Dec 22, 2018; Carson, CA, USA; Los Angeles Chargers defensive end Joey Bosa (99) looks on before the game against the Baltimore Ravens at StubHub Center. You don't know a lateral from a screen pass or the difference between a tight end and wide receiver. And what the heck does "three men in a box," "RPO" "nickel defense" or the "coffin corner" mean? Your significant other is fixated on watching the NFL playoffs that kick off this weekend. And if you're going to spend any meaningful time with your honey, then you best watch, too.

Equipped with innovative Artificial Intelligence, the impressive AXI washing machine and washer dryer can understand your voice, your laundry habits and provide washing and drying solutions personalised to your family's life and needs. Fully Wi-Fi connected with a host of bespoke functions, you can control AXI via our Wizard app, using Amazon Alexa or Google Assistant.

Playing music, listening to directions or ordering a takeaway while you commute home from work could soon be a reality thanks to a new'smart bike'. The Cybic Legend, being unveiled at the Consumer Electronics Show (CES) in Las Vegas next week, comes equipped with Amazon's Alexa digital assistant. The bike, which will be launched alongside an electric version, features a control mounted on the handlebars that lets riders access its internet connected features. That includes performance data, personalised light settings, theft tracking, a security lock, an alarm and a music player. Playing music, listening to directions or ordering a takeaway while you commute home from work could soon be a reality thanks to a new'smart bike'.

The concept of machine learning is becoming better understood as we increasingly interact with it every day. From Netflix and Amazon recommendations, to Siri and Cortana voice recognition, to Google Maps travel time calculations, we're all becoming more familiar with machine learning technologies--even if we don't quite realize it yet. Applying machine learning in industry, however, is a different story. Though several companies are doing it, it's not nearly as ubiquitous as the consumer-oriented applications mentioned above. And that's what made a presentation by Kathy Applebaum and Kevin McClusky of Inductive Automation during the Ignition Community Conference 2018 so interesting.

As we look back to 2018, we can trace some technologies which impacted the lives of an ordinary man both in the personal and professional terms. Artificial intelligence which was thought to be a simple assistant for making a person's life easier has now become an integral part of many people's lives in certain spheres. Did you ever imagine in your wildest dreams that in future you will be conversing with an artificial assistant? We always used to think it as a scene straight out from the Hollywood science fiction movie, but as we usher into the brave new world of incredible inventions, fictions are turning into reality making us question the very existence of the statement "This is not possible." This was highly questioned as consumers were in a dilemma how trustworthy would it be, but as in case of every new invention people are skeptical in the beginning but get used to it with each passing year.

The virtual assistant on your smart speaker and smartphone draws on artificial intelligence; so do every Google search and every Netflix recommendation. And while the bulk of the investment in AI and machine learning--the subset of AI in which computers look for patterns in large data sets--is coming from the tech sector, it is spilling into other areas. Which uses of AI will come to ubiquitous fruition? Bloomberg offers a simple test: "Ultimately, the future of AI will depend on its ability to make money." Financial services seems like fertile ground for AI to generate profit.

When we reviewed Amazon's updated Echo Plus, we concluded that the $120 device was a solid improvement with "some noticeable thump" and "crisper and more detailed" music tracks. But as a gadget that doubles as a smart home hub, it's less impressive. In particular, we were disappointed by the lack of support for Z-Wave or Lutron Clear Connect protocols, especially since the control over smart devices like the Hue bulbs felt basic and underwhelming for a smart home hub. While the audio and the price caught our attention, we ultimately didn't feel it was a necessary upgrade over the first-gen Echo. But that's just our take -- now we'd like to hear yours.

You no longer have to pull out your phone (or look at your watch) to track your dietary habits. Lifesum has introduced what it says is the first food tracking app for Google Assistant, making it easier to keep tabs on your eating patterns. If you ate a large meal or grabbed a glass of water, you just have to use your voice to add that to your log. You can also update your body weight, tackle challenges (such as hiding sugary food in your kitchen) and ask for updates on your progress. Lifesum personalizes meal sizes based on your goals, but it's not very specific beyond that.

Vuzix has been making smart glasses for well over a decade, primarily for enterprise use such as medical applications or stocking shelves in warehouses. Last year, Vuzix teased a prototype of the Blade, a smaller, slimmer pair made for consumers. Not only does it come with a floating display a la Google Glass, it's also compatible with Alexa (and, eventually, Google Assistant). Now the company says it's ready to ship the Blade for $1,000 as it attempts to pick up where Google Glass left off. "This represents a huge step forward for us," Vuzix CEO Paul Travers told Engadget.

Recommender systems are one of the most common used and easily understandable applications of data science. Lots of work has been done on this topic, the interest and demand in this area remains very high because of the rapid growth of the internet and the information overload problem. It has become necessary for online businesses to help users to deal with information overload and provide personalized recommendations, content and services to them. Two of the most popular ways to approach recommender systems are collaborative filtering and content-based recommendations. In this post, we will focus on the collaborative filtering approach, that is: the user is recommended items that people with similar tastes and preferences liked in the past.