Our modern age is rife with questions that could have been (indeed, often were) posed by genre writers such as Ray Bradbury, H. G. Wells or Philip K. Dick. We'd like to pose a few of our own: Is it truly safe to put our lives in the "hands" of self-driving cars? Is Amazon's Alexa spying on our idle chatter? What happens when smart machines become smarter than the people who operate them? Many of the most critical questions brought about by advancing technology are related to work.

New Mexico police report that a smart home device (incorrectly labeled at first as a Google Home) intervened in a domestic violence incident by calling 911. When Eduardo Barros asked "did you call the sheriffs?" They overheard the altercation and called both negotiators and a SWAT team, who arrested Barros over assault, battery and firearms charges after a stand-off. Barros' girlfriend was hurt in the altercation. However, police contend that the situation could have been much worse.

Smart home devices are popular purchases for home users, but they're also increasingly capable of doing things that their owners might not expect. Eduardo Barros was house-sitting with his girlfriend and her daughter when the two got into an argument that became physical, ABC News reports. Barros allegedly pulled a firearm on his girlfriend and threatened to kill her, asking if she'd called the sheriff. The home speaker heard this as a command and proceeded to call the police. Deputies then arrived on the scene, removing Barros' girlfriend and her daughter from the home. A SWAT team and crisis negotiation team also came to the home and were able bring Barros into custody after an extended stand-off.

Q: I looked up my name at a people search site. Wow! Anyone can see my age, where I live, names of my relatives and more, for free! Can I remove these very personal details? A: I'm glad you searched for yourself, and I wish more people would. Many people are shocked to learn how much is freely exposed online: name, age, current address, past addresses, voting records, criminal history and so on. It's almost impossible to delete yourself from the internet completely, but you can easily crack down on these people search databases, no lawyer required.

One of the most surprising part about Recommender Systems is, 'we summon to its suggestions / advice every other day, without even realizing that'. Let me show you some examples. Facebook, YouTube, LinkedIn are among the most used websites on Internet today. Let us see how they use recommender systems. Facebook: Suggests us to make more friends using'People You May Know' section Similarly LinkedIn suggests you to connect with people you may know and YouTube suggests you relevant videos based on your previous browsing history.

Thanks to the likes of Google, Amazon, and Facebook, the terms artificial intelligence (AI) and machine learning have become much more widespread than ever before. They are often used interchangeably and promise all sorts from smarter home appliances to robots taking our jobs. But while AI and machine learning are very much related, they are not quite the same thing. AI is a branch of computer science attempting to build machines capable of intelligent behaviour, while Stanford University defines machine learning as "the science of getting computers to act without being explicitly programmed". You need AI researchers to build the smart machines, but you need machine learning experts to make them truly intelligent.

Often called out for being slow to change, the insurance industry is beginning to catch up quickly on cognitive technologies. You've probably had regular help from a virtual assistant by phone or online, assisting you with basic tasks such as directing your call or giving you your bank balance. The companies that employ the virtual assistants think so, too, and are applying these AI/robotic processes to more and more of their everyday business operations. Often called out for being slow to change, the insurance industry is beginning to catch up quickly. Carriers like Celina and USAA are using AI in their daily operations and reaping the benefits.

"If you're not doing AI today, don't expect to be around in a few years," says Japjit Tulsi, VP of engineering at eBay, "It really is that important for companies to invest in -- especially commerce companies." Tulsi will speak next week at MB 2017, July 11 and 12 in SF, MobileBeat's flagship event where this year we've gathered more than 30 brands to talk about how AI is being applied in businesses today. It has focused on the potential of AI for the past ten years. The company's approach to AI has been built on a platform of research and development, Tulsi says, plus decades of insights and data about consumer behavior, making even the simplest applications incredibly valuable. As an example, Tulsi points to the merchandizing strip at the bottom of every item page, which shows similar items that a shopper might be intrigued by, and often leads them down a positive rabbit hole of shopping and buying.

Amazon's notification feature on Alexa is now running, which means you'll be able to get notifications if you have the Amazon Echo, Echo Dot, Echo Show or a compatible Alexa-enabled device. You can opt-in for what features you want Alexa to notify you about, but as of now Alexa can only tell you about packages are out for delivery, according to Amazon Fire TV & Fire TV Stick News. Amazon announced exclusive deals for Alexa Prime users. Telling the voice assistant: "Alexa, sign me up for Prime," will allow users to sign up for the one-year membership for $79.

It's a type of artificial intelligence that allows computers to learn new data and apply it to a service, all without being explicitly programmed to do so. There are a few obvious examples, like chatting with Amazon's Alexa in your living room or Siri on your iPhone. Machine learning can also be more subtle, like when Google suggests a new route after sneakily cross-referencing your common destinations with a daily traffic report. Similar conveniences have made their way into customer service via machine learning. The difference is that while the aforementioned machine learning examples learn and adapt to your daily routines, AI tools for customer service focus more on the customer's journey and the workflows of support staffs.