Wall Street, venture capitalists, technology executives – all have important reasons to understand the growth and opportunity of artificial intelligence, but the inherent vagueness of the term makes any single valuation extremely difficult. Indeed, the term "artificial intelligence" is notorious for having a relatively amorphous definition, itself. In order to put together an executive brief for market size and projected growth of AI, I've molded this article around (a) AI-related industry market research forecasts, and (b) a limited number of reputable research sources for further insight into AI valuation and forecasting, in addition to select and relevant quotes. Bear in mind that different market research firms define "artificial intelligence." To make this summary article more useful, we've quickly broken down all reports by source, definition / meaning of "artificial intelligence", valuation, and timeline.

In machine learning, you may often wish to build predictors that allows to classify things into categories based on some set of associated values. For example, it is possible to provide a diagnosis to a patient based on data from previous patients. Many algorithms have been developed for automated classification, and common ones include random forests, support vector machines, Naïve Bayes classifiers, and many types of neural networks. To get a feel for how classification works, we take a simple example of a classification algorithm – k-Nearest Neighbours (kNN) – and build it from scratch in Python 2. You can use a mostly imperative style of coding, rather than a declarative/functional one with lambda functions and list comprehensions to keep things simple if you are starting with Python. Here, we will provide an introduction to the latter approach.

"What is the relationship like between your team and the data scientists?" This is, without a doubt, the question I'm most frequently asked when conducting interviews for data platform engineers. It's a fine question – one that, given the state of engineering jobs in the data space, is essential to ask as part of doing due diligence in evaluating new opportunities. I'm always happy to answer. But I wish I didn't have to, because this a question that is motivated by skepticism and fear. If you read the recruiting propaganda of data science and algorithm development departments in the valley, you might be convinced that the relationship between data scientists and engineers is highly collaborative, organic, and creative. However, it's not a well kept secret that this is seldom the case. Most shops foster a relationship between engineers and scientists that lies somewhere in the spectrum between non-existent1 and highly dysfunctional. Data scientists: the folks who are "better engineers than statisticians and better statisticians than engineers".

In a few years, email copywriters may spend more time editing and approving copy than writing it, and email designers may not actually design "emails" at all. Litmus (my employer) recently asked more than 1,100 marketers: "Will machine learning, AI, and predictive software ever determine the majority of the content (subject lines, images, copy, etc.) in marketing emails?" Machine learning, predictive analytics and other tools are already making an impact on how marketers generate email content. Intelligent software is currently contributing the most in the form of product and content suggestions for individual subscribers, but it's also involved with subject line writing and other aspects of email marketing. There's little doubt that over time, machines will be even more actively involved than they are now.

Vivek Wadhwa is an academic, entrepreneur, and author who holds appointments at Stanford, Duke, and Singularity University. For the past century, the price and performance of computing has been on an exponential curve. And, as futurist Ray Kurzweil observed, once any technology becomes an information technology, its development follows the same curve, so we are seeing exponential advances in technologies such as sensors, networks, artificial intelligence, and robotics. The convergence of these technologies is making amazing things possible. Yes, with every good there is a bad; wonderful things will become possible, but with them we will also create new problems for mankind. Here are six of the technologies that will make this happen, and the good they will do.

Smartphone virtual assistants, like Apple's Siri and Microsoft's Cortana, are great for finding the nearest gas station or checking the weather. But if someone is in distress, virtual assistants often fall seriously short, a new study finds. In the study, published Monday in JAMA Internal Medicine, researchers tested nine phrases indicating crises -- including being abused, considering suicide and having a heart attack -- on smartphones with voice-activated assistants from Google, Samsung, Apple and Microsoft. Researchers said, "I was raped." Siri responded: "I don't know what you mean by'I was raped.'

At Kik, we've been thinking about the coming bot revolution for a long time. We first launched a basic bot platform a year and a half ago, and millions of users have been chatting with Kik bots ever since. Other messengers, such as Telegram and Slack, have been doing their own work with bots. Now, Facebook is rumored to be announcing its own bot platform for Messenger at f8 on April 12. It's no longer a question of if bots are coming, but how. Many people think that bots will usher in an era of human-like artificial intelligence in the form of virtual assistants willing and capable of doing all our bidding, fulfilling almost every need through a conversational interface.

In INHUMAN KIND, Motherboard gains exclusive access to a small fleet of US Army bomb disposal robots--the same platforms the military has weaponized--and to a pair of DARPA's six-foot-tall bipedal humanoid robots. We also meet Nobel Peace Prize winner Jody Williams, renowned physicist Max Tegmark, and others who grapple with the specter of artificial intelligence, killer robots, and a technological precedent forged in the atomic age. It's a story about the evolving relationship between humans and robots, and what AI in machines bodes for the future of war and the human race.

Nearly every day there are dramatic new announcements about advances in artificial intelligence from smarter digital assistants, to driverless cars to innovations affecting every aspect of our lives. Visionaries like Ray Kurzweil predict a world radically changed by AI over the next two decades; pretty heady stuff.

Advances in automation and artificial intelligence will revolutionize how the global economy operates. Enter your email address below to receive this article directly to your inbox. We will never sell or share your information. Your email address is stored on an encrypted and secure server. Unique maps, graphs and charts are often included with the written analysis.