From the advancements in natural language processing that make Siri and Alexa possible, to the machine learning advancements that give robo-advisors their trading chops, AI's ability to simulate human thinking means it can also streamline our lives. It can preempt our needs and requests, making products and services more user friendly as machines learn our needs and figure out how to serve us better.

I've let a few friends try Sony's newest flagship active noise-cancelling headphones, and the first thing they comment on is just how eerily quiet the world gets. Right now, as I write this, there's a construction crew ripping up the concrete outside my apartment. They've been at it for more than a week, and it's made it difficult to concentrate. With Sony's ANC on and my window open, the loud commotion is flattened to a light hum. With the window closed, I have trouble telling if they're still at it out there.

The Reco Algorithms Team is hiring a Principal Research Engineer.

Today, with Digitization of everything, 80 percent the data being created is unstructured. Audio, Video, our social footprints, the data generated from conversations between customer service reps, tons of legal document's texts processed in financial sectors are examples of unstructured data stored in Big Data. Organizations are turning to natural language processing (NLP) technology to derive understanding from the myriad of these unstructured data available online and in call-logs. Natural language processing (NLP) is the ability of computers to understand human speech as it is spoken. NLP is a branch of artificial intelligence that has many important implications on the ways that computers and humans interact.

If you've been eyeing a new gadget for your home, you may have noticed a curious trend. While much of the tech world is still made of glass, aluminum, plastic, and composites, a number of companies are opting for a softer material to outfit their electronics: cloth. Textiles are emerging as a fun, stylish, and irreverent way to accessorize and protect the tech we use in our homes each day. We saw a few examples among the smorgasbord of products Amazon announced at its surprise hardware event in Seattle last month. The Echo Dot and Echo Plus each got a cloth-covered refresh.

Whether you observe Columbus Day or Indigenous People's Day, this is a weekend with a few extra tech and gaming sales. We've highlighted some discounts for tech we really like. We've tested many of these items, and the rest look like they're well worth your hard-earned money. New Fire TV Stick 4K for $50 (Was $70). We haven't yet tested the latest Fire TV, but it doesn't appear to pack a lot of surprises.

In recent years, Variational Autoencoders (VAEs) have been shown to be highly effective in both standard collaborative filtering applications and extensions such as incorporation of implicit feedback. We extend VAEs to collaborative filtering with side information, for instance when ratings are combined with explicit text feedback from the user. Instead of using a user-agnostic standard Gaussian prior, we incorporate user-dependent priors in the latent VAE space to encode users' preferences as functions of the review text. Taking into account both the rating and the text information to represent users in this multimodal latent space is promising to improve recommendation quality. Our proposed model is shown to outperform the existing VAE models for collaborative filtering (up to 29.41% relative improvement in ranking metric) along with other baselines that incorporate both user ratings and text for item recommendation.

The machines haven't taken over. However, they are seeping their way into our lives, affecting how we live, work and entertain ourselves. From voice-powered personal assistants like Siri and Alexa, to more underlying and fundamental technologies such as behavioral algorithms, suggestive searches and autonomously-powered self-driving vehicles boasting powerful predictive capabilities, there are several examples and applications of artificial intellgience in use today. However, the technology is still in its infancy. What many companies are calling A.I. today, aren't necessarily so.

"Alexa, what's the weather going to be like today." It's taken decades for scientists to understand natural human speech to the point where voice-activated interfaces such as Alexa, the natural language processing system by Amazon, are sufficiently enabled to be successfully accepted by consumers. Alexa is who talks to users of Amazon's Echo products including the Echo, Dot and Tap, as well as Amazon Fire TV and other third-party products. Even since 2012, when the patent was filed for what would ultimately become Amazon's artificial intelligence system Alexa, there has been tremendous growth in capabilities and the credit for that growth goes to machine learning. For something that we do every day without giving it any thought, conversation between machines and humans is complex.

As technology has continued to accelerate in recent decades, workers throughout many industries have faced an increasingly real threat of having their positions become obsolete, be it due to changing economic forces or new innovations that allow employers to replace them with automated processes. One recent innovation has been that of voice-activated hardware and software, specifically thinking of platforms such as Amazon's Alexa. Tech experts have said that this platform has spread rapidly, so much so that they expect it to become an even larger part of the way we interface with all things digital in the coming years. Even now in the early phase of this latest tech progression, some in the hospitality sector have embraced tech like Amazon's Alexa (or other products similar to it) in order to serve their guests. As a result of this, some hotel staff members have begun to worry that Amazon Alexa and other voice-activated platforms could soon replace them, greeting and attending to guests at the front desk the way humans generally do now.