FILE - This Dec. 20, 2010, file photo, shows signage at a Starbucks store in New York. Starbucks is launching voice ordering though its iPhone app. Starting Monday, Jan. 30, 2017, anyone with a device that has an Amazon device with Alexa, like the Echo smart speaker, is able to place a Starbucks order by just using their voice. Starbucks is also launching a beta test of voice ordering through its iPhone app. The Seattle-based coffee giant says the feature is being rolled out to a limited group of 1,000 people nationwide Monday.

We can't deny that artificial intelligence assistants have come flooding in the market lately. You have Amazon's Alexa, Google Assistant, Apple's Siri, and Microsoft Cortana. Finnish tech company Nokia is also getting in on the AI Assistant bandwagon. Its name is Multi-purpose Intuitive Knowledge Assistant or simply MIKA. The announcement for Nokia's new AI voice assistant comes a month before Nokia's expected appearance at the Mobile World Congress.

Amid Nokia's planned comeback in the smartphone scene, there were reports that the Finnish company was also interested in joining the digital assistant trend. However, it seems Nokia does not have any intention of joining the major players in the growing market. In fact, the formerly top cellphone maker is not planning to position its voice-activated assistant as a direct rival to Amazon's Alexa, Apple's Siri, Microsoft's Cortana and Google's Google Assistant. Nokia's smart assistant's name, MIKA, has a nice ring to it mainly because it is an acronym that stands for what it is and what it does. Short for Multi-purpose Intuitive Knowledge Assistant, MIKA is not like any of the digital assistants that are being marketed as commercial services at present.

Since then, as Digital tsunami flooded, there are tons of websites selling everything on web but these two are still going great because of their product recommendations. We as customers, love that personal touch and feeling special, whether it's being greeted by name when we walk into the store, a shop owner remembering our birthday, helping us personally to bays where products are kept, or being able to customize a website to our needs. It can make us feel like we are single most important customer. But in an online world, there is no Bob or Sandra to guide you through the product you may like. This is where recommendation engines do a fantastic job.

Content curation, sentiment analysis, predictive customer service, and optimal ad targeting are among multiple examples of where AI is already impacting marketing. Our expectations of how AI can radically transform marketing in coming few years is nothing short of mind blowing. Billions of web pages and social media posts supplementing CRM data will provide a 360-degree view of each customer. This will enable hyper personalized marketing in which an AI-driven business concierge delivers end-to-end curated buying experiences tailored to each individual customer. These scenarios are based on emerging practice and trends, and therefore completely realistic, but they mask the anxiety about the possible downside of AI's increasing role in marketing.

Cleo, the London-based FinTech startup, got a recent boost in its angel investing round from Skype Founder Niklas Zennström. Cleo has created an artificial intelligence-powered chatbot program that works with users to manage their finances. To date, Cleo has received $700,000 in funding from eight angel investors, including the recent contribution from Zennström. Users seeking financial advice can currently access Cleo via multiple channels, including the chatbot's mobile app, Facebook Messenger, as well as through AI-assistant integrations with Amazon's Alexa and Google Home. Barney Hussey-Yeo, Cleo's cofounder and CEO, was quoted by TechCrunch as saying: "We're trying to reduce the complexity and increase the transparency of financial services for our generation. Cleo's an AI financial assistant that makes managing your money incredibly simple. Using artificial intelligence and machine learning, you can ask Cleo nearly anything about your finances."

As it goes every year, one hot feature sets a trend in technology, and suddenly every company boasts some variation of which that is uniquely theirs. This year, that feature is AI. Hot on the heels of Alexa's and Google Assistant's holiday successes, Artificial Intelligence on phones has become the de facto must-have feature – whether consumers know it or not. In any case, manufacturers seem not to realize that AI doesn't mean "Anything Intuitive" – that's just how operating systems are supposed to be. Yet it seems that OEM's are eager to label nearly any vaguely intuitive feature as AI.

Machine learning has long powered many products we interact with daily–from "intelligent" assistants like Apple's Siri and Google now, to recommendation engines like Amazon's that suggest new products to buy, to the ad ranking systems used by Google and Facebook. More recently, machine learning has entered the public consciousness because of advances in "deep learning"–these include AlphaGo's defeat of Go grandmaster Lee Sedol and impressive new products around image recognition and machine translation. In this series, we'll give an introduction to some powerful but generally applicable techniques in machine learning. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.

Christina is audience development editor. After graduating from the University of Nottingham reading philosophy and theology in 2013, Christina joined a tech start-up specialising in mobile apps. She has a keen interest in the mobile platform and innovative tech. In recent years AI has brought us some pretty impressive and widely used tech, from the image recognition being used by Facebook to speech recognition technology at work in Amazon's Alexa or Apple's Siri. It's these breakthroughs in deep learning and neural networks that have led to some of the most exciting yet also worrying times in tech. Stephen Hawking, Elon Musk and Bill Gates (to name a few) have all warned us about the dangers of unregulated AI development.