You can solve that optimisation problem using both gradient descent and as a closed-form solution, although for really big datasets it is preferable to use the former since calculating the inverse would be really computationally costly.

In the latest twist of events, Apple Inc. (NASDAQ:AAPL) has joined some of its biggest rivals like Microsoft, Google and Amazon to support a newly formed artificial intelligence partnership agreement. Interestingly, this AI agreement has been designed to serve as a non-profit basis. Tech giants are all well aware of the potential threat from artificial intelligence development, which is why such companies have founded such a group. On Friday, this particular partnership confirmed that Apple has officially joined its efforts to protect humanity against any potential risk from artificial intelligence software. Interestingly, Tom Gruber, Apple's leading head for developments regarding Siri, confirmed that he has officially been inducted in the board for this mentioned partnership.

Two summers ago, Magna International Inc. and Royal Bank of Canada brought together some of Canada's brightest entrepreneurs and innovators to brainstorm what Canada needs to foster the development of emerging technologies and tech companies. Fast forward to today and we are on the cusp of the next great technological revolution, driven by artificial intelligence (AI). The term may conjure up visions of science-fiction movies with apocalyptic outcomes, but the reality is we are already living in a world infused with AI, from music and movie recommendation services, to driver assistance systems in cars, to virtual personal assistants in our phone or in our home. Over the past few years, the pace of technological innovation and exploration of AI has increased exponentially, with futuristic ideas such as self-driving cars becoming tangible products of today. At the recently concluded World Economic Forum in Davos, Switzerland, one of the major themes centred on AI as the Fourth Industrial Revolution.

Artificial intelligence (AI) is all the buzz this year. According to CB Insights, as of June 15, this year, more than 200 AI venture financing deals have been completed already totaling $1.5B in dollar volume. If the latter half of the year continues at this pace, 2016 will be a record year. Based on analysis by CB Insights, most of the deals being done are at a series B or C stage, indicating that startups in this space are beginning to see success. AI, as most people now know, has several applications in health technologies, marketing & sales, business analysis and financial services.

This article has been updated as of September 30, 2016 to reflect new research and industry progress in the artificial intelligence market. Wall Street, venture capitalists, technology executives – all have important reasons to understand the growth and opportunity in 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" according to varying criteria.

Artificial intelligence startups raised $5.02 billion worldwide in 2016 to hit a five-year high, as application of the technology expands from online services and finance to such far-ranging fields as agriculture. This trend is likely to continue through 2017, as investors scout out promising technologies and talent. AI-related startup funding rounds totaled 658 last year, up from 493 rounds in 2015, when funding reached $3.12 billion, according to U.S.-based research firm CB Insights. So-called mega-rounds are also increasing. For example, Texas-based StackPath, a startup offering AI-based cybersecurity services, took in $180 million.

If you've ever left a poker table penniless, you definitely don't want to go up against Libratus. Built by a computer science professor and a graduate student, the artificial intelligence system is handily beating pro poker players in a Texas hold'em tournament in Pittsburgh. Two weeks into the 20-day heads up (or one-on-one), no-limit tournament, Libratus is up by more than a million dollars on its human counterparts. The A.I. system was designed by Tuomas Sandholm, a professor at Carnegie Mellon, and his student, Noam Brown. A.I. systems have already wiped the floor with humans at a number of games.

Artificial Intelligence has another champion and watchdog. Four months after its formation, the Partnership on AI, a group dedicated to tackling AI opportunities and challenges finally, officially welcomed Apple as a member. Tom Gruber, Apple's head of advanced development for Apple's digital assistant, Siri, joined the Partnership on AI's board of Trustees on Friday. Gruber joins science, research and AI leaders from a disparate group of companies including Google, Amazon, Microsoft, IBM and DeepMind (part of Google), along with leaders from the ACLU, UC Berkeley and the Association for the Advancement of AI. "We're glad to see the industry engaging on some of the larger opportunities and concerns created with the advance of machine learning and AI. We believe it's beneficial to Apple, our customers, and the industry to play an active role in its development and look forward to collaborating with the group to help drive discussion on how to advance AI while protecting the privacy and security of consumers." said Gruber on the Partnership on AI site.

Today's guest blogger, Toshi Takeuchi used machine learning on a job-related dataset for predictive analytics. Let's see what he learned. Companies spend money and time recruiting talent and they lose all that investment when people leave. Therefore companies can save money if they can intervene before their employees leave. Perhaps this is a sign of a robust economy, that one of the datasets popular on Kaggle deals with this issue: Human Resources Analytics - Why are our best and most experienced employees leaving prematurely?

Machine learning as a subset of Artificial Intelligence is an emerging trend in South Africa, with demand for data scientists rising sharply and university programmes incorporating the discipline in study programmes. The machine learning sector is really beginning to take form in South Africa with various start-ups taking off and entering the international scene. At DataProphet, we specialise in the application of machine learning algorithms to provide actionable solutions for a variety of industries. Having built a presence in the U.S. we have experienced the difference in industry trends first hand. South Africa's diverse range of spoken languages makes it difficult to use existing personal assistants, chatbots and speech recognition tools which were designed solely for the English language.