The technology is being used for a wide array of purposes in many industries. Amazon's Alexa, Apple's Siri, Google Assistant and many more, are examples of AI being used to make our lives easier. But what exactly is Artificial Intelligence, and how can it help you increase your website's conversions? Put simply, it's the idea that a machine (or more specifically, a computer program) can complete tasks in a very similar way to a human. And the main difference between how a human and a conventional computer program approach solving a problem is that a human can improvise, learn from mistakes and get better with experience.

It has been said that to give a man a fish is to feed him for a day, whereas to teach a man to fish is to feed him for life. Forward-looking financial service companies are similarly finding that giving computers instructions is not nearly as fruitful as teaching them to write their own. From assessing credit risks to beefing-up the security of their own networks, fintech startups, in particular, are turning to machine learning finance-based solutions in order to work smarter rather than harder. Considering that over 200 leading financial institutions will attend the upcoming October 2016 Machine Learning Fintech Conference, investment in this subset of artificial intelligence (AI) seems to be a wise move, indeed, for companies that don't want to be left behind. With leading banks starting to invest in AI, and machine learning in particular, fintech companies will be significantly disadvantaged if they fail to do likewise.

Amazon is encouraging us to put listening devices in every room of the house with executives from Amazon saying that Echo assistants don't listen to private conversations, they say the device will start listening to conversations only if the word Alexa was used, this is not always the case as a story from a user in Portland highlights. An Alexa user from Portland, Oregon has installed Echo and Smart bulbs in every room of their house thinking that nothing bad will happen, however when asking Amazon to investigate an issue about Alexa recording a private conversation between her and her husband that was sent to a random number in her address book without her consent. She didn't believe her friend at first, however when her he explained the conversation between her husband she finally believed them. "You sat there talking about hardwood floors." Danielle realised the colleague must have heard everything.

It was a week of near misses and closer hits than the tech industry probably would have wanted. Amazon's Alexa "accidentally" recorded more than a few customers' private conversations, Apple's iPhones turned out to be bendier than anticipated, and that PUBG chicken dinner of yours wound up being harder fought than anybody had previously thought. Nobody: The number of people who saw that coming. Kidding, of course, even the greenest of horned labor attorney could tell you that Tesla CEO Elon Musk was simultaneously talking out of his tailpipe and putting his entire automotive empire in legal jeopardy when he started running his mouth on Twitter the other night. This is why you don't let the guy who owns the business do the ads for said business.

Ask around, and you'll find a surprising number of people have a smart speaker in their homes. As of January, 1 in 6 Americans own a voice-activated speaker, but Gartner predicts 75 percent of U.S. households will have one by 2020. With a broad gamut of capabilities--streaming news and music, answering questions, issuing reminders, and controlling connected home products--they can offer a good value proposition, particularly when paired with an attractive price point. But just because our Echos, Google Homes, and HomePods can do all sorts of things doesn't mean we're taking advantage of every single one of their features. Many of us are content to rely on our digital assistants for just one, or a handful, of specific tasks.

The challenge of controlling and protecting data is a big one, but the bigger question is how to make people more productive with corporate information while maintaining standards of compliance and governance for broad access and use in the age of digital business. Applying AI and Natural Language Processing within the various stages of data analytics is a key way to democratize data and build in safeguards for broad use. Below is a Q&A with Ayush Parashar, a Co-Founder and Vice President of Engineering with Unifi Software. Often the quest for security can eclipse data usability. How can applying AI be used to both discover data and ensure information is not being seen or used by those that shouldn't have access to certain kinds of data?

From Daniel Eran Dilger's More companies need to temper their Artificial Intelligence with authentic ethics: When Apple outlined that its new HomePod didn't initiate phone calls on its own, nobody jumped to the conclusion that this was because having a device in your home that anyone's voice could use to place a telephone call from your personal mobile number might be a bad idea. Instead, the company was generally lambasted for "again" failing to match one of the many features of Amazon's Alexa Echo always-listening appliances. This week, Alexa got famous for recording a private conversation and automatically sending it to a random contact of the owner. That's something HomePod doesn't do, not because Apple doesn't know how, but because Apple chose not to rush to make it possible to do things that might not be a good idea in the long run. My take: Does HomePod really know how to initiate a phone call?

Tasks such as search and recommendation have become increas- ingly important for E-commerce to deal with the information over- load problem. To meet the diverse needs of di erent users, person- alization plays an important role. In many large portals such as Taobao and Amazon, there are a bunch of di erent types of search and recommendation tasks operating simultaneously for person- alization. However, most of current techniques address each task separately. This is suboptimal as no information about users shared across di erent tasks. In this work, we propose to learn universal user representations across multiple tasks for more e ective personalization. In partic- ular, user behavior sequences (e.g., click, bookmark or purchase of products) are modeled by LSTM and attention mechanism by integrating all the corresponding content, behavior and temporal information. User representations are shared and learned in an end-to-end setting across multiple tasks. Bene ting from better information utilization of multiple tasks, the user representations are more e ective to re ect their interests and are more general to be transferred to new tasks. We refer this work as Deep User Perception Network (DUPN) and conduct an extensive set of o ine and online experiments. Across all tested ve di erent tasks, our DUPN consistently achieves better results by giving more e ective user representations. Moreover, we deploy DUPN in large scale operational tasks in Taobao. Detailed implementations, e.g., incre- mental model updating, are also provided to address the practical issues for the real world applications.

Using AI to create humanlike computers is a shortsighted goal. When customers feel like no one is listening, they may be right. Or, they may be unknowingly talking to a machine. Last week, Google announced Duplex, an artificial intelligence (AI) assistant that can handle customer service requests, such as booking an appointment or providing basic information. We've had automated phone attendants for years, but the new buzz is that customers can't tell that this automated attendant isn't human.

Amazon.com Inc. AMZN 0.44% said that one of its Echo home speakers mistakenly recorded a private conversation and sent it to a person in the owners' contact list, an incident that raises questions about the security of such voice-operated devices. Confirming a report by a local television station in Seattle, Amazon on Thursday said that the Echo device misunderstood pieces of a conversation as commands, causing it to think it was being instructed to send the message. "As unlikely as this string of events is, we are evaluating options to make this case even less likely," a spokeswoman added in a statement. The incident was first reported by KIRO 7, which aired an interview with a Portland, Ore., user identified only as Danielle. The user said that one of her husband's employees had received a recording sent from inside her house.