Let's kill a few false ideas first. No, artificial intelligence won't take the control of the world. You can forget your dreams about Terminator, The Matrix, Johnny 5 and Wall-e (yes I know for the last one it's kind of sad). But you just have to watch some Alexa, Google home or any other AI fails on YouTube to understand that we are far away from that scenario. Now that we agree on that, let's talk more seriously.

If the bot answers a question logically or solves a given task, it should be considered smart. A lot of personal assistants like Apple Siri, Amazon Alexa and Google Home can be regarded as intelligent. But can we say these assistant bots are Turing smart? Well, when we cannot distinguish between a bot and a human, then the bot can be called Turing smart. To check whether a bot is human level intelligent or not, a lot of ways are there, and the most prominent one is the Turing test.

Have you ever wondered why so many companies program robots, virtual assistants, and AI with feminine traits? Have you ever pondered, if there were more women behind the algorithms, how AI would be different -- not just vocally and aesthetically, but functionally? With Alexa, Cortana, Siri, Google Home, and most GPS systems defaulting to female, there has been plenty of speculation over the ubiquity of demure, ladylike tones emitted from the speakers of modern machines. Research has demonstrated a greater affinity for female voices on the part of men and women alike, prompting big tech companies like Amazon to opt for "Alexa" over "Alexander." Still, it's impossible to ignore the gendered implications at play, even if consumer demand drives such decisions.

You don't need a Facebook account to sign up for Bumble anymore. Starting tomorrow, you can use your phone number to register for a new account on the dating app, according to Wired. Like Tinder, Hinge and countless other apps and services, Bumble streamlined the process of setting up a profile and adding photos by offering Facebook as a login option. Last week Tinder users had trouble logging in due to a glitch with Facebook privacy settings. In the wake of Cambridge Analytica (CA) and Mark Zuckerberg's congressional testimony, Bumble's VP of international marketing and communications Louise Troen said "many" of its over 30 million users were looking for a different sign-up/log-in method.

Alexa and Google Assistant have been taking over homes for a few years now, so it's probably easier to name the companies that haven't made a smart speaker. The options are seemingly endless. Audio gear that harnesses a virtual assistant comes in all shapes and sizes, with some making big claims about the quality of sound they get out of such small devices. Panasonic is doing just that with its $250 SC-GA10; however, the company's promise of "premium hi-fi sound" failed to make a lasting impression. As you should expect, Google Assistant works just fine here to deliver a "smart" speaker experience.

Voice-enabled assistants are the newest buzz among consumers across industries with Google, Amazon, Apple, and other giants rolling out AI-infused gears functioning primarily through conversational voice interfaces. Globally, the number of customers using voice-assistants is increasing with a CAGR of 29.4% and is estimated to reach 1.83 billion by 2021. Alexa, Siri, and Google Assistant have all become an integral part of a millennial's day. From setting up reminders, checking the weather, to shopping – these voice-enabled digital assistants have covered most of the bases heavily influencing the mobile-tech experience. Financial services have been one of the biggest beneficiaries of such innovations around mobile tech and IoT.

The 2017 holiday shopping season trended better for online U.S. retailers with an estimated 16.6 percent jump in e-commerce sales compared to the same period last year. With a successful holiday season behind them and consumer confidence up, retailers are starting 2018 optimistic. But what can retailers learn from this past holiday season? When we talk to our customers, the biggest challenge in this new era of retailing is just keeping up with customer expectations. Bringing new, differentiated experiences to market is a monumental task.

Thanks to the massive increase in available data, we are seeing major advances in cognitive computing in areas such as machine learning, natural language processing, and predictive data analytics. A number of firms in financial services are taking advantage of this to cut costs and to find new, profitable strategies. While prop trading firms and hedge funds remain the biggest adopters, there are a few robo-advisors utilizing AI methods. But it's getting harder to identify the fakers from the makers in such an overcrowded market. As competition heats up, firms are cavalierly tossing out buzzwords: risk management, artificial intelligence, tax loss harvesting, re-balancing.

She sits patiently in millions of homes, an unremarkable cylinder commonly referred to as Alexa. But Amazon's new'virtual assistant' has been touted as nothing short of technological revolution. In response to spoken commands, she answers questions which previously required an internet search, can perform mundane domestic tasks such as turning on lights, and makes online purchases – through Amazon, obviously. Can it all be as innocent as it seems, particularly in an age rife with internet snooping? Some users have even reported'bone-chilling' cackles emanating from their speakers at random moments.

As big data gradually comes into play in the world of business, machine learning has become one of the most important tools for companies to solve various kinds of problems. Firms across various industries are all trying to incorporate this rising technique into their business and get a competitive edge in understanding their consumers better. In fact, Google, Apple, Facebook and other major tech firms have been in a race to acquire AI startups focusing on machine learning. In May 2017, Apple acquired a California-based startup Lattice.io for around $200 million. The startup specialized in using machine learning techniques to make "dark data" machine readable. This only goes to say how the industry leaders too believe in the power of machine learning.