CyberGuy shows you how to create and customize events in the calendar app. We all have a ton going on in our lives, and I know that I would never be able to keep all my events and appointments in order without the help of technology. Some of you might use desk calendars to have all your appointments written down, however, even those can quickly fill up. Try using a calendar app on your smartphone by following these easy steps. CLICK TO GET KURT'S CYBERGUY NEWSLETTER WITH QUICK TIPS, TECH REVIEWS, SECURITY ALERTS AND EASY HOW-TO'S TO MAKE YOU SMARTER Not only is it easy to add an event to your iPhone calendar, you can also set reminders for the event, giving it a color code, inviting people, and more.

As I write this, Amazon is announcing its purchase of iRobot, adding its room-mapping robotic vacuum technology to the company's existing home surveillance suite, the Ring doorbell and prototype aerial drone. This is in addition to Amazon already knowing what you order online, what websites you visit, what foods you eat and, soon, every last scrap of personal medical data you possess. The trend of our gadgets and infrastructure constantly, often invasively, monitoring their users shows little sign of slowing -- not when there's so much money to be made. Of course it hasn't been all bad for humanity, what with AI's help in advancing medical, communications and logistics tech in recent years. In his new book, Machines Behaving Badly: The Morality of AI, Scientia Professor of Artificial Intelligence at the University of New South Wales, Dr. Toby Walsh, explores the duality of potential that artificial intelligence/machine learning systems offer and, in the excerpt below, how to claw back a bit of your privacy from an industry built for omniscience. Published by La Trobe University Press. The Second Law of Thermodynamics states that the total entropy of a system – the amount of disorder – only ever increases.

If companies are changing to exploit the potential of digital business, can the leader's figure ever remain anchored to old practices? The cultural transformation underway necessarily requires an adjustment of professional figures and corporate roles to the new business models and visions. Abandoning the beliefs that worked in the past means using an approach that is more in line with the new goals of Digital Transformation. Let's see what aspects the digital leader will need to work on. We imagine a charismatic man or woman mass dragger when we hear the word leader. A kind of hero who can be trusted to achieve a goal.

If companies are changing to exploit the potential of digital business, can the leader's figure ever remain anchored to old practices? The cultural transformation underway necessarily requires an adjustment of professional figures and corporate roles to the new business models and visions. Abandoning the beliefs that worked in the past means using an approach that is more in line with the new goals of Digital Transformation. Let's see what aspects the digital leader will need to work on. We imagine a charismatic man or woman mass dragger when we hear the word leader.

Is this real or did artificial intelligence create this episode? This week an article came out about Artificial Intelligence aka AI used all of Nirvana's songs to create a new Nirvana song. The scientists feed all of Nirvana's songs into an algorithm (first they converted all of the songs to MIDI (Musical Instrument Digital Interface) and then the computer created music that sounded like Nirvana. Then they followed suit with the lyrics. Between them both they created a "new" Nirvana song.

Since NLP is a subfield of Linguistics, many key terminologies from Linguistics have been adopted in the field. The word corpus translated to Latin means body. The body constitutes the physical structure which includes bones, flesh, and organs of a person or animal, therefore we can say the body is made up of a collection of other parts. In the same way, we say a corpus is a collection of other parts, but the other parts in this respect are other documents. For example, you may have corpora (plural of corpus) made up of different religious books where each book would be referred to as a document and the collection of books is the corpus.

If you've heard of validation in the context of machine learning (ML) and AI but you're not quite sure what all the fuss is all about -- validation is only one of the most important applied AI concepts ever, no big deal -- then here's the analogy you've been waiting for. Imagine that Mr. Bean is about to take his first calculus exam… Mr. Bean unearths the single equation he squirreled away and begins studying it for tomorrow's exam. He's got no other examples (datapoints) or resources to help him along and he didn't bother to write down any explicit rules explaining how calculus works, so all he can try doing is search for patterns in his equation: Just like an AI algorithm, his goal is to find a data pattern that he can turn into a recipe ("model") that successfully takes him from the input on the left of the " " to the output on the right-hand side. That is precisely what goes on during the training and tuning steps of an applied AI project (steps 6–7 in my step-by-step guide). Training is all about making a recipe out of patterns in the available examples.

If you've heard of validation in the context of machine learning (ML) and AI but you're not quite sure what all the fuss is all about -- validation is only one of the most important applied AI concepts ever, no big deal -- then here's the analogy you've been waiting for. Imagine that Mr. Bean is about to take his first calculus exam… Mr. Bean unearths the single equation he squirreled away and begins studying it for tomorrow's exam. He's got no other examples (datapoints) or resources to help him along and he didn't bother to write down any explicit rules explaining how calculus works, so all he can try doing is search for patterns in his equation: Just like an AI algorithm, his goal is to find a data pattern that he can turn into a recipe ("model") that successfully takes him from the input on the left of the " " to the output on the right-hand side. That is precisely what goes on during the training and tuning steps of an applied AI project (steps 6–7 in my step-by-step guide). Training is all about making a recipe out of patterns in the available examples.

Data Science is considered as one of the most modern and fascinating jobs of our time. It can be funny and can give you satisfaction, but is it really as it's described? At the beginning of their career, Data Scientists think that Data Science is a wonderful, magical world full of algorithms, Python functions that performs every possible spell with a line of code and statistical models able to detect the most useful correlations among data that could make you an invincible superhero in your company. You start dreaming about your CEO congratulating with you and shaking your hand, you begin to see decision trees and clusters everywhere and, of course, the most terrifying neural network architectures your mind can dream. But since the very first day of your first Data Science project, you start to realize what reality is.

Data Science is considered as one of the most modern and fascinating jobs of our time. It can be funny and can give you satisfaction, but is it really as it's described? At the beginning of their career, Data Scientists think that Data Science is a wonderful, magical world full of algorithms, Python functions that performs every possible spell with a line of code and statistical models able to detect the most useful correlations among data that could make you an invincible superhero in your company. You start dreaming about your CEO congratulating with you and shaking your hand, you begin to see decision trees and clusters everywhere and, of course, the most terrifying neural network architectures your mind can dream. But since the very first day of your first Data Science project, you start to realize what reality is.