Humans pricked by info-hunger pangs used to hunt and peck for scraps of trivia on the savanna of the internet. Now we sit in screen-glow-flooded caves and grunt, "Alexa!" Virtual assistants do the dirty work for us. Problem is, computers can't really speak the language. Many of our densest, most reliable troves of knowledge, from Wikipedia to (ahem) the pages of WIRED, are encoded in an ancient technology largely opaque to machines--prose.

Artificial intelligence has, irrefutably, revolutionized our lifestyle as well as business processes, including digital marketing, in ways once impossible to imagine. Artificial Intelligence… This long, wordy term may sound perplexing to you, but what's more perplexing is the fact that we are using AI technology every day and most of us didn't even realize it till now. Let's just take a reality check. Think of all those times when Gmail suggested you smart replies for an email or Spotify recommended new releases and old favorites as per your music taste. Artificial Intelligence lies behind all this; it capitalizes on the algorithms that determine our online activities and thereby makes suggestions relevant to how we behave online.

We demonstrate the first possibility of a sub-linear memory sketch for solving the approximate near-neighbor search problem. In particular, we develop an online sketching algorithm that can compress $N$ vectors into a tiny sketch consisting of small arrays of counters whose size scales as $O(N^{b}\log^2{N})$, where $b < 1$ depending on the stability of the near-neighbor search. This sketch is sufficient to identify the top-$v$ near-neighbors with high probability. To the best of our knowledge, this is the first near-neighbor search algorithm that breaks the linear memory ($O(N)$) barrier. We achieve sub-linear memory by combining advances in locality sensitive hashing (LSH) based estimation, especially the recently-published ACE algorithm, with compressed sensing and heavy hitter techniques. We provide strong theoretical guarantees; in particular, our analysis sheds new light on the memory-accuracy tradeoff in the near-neighbor search setting and the role of sparsity in compressed sensing, which could be of independent interest. We rigorously evaluate our framework, which we call RACE (Repeated ACE) data structures on a friend recommendation task on the Google plus graph with more than 100,000 high-dimensional vectors. RACE provides compression that is orders of magnitude better than the random projection based alternative, which is unsurprising given the theoretical advantage. We anticipate that RACE will enable both new theoretical perspectives on near-neighbor search and new methodologies for applications like high-speed data mining, internet-of-things (IoT), and beyond.

At the beginning of last year we announced an Amazon Polly plugin for WordPress. This plugin allows blog and website creators who are using WordPress to quickly and easily create audio versions of their posts, articles and websites. A few months later, we updated the plugin with the ability to quickly translate the content of websites to other languages using the Amazon Translate service. This functionality, together with the ability to create audio versions, allows you to voice the content of sites in translated languages. We want to allow creators and authors to reach more readers/listeners around the world using the latest AI services offered by AWS.

Surely we've heard the word float around in recent years as one of the hottest new buzzwords to hit the technosphere, but does anyone know what machine learning is? Well, from the title alone we can deduce that it has something to do with machines learning, which is undoubtedly true. However, let's look at a more formal definition: "Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to'learn' with data, without being explicitly programmed." The magic of this field of study comes in the very last segment of that definition: "Without being explicitly programmed." Traditionally in computer science, whenever we needed to have the machine do something, we'd write out a clear-cut instruction set in the form of code.

The recent breakthroughs in Artificial Intelligence has opened insurmountable opportunities for businesses, especially in digital marketing domain. As technology is advancing at a rapid pace, AI has already emerged as a disruptor that is significantly impacting various sectors like finance, education, and e-commerce. AI can effectively transform digital marketing because it can help businesses deliver improved customer experience. At its core, AI pertains to the use of machines and their ability to continuously learn and solve problems. This augmentation can make a big difference in digital advertising space as it will not only create efficiency but proffer more satisfying work on behalf of employees.

John McCarthy first coined the term "Artificial Intelligence" (AI) in 1956 at the Dartmouth Conference along with four other founding colleagues – Marvin Minsky, Oliver Selfridge, Ray Solomonoff, and Trenchard More. The original definition and concept of AI according to John McCarthy is "Every aspect of learning or any other feature of intelligence can in principle be so preciously described that a machine can be made to simulate it. An attempt will be made to find how to make machines and concepts, solve kinds of problems now reserved for humans, and improve themselves." What it simply means is that AI is a term for "simulated intelligence" in machines. The machines are programmed to mimic the cognitive functions of the human brain. Upon further discussion, seven following criteria were agreed for the Artificial Intelligence (AI).

Move over Alexa… there's a new virtual assistant in town. Passengers on board MSC Bellissima, which will be launched by godmother Sophia Loren in Southampton next month (March 2), will meet MSC's newest crew member Zoe – the cruise industry's answer to the voice-activated digital assistant. Powered by artificial intelligence (AI), Zoe can speak seven languages and answer over 800 of the most commonly asked questions – with thousands of different variants of each query – providing information about on-board services, suggestions for activities, and even help in booking a specific service. She's easy to use too: all guests need to do is say, "OK Zoe", and she's ready to help. Developed in partnership with HARMAN and Samsung Electronics, Zoe will be able to interact with in-cabin TVs to offer further guidance to passengers and, as with at-home devices, passengers will be able to connect their phones directly to the device via Bluetooth in order to access personal music and podcasts.

As a futurist, some patents really stand out. Here is one I'm really bullish on, as we enter a post-mobile world of Voice-AI controls and hand gestures. What if there was an invisible button between your thumb and index finger, what could it do? What AI-assistant or dashboard could it summon? Alphabet's Google unit won approval from U.S. regulators to deploy a radar-based motion sensing device known as Project Soli.

A link has been posted to your Facebook feed. Amazon acquired another startup this week, the maker of the beloved tech product Eero, a mesh router that improves dead Wi-Fi spots in the home. To that, you might have said, OK, so? But, more importantly, it's an indication of how Amazon wants to go further than just making our homes "smart." It wants to turn our dwellings into the "Amazon Home."