It wasn't so long ago that all banking was done in a branch, by phone, via an envelope or at an ATM. Then came the personal computer, and online banking became popular because of its convenience and ability to track balances, which used to require a branch visit and updating a passbook. Today, most transactional banking is done on mobile devices. The smartphone's dominance in banking and of consumers' communication, social, entertainment, health, shopping, scheduling and research lives is the perfect example of digital integration done right. Today's smartphone replaces separate music players, cameras, game consoles, fitness trackers, personal digital assistants and a phone.

Badri is the Senior Vice President, Technology at Vonage - Video Engineering. As I speak with business leaders from around the world, I'm continually surprised by two important realities that seem to go unnoticed and that are poised to transform the way companies engage with their customers. First, while artificial intelligence (AI) remains a buzzword, many people are still unaware of how advanced algorithms have become. We're not talking about a collaborative filtering algorithm that predicts which Netflix shows you'll want to watch next. Today's algorithms are able to mimic human decision-making on tasks as complex as composing music and predicting what topics are of interest to your Congressional representatives.

Recent years have seen a proliferation of chatbots and so called'personal assistants.' These supposedly serve both the convenience of the user, as well as the goals of a company. However, these bots often realize poor adoption rates, high user frustration, and limited benefit to the corporation. In fact, they often hurt an enterprise. Current reality is that natural language applications have severe limitations, failing on tasks that even a child could easily handle.

Production recommendation systems rely on embedding methods to represent various features. An impeding challenge in practice is that the large embedding matrix incurs substantial memory footprint in serving as the number of features grows over time. We propose a similarity-aware embedding matrix compression method called Saec to address this challenge. Saec clusters similar features within a field to reduce the embedding matrix size. Saec also adopts a fast clustering optimization based on feature frequency to drastically improve clustering time. We implement and evaluate Saec on Numerous, the production distributed machine learning system in Tencent, with 10-day worth of feature data from QQ mobile browser. Testbed experiments show that Saec reduces the number of embedding vectors by two orders of magnitude, compresses the embedding size by ~27x, and delivers the same AUC and log loss performance.

I am a major sci fi fan. Well, at least I thought I was until I went to my first Star Trek convention in my 20s and realized that I was in the minority of people who did not speak Klingon or know episode numbers, titles or dates. Most recently, I have become inspired by Black Mirror, a show originally aired by the BBC and now offered on Netflix. The brainchild of Charlie Brooker, Black Mirror is the Twilight Zone for our times, giving us a glimpse as to how technology trajectories can be used to affect society in unintended ways in the coming decades. As Frederik Pohl used to say, 'A good science fiction story should be able to predict not the automobile but the traffic jam.' Metaphorically speaking, this show sure is predicting traffic jams.

The mention of artificial intelligence usually sparks conversations around the singularity and robots revolting against humans, but what really is AI and how is it used today? Outside of the realm of science fiction, AI is becoming more and more prevalent in our society. The technology can be discreet, such as a mobile phone voice-controlled assistant, or more obviously, such as self-driving cars. Artificial intelligence programs are widely used over a number of industries. The technology can be used to help doctors to analyse images, control robots in automotive manufacturing and even translate for Amazon's home assistant, Alexa.

The concept of Artificial Intelligence (AI) or Machine Intelligence is no more an unknown or unexplored concept to us and all the thanks go to Siri, Alexa, Cortana, and Google Assistant for being live examples. Even though these assistants evolved recently, but AI was there for quite some time. Right from filtering our mailboxes to AI-powered chatbots or AI enabled recommendations; we were always surrounded by Artificial Intelligence. AI has also impacted various fields, like aiding in synthesizing new chemicals, medical diagnoses, identifying the faces of criminals in a huge crowd, self- driving cars, and even creating new works of art. Even though there is a lot of debate and discussion going on about the future of AI but for now Artificial Intelligence is here to stay.

Google is doubling down on KaiOS, the "light" operating system that makes low-cost feature phones feel a little smarter. Today, the company announced that the Google Assistant will be upgraded with Voice Typing "over the coming months," allowing KaiOS users to dictate text messages, web searches and basically anything else that uses a text box. KaiOS and the Assistant can also be set to different languages, according to Google. That means you could read the phone's menus, icons and settings in English and then talk, text and search through the Assistant in Spanish. KaiOS, if you need a refresher, is a spiritual successor to the ultimately-doomed Firefox OS.

Google is continuing its mission to put Assistant everywhere and it's not just trying to stuff its digital helper in various hardware, but in more apps as well. The company already inserted Assistant in the Maps app, which it officially unveiled at CES this year. Here at MWC, Assistant is showing up in perhaps a more personal, conversational app -- Android Messages. It's basically the Assistant as it was in the Allo app (RIP) -- when you chat with your friends about things like movies, restaurants and the weather, Assistant will show suggestion bubbles to let you send info cards to your pal. The AI scans your texts for contextual clues as to what you're talking about.

However similar they may seem in terms of underlying technology, conventional search engines are quite different from product recommendation engines. Behaviour is typically at the center of a recommender system, while it is an added dimension for the search engine.