How many virtual assistants can you fit in one smartphone? European network operator Orange is hoping there's room to squeeze in one more. With the right apps, you can already talk to Alexa, Cortana and Google through your smartphone -- and maybe also to Siri or Bixby if you went with one of the big brands. Djingo will be able to answer questions, send text messages, place calls, play music and video from Orange's set-top box, and control smart home devices. It draws on the company's research into linguistics and artificial intelligence, and will even offer financial advice in conjunction with a new banking service Orange is launching, the company said.

Google's Home device is late to the domestic AI assistant game, but it can do one trick that Alexa can't right now: Tell family members apart just by their voices. Up to six people can link their Google accounts to one Home device, then train Google's Assistant to recognize their voices. Once that's done, it'll be able to distinguish you from your spouse or other family members and give you pertinent info, like your schedule or traffic on your usual route. As it stands, the lack of multi-user support is a nuisance. While Home can still give everyone general information and trivia via the Knowledge Graph (and more erratic "featured snippets"), it can only create appointments and do other user-specific stuff for one designated Google account.

Cortana is one of our favorite tools for getting things done more quickly and easily in Windows 10. So we're pretty pleased that Windows 10 Creators Update brings a handful of improvements to our favorite digital assistant. After using them for a few days, we've pinpointed three that can help improve your productivity right now. As helpful as it is to have Cortana at arm's reach, it's now useful when you're across the room, too, thanks to a new full-screen mode. Anytime your computer is unlocked and idle, you can summon your virtual assistant by saying, "Hey, Cortana" from anywhere within earshot and a screen-size interface will pop open.

Amazon is the exception to nearly every rule in business. Rising from humble beginnings as a Seattle-based internet bookstore, Amazon has grown into a propulsive force in at least five different giant industries: retail, logistics, consumer technology, cloud computing, and most recently, media and entertainment. The company has had its share of missteps -- the expensive Fire phone flop comes to mind -- but is also rightly known for strokes of strategic genius that have put it ahead of competitors in promising new industries. This was the case with the launch of cloud business AWS in the mid-2000s, and more recently the surprising consumer hit in the Echo device and its Alexa AI assistant. Today's Amazon is far more than just an "everything store," it's a leader in consumer-facing AI and enterprise cloud services. And its insatiable appetite for new markets mean competitors must always be on guard against its next moves.

Machine learning has long powered many products we interact with daily--from "intelligent" assistants like Apple's Siri and Google Now, to recommendation engines like Amazon's that suggest new products to buy, to the ad ranking systems used by Google and Facebook. More recently, machine learning has entered the public consciousness because of advances in "deep learning"--these include AlphaGo's defeat of Go grandmaster Lee Sedol and impressive new products around image recognition and machine translation. While much of the press around machine learning has focused on achievements that were not previously possible, the full range of machine learning methods--from traditional techniques that have been around for decades to more recent approaches with neural networks--can be deployed to solve many important (but perhaps more prosaic) problems that businesses face. Examples of these applications include, but are by no means limited to, fraud prevention, time-series forecasting, and spam detection. InfoQ has curated a series of articles for this introduction to machine learning eMagazine covering everything from the very basics of machine learning (what are typical classifiers and how do you measure their performance?), to production considerations (how do you deal with changing patterns in data after you've deployed your model?), to newer techniques in deep learning.

Entertainment has already been transformed by tech advances that seem custom-made to blow our minds. Whether it's amazing graphics that transport us to incredible new worlds or interactive 3-D games that feel like real life, entertainment is evolving into a more personalized, immersive experience, and the key to this engaging entertainment future is artificial intelligence. At its most simple, AI is technology that can operate and think for itself without traditional human intervention. If you have an iPhone, Siri is a great example. Without lifting a finger, you can ask Apple's digital assistant to find things for you, take a note or call your mom.

The first was the steam engine-driven Industrial Revolution; the second involved the innovations from Henry Ford's assembly line. Third, microelectronics and computer power appeared on factory floors. Now, manufacturing businesses are beginning to integrate robotics, automation and other data-driven technologies into their workflows. Now, manufacturing businesses are beginning to integrate robotics, automation and other data-driven technologies into their workflows. Robots have taken over difficult, dangerous and repetitive physical tasks, improving factory safety, worker comfort and product quality.

Any article on the web that starts with terms like "Machine Learning" and "Artificial Intelligence," more or less drops us hints about the future. Although it all seems like preparing a foundation for the time ahead, things have started picking up pace already. It's difficult to deny that even though machine learning and A.I. sound more like future technologies, we all have been using it already. Some of the notable examples include Google Home, Amazon Echo, Google Photos etc. What's more, smartphone manufacturers are trying their luck nowadays with these technologies. Care to think of Apple Siri, Google Assistant, Microsoft Cortana, and newborn Samsung Bixby? It often reminds me of what Elon Musk once said, "Great companies are built on great products."

From phone support and mobile apps to ATMs and chatbots -- when it comes to customer service, banking automation has come a long way. However, the one missing piece that these automated banking features lack is a real human being to interact with during a transaction. That's something that Soul Machines, a New Zealand-based startup, is hoping to change. The company's new technological development is intended to bring back the human component to customer service without relying on actual people. To meet this goal, Soul Machines is producing artificial intelligence-powered avatars that are designed to emotionally engage with banking customers.

Having artificial intelligence on our mobile devices is becoming commonplace these days. Many of our modern smartphones are equipped with AI assistants. Apple has Siri, Google has Google Assistant, and Samsung's new lineup of S8 smartphones will see the debut of their new virtual assistant, Bixby. Amazon Alexa is also coming to the iPhone. However, Facebook has now announced the launch of their new open-source platform, Caffe2, which will provide coders with the machine-learning tools necessary to develop AI software for mobile devices.