strongly that intelligent applications will fundamentally change the way you do work in the enterprise and the way you collaborate with your trading partners outside of the enterprise," he said during his keynote at 2016 SAP Sapphire Now. He went on to say it's no longer viable for businesses to just automate internal processes, rather the future needs to focus on using automated systems to make intelligent predictions. "This idea of CRM and SFA -- that's dead; everybody has got that. We're not just automating internal sales process anymore so the sales director has a sales forecast that makes sense. Even with all that technology investment you still only have about 22 percent confidence on the sales forecast, while other companies have 44 percent, so there's something wrong with the sales forecast," he said.

It was several weeks ago, Google came out with the most shocking earning and its managers could not stop taking about the business's investments in artificial intelligence and apparatus learning. For any company that would be a complete distraction from its core business. Google combined the two topics. Artificial intelligence sits on the far end of the machine learning which people create software's that can learn about what is happening around the world. Google is the largest sponsors of artificial intelligence.

Artificial intelligence (AI) may some day surpass the human race and lead to our extinction, but we're all right so far. It's technologically advanced, but it doesn't yet understand how humans interact in the real world. Remember Tay, Microsoft's teen chatbot? They released her into the wild, wild Web, innocent one moment and a racist, sexist and genocidal AI the next? Tay was an IRL Chappie, corrupted by trolls and abusers, picking up the worst parts of social media until its plug was pulled.

At Facebook's F8 developer conference in April, CEO Mark Zuckerberg announced his company's latest Messenger feature a personal shopping assistant and touted the app as being similar to shopping with a friend. There's just one key difference: The friend is a robot. More companies and organizations are turning to artificial intelligence (AI)-driven "chatbots", or conversational robots, as a new wave in customer service. The idea is to personalize each user's experience through advanced human-computer interactions. In the case of Facebook's e-commerce platform, the user will be able to interact with brands and companies that have opted to get involved with the app and order products and services without ever having to leave Messenger.

There have been an increasing number of reports about the rapidly developing world of AI, where computers can learn to use big data independently. Most recently, Google yesterday announced it would begin exploring whether automated machines are capable of creativity and producing original artwork and music. Many people's gut reaction to this is that nothing, not even the innately human ability to create, is safe from the machines. It makes me think of the "infinite monkey theorem": give a monkey a typewriter and an infinite amount of time and eventually, it will type something that makes sense. So, if we give computers (AI) huge amounts of big data and time, they will eventually develop creative ideas that can compete with the likes being dreamt up by skilled creatives and brilliant agencies all over the world?

Affectiva, a startup developing "emotion recognition technology" that can read people's moods from their facial expressions captured in digital videos, raised 14 million in a Series D round of funding led by Fenox Venture Capital. According to cofounder Rana el Kaliouby, the Waltham, Mass.-based company, wants its technology to become the de facto means of adding emotional intelligence and empathy to any interactive product, and the best way for organizations to attain unvarnished insights about customers, patients or constituents. She explained that Affectiva uses computer vision and deep learning technology to analyze facial expressions or non-verbal cues in visual content online, but not the content or conversations in a video. The company's technology ingests digital images--including video in chat applications, livestreamed or recorded videos, or even GIFs--through typically the simplest web cams. Its system first categorizes then maps the facial expressions to a number of emotional states, like happy, sad, nervous, interested or surprised.

Many people worry when they hear that organisations are using and sharing digital health data. What are they up to? Meanwhile, those organisations may worry that being more open could lead people to complain about the decisions they make. It's a vicious circle that can stop good things happening. A lack of transparency over the extent of data sharing by the UK National Health Service on 1.6 million patients with Google's artificial intelligence company DeepMind has been reported by New Scientist.

Instead of clicking around inside of Google Analytics to find the answer you want about your web traffic, wouldn't it be nice to just talk to Google to get what you want? That future is coming, Google demoed today, thanks to machine learning. Google's Babak Pahlavan, who heads measurement and analytics products for Google, showed the coming capability today during the Google Performance Summit. In one example, he asked by speaking, "How many users did we get from organic search in April?" and received the answer: In another, as you can see below, he spoke, "What were my best selling products for April?" and again, got a fast answer: Wow. Speak and get answers from Google Analytics.

"And then Hephaestus, Olympian god of fire, created a massive automaton out of bronze." Known as Talos, the giant creation was to protect the island of Crete. "On seeing strangers approach, he enveloped himself in fire and engulfed them." Or so the Greek myth goes. Our fascination with machines that can think is rooted in our collective histories.

Learn machine learning for free, because free is better than not-free. This website is inspired by the datasciencemasters/go and open-source-cs-degree github pages. This one is specifically for machine learning and features textbooks, textbook-length lecture notes, and similar materials found with a simple google search. This repository is meant as a general guide and resource for a free education. Note: Please report any broken links as an issue on the Github page.