The following is an edited, updated version of an article originally written for IEEE Spectrum. I'm 62, with all that entails. I still play a mean game of hockey, but entropy looms ever larger. So part of me wants very much to believe that we are rapidly approaching "The Singularity." Like heaven, the Singularity comes in many versions, but most involve bionic brain boosting.

In many ways, our current inability to replicate our own brains is not a particularly large concern. For driverless cars, for example, the aim is to create a system that combines pure logical processes with ethical judgements and a protective mentality. Google's self-driving car project proved this in February, when one of its vehicles was responsible for causing a low-speed crash. The error was a typically human one -- assuming that a bus would slow and let it pull out past some sand bags -- and Google's response is to teach the system through deep learning processes that certain vehicles will be less likely to slow down for it.

Sometimes, the field of artificial intelligence looks pretty ridiculous, like when Microsoft's teen chatbot was tricked by online trolls to say racist and sexist things. Consider how it's affecting our working world. Jen-Hsun Huang, the CEO of computer graphics hardware company Nvidia, can see this clearly. For a long time, gamers have loved Nvidia for the company's graphics processors (GPUs) that have the ability to gorgeously render insanely violent games. Here's the twist: Nvidia's GPUs also happen to be excellent for deep learning, an AI technique that allows algorithms to recognize patterns and become more adept at finding them over time.

Long before we kneel to our robot overlords, AI tools will help schedule meetings and perform research for busy business professionals. Sustaining a positive work-life balance has become increasingly more challenging in today's technology-driven business environment. Automation technology thrives in environments traditionally considered laborious and time consuming – time better spent on tasks that make money, instead of wasting it. Time spent manually entering tasks, calendar items, and typing up emails on smartphones, in particular for those of you, like myself, blessed with sausage fingers, quickly became more hassle than it was worth. This process became especially irritating for business pros that are constantly on the move and rely, almost exclusively, on the features and functionality of their smart devices.

The Science and Technology Committee is undertaking an inquiry into robotics and artificial intelligence. Robotics and Autonomous Systems (RAS) is one of the'Eight Great Technologies' identified by the UK Government in 2012. A national strategy for RAS innovation from a'RAS Special Interest Group' was published by Innovate UK in 2014. The Government responded to that strategy in March 2015 (PDF 405 KB) and agreed to establish a RAS Leadership Council to oversee its execution. The Special Interest Group also published The UK Landscape for Robotics and Autonomous Systems in 2015.

Machine learning, the act of computers learning without being explicitly programmed,has typically been thought of as magic that only mathematicians and programmers could perform. That has been the case for a while and that is due to several reasons. Not only do you need to be able to write code, but you need to have strong math skills. There is no way around it, but you can still do a lot of meaningful work if you don't have the full math background. I believe we are on a path where everyone who programs now will be building some form of machine learning models in the future.

It was end of last year, I decided to research upon Machine learning (ML) and have been taking few little steps. I need to understand what it's all about ML and related hype factor that it has created in the technology industry. Few articles suggested that I should have good understanding of basic Mathematics, Statistics and few suggested that I need to be good in domain knowledge etc. etc. Most of the basic algorithms or ML Techniques has been there for many years but it has gained lot of momentum now. We see the modern systems have good computing power to execute ML at ease and also due to exponential data growth every year (Lot of data are available to us) which encourages us to build systems that could deliver better insights real-time.

A company that helps users to create their own websites now knows what kind of sites their 80 million users are building without pestering them with repeated questions. Wix, a Tel Aviv-based Web development company, is using machine learning on Google's cloud platform to learn more about its users so it can help them find the images they need to build interesting and useful websites. That's just the beginning of how machine learning will be used in the cloud, according to industry analysts who say machine learning will be the biggest thing that's ever hit the cloud. David Zuckerman, head of developer experience for Wix, said machine learning in the cloud will be a boon to companies that don't have a major research division. "The cloud has brought this technology to everyone," he said.

Machine learning algorithms can warn investors when a particular stock is going to fall by predicting likely instances of insider trading (when information that's not in the public domain is capitalised upon by people in the know). This can be done by analysing previous occasions when company insiders did apparently well-timed trades in their own stocks, and recognising these patterns. This might seem deceptively simple, but it isn't, explains Tom Doris, CEO of OTAS Technologies, a London-based market analytics and machine learning trading system. While company executives are required to file details of transactions in their company's stock, most insider trades are few and far between: a needle in a haystack. Doris told IBTimes UK: "We look at all of the insiders, the directors of companies, and we see all of their historical transactions in their own stock. If you are the chief financial officer of Vodafone, any time you buy or sell Vodafone stock, you're obliged under regulation to file details of those transactions. So that would include the amount that you bought or sold, when you did it and what price you got and the reason, if any, for the transaction. There is an enormous database of all of these transactions for all of the world's listed stocks and we go and we basically back-test all of the insiders and we find the ones that are apparently good at timing their own stocks."

Tay inexplicably added the "repeat after me" phrase to the parroted content on at least some tweets, implying that users should repeat what the chatbot said.Quickly realizing its teenage bot had been radicalized into a genocidal, Nazi-loving, Donald Trump supporter, Microsoft shut Tay down. According to Tay's "about" page linked to the Twitter profile, "Tay is an artificial intelligent chat bot developed by Microsoft's Technology and Research and Bing teams to experiment with and conduct research on conversational understanding". Unfortunately, Microsoft continues, within the first 24 hours of coming online, they became aware of a coordinated effort by some users to abuse Tay's commenting skills to have it respond in inappropriate ways. Apple Temporarily Pulls iOS 9.3 Update for Older iOS Devices It will then click on "All my devices" and select the device before clicking "Delete Account" and restart the terminal again. The video below (and its comments) will give you some idea about what to expect if you're coming from iOS 8 to iOS 9.3.