Bio: Alexander Gude is currently a data scientist at Lab41 working on investigating recommender system algorithms. He holds a BA in physics from University of California, Berkeley, and a PhD in Elementary Particle Physics from University of Minnesota-Twin Cities. About: Lab41 is a "challenge lab" where the U.S. Intelligence Community comes together with their counterparts in academia, industry, and In-Q-Tel to tackle big data. It allows participants from diverse backgrounds to gain access to ideas, talent, and technology to explore what works and what doesn't in data analytics.

That's the warning of a whole range of experts who warn that the connected home – the idea that appliances and gadgets throughout the home – might be turned on their users. The technology is intended to make life easier for the people who use it, but like many new developments comes with terrifying warnings for their users. That's because the same things required to use the smart home – internet connections, microphones and cameras – also make them perfect targets for hackers. And because they occupy such an intimate place in people's homes, once they're spying on you they can learn some of the most intimate data there is. Those problems primarily hit cheap devices, many of which are made with little interest in how private they are.

Burdened with outdated legacy systems and the rise of advanced fintech banking options, banking executives continue to seek out new ways to boost margins and embrace the technological disruption prevalent in their industry. While the promise of artificial intelligence signals new opportunities for robust growth, it's important for banks to first ensure they have all their data organized and ready to use for the prerequisite machine learning necessary to ramp up an AI system. While popular culture has been predicting the coming of advanced AI for decades, it's taken a bit longer for reality to catch up to the movie magic. But now AI is a major part of society and business, as consumers comfortably talk to their Amazon Echoes or easily discuss their daily schedules with Apple's Siri. "Some analysts dubbed 2017 as the Year of AI in banking." Beyond the personal assistant, another place AI has planted a firm foothold is the banking sector.

Artificial intelligence is not fiction. It is already our reality and has been for a very long time. Its origins date back to the 1950s. How has it changed since then? Are computers able to teach themselves? What does a smartphone have to do with the landing on the moon, and could machines be smarter than humans?

Using AI And Machine Learning To Personalize Content Creating original branded content solves many problems for marketers, but also presents challenges - among them distribution and realizing ROI from what can be a costly investment. Time Inc., CBS and Telepictures are among hundreds of publishers working with IRIS.TV, which recently introduced a product to manage the distribution of branded content. Creating original branded content solves many problems for marketers, but also presents challenges - among them distribution and realizing ROI from what can be a costly investment. Time Inc., CBS and Telepictures are among hundreds of publishers working with IRIS.TV, which recently introduced a product to manage the distribution of branded content.

When Amazon first came out with a smart recommendation algorithm for customers, millions of consumers receive their first tailored shopping experience personalized to their own interests. This changed the consumer world and introduced us to a whole new era of shopping. Amazon's algorithms, using a method called "item-to-item collaborative filtering", are able to provide targeted shopping recommendations by creating a personalized experience for each person. Even in a very basic form, this was the beginning of using machine learning in a very practical manner. But can such artificial intelligence and machine learning also act as an enabler for changes in medicine and healthcare, as much as Amazon's algorithm changed consumerism?

What is the future according to Google? All of the world's information is available right at our finger tips, and, of course, Google is the company to provide it. Google may seem to have diversified in recent years, exploring everything from self-driving cars to smartphones. The truth is that machine learning is actually at the heart of everything it does. Google started off as a search engine, and naturally expanded into the machine learning and AI fields.

In just a few short years, we've seen an incredible proliferation of devices that want to quantify, connect, and regulate your home. While the potential is huge, the actual results vary widely. Some products, like the Amazon Echo and Philips Hue light bulbs, are nailing the fundamentals, while others struggle with basic functionality. We tested 75 smart home products over hundreds of hours. In the end, we found eight stellar examples of how to do smart home right.

The company is touting the HomePod as a high-fidelity speaker programmed to learn people's tastes so it can become a digital disc jockey that can automatically play tunes that its listeners will like. The HomePod also will include Apple's voice-activated assistant Siri to respond to requests like the Echo and Google Home.

Plenty of companies offer chat support to troubleshoot problems with your phone. But do you really want to talk to another human for what could be a simple fix? You don't have to... if you have a Pixel 2. Android Police has discovered that you can ask Google Assistant for help with battery issues. Ask why your battery isn't charging properly and the AI companion will not only run a diagnostics check, but look for particularly power-hungry apps. It offers to connect you to Google's chat or phone support if it can't answer your questions in one shot, although problems in the AP test suggest this component isn't ready for prime time.