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8 Cases Where You Use Artificial Intelligence Without Knowing It

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It is no coincidence that Artificial Intelligence and Machine Learning are used or will be used for such technologies that will define how the real future of many industries. However, one can not and should not talk about the future, but of the present. In the field of communication and marketing, a lot of algorithm-based tools can be used daily, which can suggest the best thing to do, lighten up the work, or be able to help us in more basic tasks, writing a message in the best possible way. Think also of customer care services, which in many cases consist of real chatbots that can answer many different questions or needs. The artificial intelligence has come to our lives for some time now, even outside the scope of work, if you think of apps that we listen to music, play online, or allow us to get in touch with our friends.


Tech Leaders Dismayed by Weaponization of Social Media

IEEE Spectrum Robotics Channel

The tech industry can't hide from the information war, particularly when its own creations are being weaponized. That was the consensus of a panel at the Techonomy17 conference in Half Moon Bay, Calif., last week. The group assembled to discuss the meaning of authority in a networked, artificially intelligent world. The panelists quickly zoomed in on the manipulation of Facebook, Google, and other sites by Russians during the U.S. presidential election. They, as well as several other speakers at the conference, painted a dark picture of our current online world for at least the immediate future; they concluded that preventing such manipulation is not going to be easy.


Is machine learning the future of marketing?

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Will it be entirely automated by smart AIs that fully understand human nuance? Will it be entirely manual and managed only by individual people without the aid of technology? As we'll discuss shortly, the top influencers in marketing put their heads together on this very topic, and the results may surprise you. In any case, it's safe to say that marketing probably isn't going back to the old days of billboards, newspapers, and radio spots. The numbers don't lie: the future of marketing is definitely digital.


Advertisers' Biggest Misconceptions About Silicon Valley's Two Giants AdExchanger

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"Data-Driven Thinking" is written by members of the media community and contains fresh ideas on the digital revolution in media. Today's column is written by Jared Belsky, president at 360i. Coming fresh off my latest trip to Palo Alto visiting with tech powerhouses and the C-suite of one of my favorite clients, I'm feeling energized, empowered and flush with ideas about where advertising is going. More importantly, though, I've gained some needed clarity around the industry's biggest misconceptions about the valley's two giants. In our industry, we tend to refer to and think of Facebook and Google as publishers.


Machine Learning Crash Course, Part I: Supervised Machine Learning IoT For All

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When you type'machine learning' into Google News, the first link you see is a Forbes Magazine piece called "What's The Difference Between Machine Learning And Artificial Intelligence?" This article contained so many flowery, grandiose descriptions about ML and AI technology that I couldn't help but laugh. With all the nonsense the media uses to describe machine learning (ML) and artificial intelligence (AI), it's time we do a deep dive into what these technologies actually do. First, we need to learn the difference between AI and ML. Fortunately, a fellow writer has already written an excellent explanation here.


AI Is Changing Marketing As We Know It, And That's A Good Thing

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Artificial intelligence (AI) seems to be the current business hot topic, including in marketing. It seems nearly impossible for any kind of marketing/advertising industry event or conference to not have at least one (or likely more!) session or panel discussion on the subject. Are we at "peak AI" or is this trend of great interest in the topic set to continue? The AI revolution in marketing, which I'll focus on in this post, has been spurred by the influx of affordable and accessible advanced data analytics tools (typically based on machine learning methods), the availability of increasingly rich (albeit still noisy) and extensive datasets, and a growing acceptance among marketers of the potential power of data-driven approaches to marketing decision making. The winds have been blowing in this direction for some time, so this is not a new phenomenon.


Artificial Intelligence in Marketing and Advertising - 5 Examples of Real Traction -

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In the hundreds of researcher and executive interviews we've been fortunate enough to conduct in the last three years, few artificial intelligence applications are brought up more than marketing and advertising. During talks with execs and researchers from companies ranging from Facebook to Baidu, and IBM to AT&T, marketing has been a perennial theme in conversations of AI's hottest applications. We'll begin with examples of what's currently viable in the AI marketing world: Below are seven extremely prevalent example applications that we've decided to highlight for this article, accompanied by a brief description of how the AI approach works, and companies currently leveraging the application. In this section of the article I've aimed to stay away from (a) applications with limited traction (speculative or burgeoning applications are reserved for the next section), and (b) AI applications that have only partial overlap with marketing today (IE: fraud and security could / should be considered to be their own category, and will not be referred to here as a marketing application). A complete list of currently viable AI marketing applications would be much more broad, but we've decided to focus on some of the most popular uses in marketing today: In 2005, if you "searched" an eCommerce store to find a product, you'd be unlikely to find the result you had in mind unless you knew it's name or title exactly.


There's a Lot More to AI Than Just Chatbots

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Whenever artificial intelligence (AI) is mentioned in a business context, the conversation inevitably turns to the subject of chatbots. Chatbots are great business tools, from an ecommerce standpoint. Those developed by Fluid and North Face, for instance, can be used to replicate in-store interactions, improving the online shopping experience and increasing the number of consumers who spend on your products and services online. Chatbots can be used to deliver better customer service, operate call centers and improve your brand-building: The Walk with Yeshi chabot created by the well-building nonprofit CharityWater earlier this year was an outstanding example of how chatbots can be used to build brand perception, awareness and sentiment. But, are chatbots the definitive example of how businesses can use AI?


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ZDNet

Google has made no secret of its overarching ambition to organise the world's information and make it accessible to anyone. And the healthcare industry has no shortage of such information, in any number of repositories and diverse formats, from MRI images to patient notes and data gathered from wearable devices. Google's DeepMind and the NHS: A glimpse of what AI means for the future of healthcare The Google subsidiary has struck a series of deals with organisations in the UK health service -- so what's really happening? Google has long sought to diversify its revenues streams away from search and advertising, the business it was founded on and which continues to make up the bulk of its revenue nearly 20 years later. So could health be the industry that helps the company to achieve that aim?


17.10.31 AI Is Changing Marketing As We Know It, And That's A Good Thing

#artificialintelligence

Artificial intelligence (AI) seems to be the current business hot topic, including in marketing. It seems nearly impossible for any kind of marketing/advertising industry event or conference to not have at least one (or likely more!) session or panel discussion on the subject. Are we at "peak AI" or is this trend of great interest in the topic set to continue? The AI revolution in marketing, which I'll focus on in this post, has been spurred by the influx of affordable and accessible advanced data analytics tools (typically based on machine learning methods), the availability of increasingly rich (albeit still noisy) and extensive datasets, and a growing acceptance among marketers of the potential power of data-driven approaches to marketing decision making. The winds have been blowing in this direction for some time, so this is not a new phenomenon.