The new MacBook Pro was always going to be expensive. But it is very expensive indeed in the UK, after the prices were shifted because of the falling pound. The computers are as much as £500 more expensive than previous models, because of a combination of the currency changes and the upgrades introduced by Apple. Buying the cheapest version of the MacBook Pro with Touch Bar that was released yesterday will cost customers £1,749. Customers can spend as much as £2,699 on stock models of the computer, if they buy the 15-inch version.

The New York businessman with a penchant for celebrity television may suddenly find himself in love with artificial intelligence developed in India. The polls and simulations that involve the skills and insight of human beings suggest Donald Trump could be heading for something of a pasting. But an artificial intelligence (AI) system developed in Mumbai, and which correctly predicted the last three US presidential elections, puts the Republican nominee ahead of his rival Hillary Clinton in the battle to secure the keys to the White House. MogIA was developed by Sanjiv Rai, the founder of Indian start-up Genic.ai. It has taken 20 million data points from public platforms such as Google, Facebook and Twitter and analysed the information to create predictions, CNBC reported.

European privacy experts have sent letters to WhatsApp telling it to stop sharing people's data with Facebook. WhatsApp announced in recent weeks that it would start handing over information about the people who use it to Facebook, so that its parent company could use that data to better target ads. But the company didn't give a very easy way of opting out of it, and the deal has drawn the attention of customers and regulators. Now EU privacy watchdogs have told WhatsApp and Facebook that the deal must be stopped until it can be checked whether it is legal or not. Presumably if the deal is found to be illegal then it will be forced to stop.

Adult website Pornhub says that it can save Vine, the video sharing company, by buying it. The company has sent an official letter to Jack Dorsey, the CEO of Vine's owner Twitter, offering to buy the company. In doing so it hopes to help avoid it being shut down entirely, as Twitter and Vine have announced it will do. The company does make clear that the site would turn into a porn site. The letter sent to Mr Dorsey by Pornhub CEO Corey Price says that Vine would be restored "back to its NSFW glory".

Apple has launched its latest products in its headquarters in Cupertino, California. In the 24 hours since, I've been trying out the new MacBook Pro for size. First of all, I should point out that this is the entry-level MacBook Pro, not the more expensive MacBook Pro with TouchBar. TouchBar is the ground-breaking innovation where the top row of function keys is replaced with a long, touch-sensitive display strip. I tried this briefly and it's frankly pretty amazing. But I'll be reviewing that and the sapphire-crystal power and Touch ID button also found on the MacBook Pro with TouchBar in due course.

Companies have been trying to drum up enthusiasm for them for years, with little success. Pepper, a humanoid machine carrying the hopes of SoftBank Group Corp.'s billionaire founder Masayoshi Son, was supposed to change that. Promoted as the first robot to be endowed with emotions, the company marketed Pepper aggressively after it was unveiled in 2014, promising the gadget was sophisticated enough for tasks usually handled by shop clerks, receptionists and translators. "It's not there to have a conversation," said Junichi Nishi, a municipal official in Fujieda, Shizuoka Prefecture, a city of about 140,000. "We use it primarily as a tablet," he said, referring to the touch screen attached to the robot's chest.

If you're inclined to think of cybersecurity as lending itself to clean, elegant, better-than-human, extremely secure solutions, you probably don't work in the field. But one bias held by many in information security is that much of the mess is because humans -- not hackers, shoddy software or poorly-built devices -- are the source of the vast majority of our digital vulnerabilities. Why extend the time and energy to hack into a heavily-guarded system, security experts might opine, if you can simply trick a user into clicking a link laden with malware? If businesses didn't have to deal with the "end user" (that is, you and I), this reasoning goes, all our problems would be solved. This represents a quiet bias against users in nearly every conversation about cybersecurity.

In the first part of this series we set the context for Random Forest algorithm by introducing the tree based algorithm for classification problems. In this post we will look at some of the limitations of the tree based model and how they were overcome paving the way to a powerful model – Random Forest. Two major methods that were employed to overcome those pitfalls are Bootstrapping and Bagging. We will discuss them first before delving into random forest. When we discussed the tree based model we saw that such models are very intuitive i.e. they are easy to interpret.

According to Business Insider, 10 million self-driving cars are expected to hit the road by 2020. For many, the prospect of taking trips with unmanned vehicles may seem akin to magic, but the capability is actually the result of machine learning, a form of artificial intelligence that uses algorithms designed to learn from and respond according to the data it receives. In the transportation industry, machine learning is the driving force behind many burgeoning technological advances. On Wednesday, October 26, industry and academic experts gathered in Northwestern's McCormick Auditorium for "Machine Learning in Transportation," a technical workshop hosted by the Northwestern University Transportation Center and Northwestern's Center for the Commercialization of Innovative Transportation Technology that featured speakers from Northwestern, BMW, IBM, and more. "Machine learning allows us to tackle tasks that are too difficult to solve with fixed programs written and designed by human beings," said Aggelos Katsaggelos, Joseph Cummings Professor of Electrical Engineering and Computer Science at the McCormick School of Engineering.

It is no doubt that the sub-field of machine learning / artificial intelligence has increasingly gained more popularity in the past couple of years. As Big Data is the hottest trend in the tech industry at the moment, machine learning is incredibly powerful to make predictions or calculated suggestions based on large amounts of data. Some of the most common examples of machine learning are Netflix's algorithms to make movie suggestions based on movies you have watched in the past or Amazon's algorithms that recommend books based on books you have bought before. So if you want to learn more about machine learning, how do you start? For me, my first introduction is when I took an Artificial Intelligence class when I was studying abroad in Copenhagen.