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.

There is a lot you can do with Alexa. Here's how you can add skills. It was every Amazon Echo owner's nightmare. Alexa, the connected speaker, really, truly, was listening in on your conservations, and behind your back, passed on the recording of a private chit-chat to someone on your Echo contact list. This actually happened this week, according to Seattle TV station KIRO, which told the story of a Portland woman's privacy gone amuck.

You love the idea of buying an AI and IoT device like Google Home or Amazon Echo for the holiday season. You want to speak and have it deliver a song or weather report or sports score. However, did you ever think about the other side of this coin? Here is a nagging question we all must wrestle with: As a technological innovation increases, how to we protect our personal information and privacy? AI and IoT devices like Google Home, Amazon Echo, Microsoft Cortana, Apple HomePod and countless others that are popping up in the marketplace are simply incredible.

Every coin has two sides. We've been talking for so long about all the coming benefits of wireless smart homes, connected homes and connected offices. And it's true, there are many incredible advancements in this space. However, there is an important warning I want to discuss. Everyone must understand other side of the coin which is seldom discussed, loss of privacy.

Building on its strategy to develop innovations that drive retail transformation for brands, retailers and manufacturers, PLM leader Centric Software announces the unveiling of its first artificial intelligence-based PLM module. Centric Software provides the most innovative enterprise solutions to fashion, retail, footwear, outdoor, luxury and consumer goods companies to achieve strategic and operational digital transformation goals. The term'artificial intelligence' dates back to the 1950's when computer scientist John McCarthy coined the phrase to describe the potential'thinking machines' of the future. Today, artificial intelligence (AI) tools are systems modeled on the problem-solving abilities of the human brain, breaking complex problems down into different layers of information comprised of many smaller problems. Applications vary considerably ranging from virtual assistants like'Alexa' and'Siri' to Netflix viewing recommendations to Amazon recommending things we might like to buy.