Dawn of the Sexbots: Is new TV show Westworld's future where tourists romance robots just a sick fantasy? Colin Morgan played Leo (right) in Channel 4's popular drama Humans, which returns on Sunday night The views expressed in the contents above are those of our users and do not necessarily reflect the views of MailOnline. By posting your comment you agree to our house rules.

Days after Apple announced the death of the function keys and the traditional USB port on the MacBook Pro, its been discovered that the machine meant the end of another iconic piece of technology. Apple ditched the startup chime in the new MacBook Pros since they automatically boot up when the lid is opened. The MacBook will also be available in a cheaper option with traditional function keys, Phil Schiller revealed. Apple has also slimmed down the new MacBook - so much so it is killing off the MacBook Air. The F-sharp sound was also used in the 2008 Pixar film Wall-E (pictured), when the animated robot used solar panels to charge itself.

People listen to the radio as the results of the presidential elections are announced in Kireka, Uganda, in February. Many rural Ugandans don't have Internet access, and the radio is a central source of news -- and platform for citizens' opinions. People listen to the radio as the results of the presidential elections are announced in Kireka, Uganda, in February. Many rural Ugandans don't have Internet access, and the radio is a central source of news -- and platform for citizens' opinions. Its omnipresence can make it easy to forget that making this technology has been really, really hard.

I sat down this week with tech columnists Fowler and Stern at the Wall Street Journal D Live conference here for an extended #TalkingTech podcast. What happens when 3 tech columnists get together? They talk gadgets and tech--or more specifically, our three highlights so far, for 2016. So with new MacBooks, Surface computers, Google Home and expected new entries from Amazon set to be released in the coming months, we look back at the previous 10 months of tech. Fowler loves the Eero, the router add-on to bring better wifi throughout the house, while Stern has fallen in love with dongles, those little doo-dads that connect devices back to devices after slots disappear.

The use of recommender systems has exploded over the last decade, making personalized recommendations ubiquitous online. Most of the major companies, including Google, Facebook, Twitter, LinkedIn, Netflix, Amazon, Microsoft, Yahoo!, eBay, Pandora, Spotify, and many others use recommender systems (RS) within their services. These systems are used to recommend a whole range of items, including consumer products, movies, songs, friends, news articles, restaurants and various others. Recommender systems constitute a mission-critical technology in several companies. For example, Netflix reports that at least 75% of its downloads and rentals come from their RS, thus making it of strategic importance to the company.a

I'd known about Warm Focus (the concept) from a series of playlists that Ewing made a few years ago, on the late and beloved streaming service Rdio. But Warm Focus (the radio show) was even better than those, because every so often Ewing would turn the music down, ask how the work was going, and remind you it was okay to take a walk. Not even Siri does that. I found this upbeat, elated song--which aurally falls somewhere between Steve Reich and I Am Robot and Proud--through Ewing's show, and he played it on his last episode. I think it's a good way to end the week or start the next one.

This is the continuation of my mini-series on sentiment analysis of movie reviews, which originally appeared on recurrentnull.wordpress.com. Last time, we had a look at how well classical bag-of-words models worked for classification of the Stanford collection of IMDB reviews. As it turned out, the "winner" was Logistic Regression, using both unigrams and bigrams for classification. The best classification accuracy obtained was .89 So, bag-of-words models may be surprisingly successful, but they are limited in what they can do.

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.

Frankfurt, Germany October 17, 2016 – Aries Systems Corporation today announces the integration of Meta Bibliometric Intelligence into Editorial Manager, Aries' industry-leading manuscript and peer-review tracking system for scholarly publications. The new technology, created by Meta, applies artificial intelligence toward the identification of high-impact manuscripts at the moment of first submission, allowing editors to triage and rank incoming manuscripts. "By incorporating Meta Bibliometric Intelligence into Editorial Manager, we're the first workflow system that helps publishers explore the potential of big data analysis during peer review," said Richard Wynne, Vice President of Sales and Marketing at Aries Systems. Bibliometric Intelligence uses sophisticated machine learning algorithms that were trained using Meta's corpus of millions of full-text articles – a collection that now comprises the largest scholarly text-mining collection on Earth. As newly-submitted manuscripts are processed, hundreds of unique features are pulled from the papers and fed through the algorithms.

All that money is providing Google with more financial firepower to buy the rights to stream cable networks' shows on YouTube, too, something likely to reel in even more viewers. It also is helping to finance Alphabet's investments in far-flung projects ranging from self-driving cars to internet-beaming balloons. That segment, known as "Other Bets," lost $865 million during the July-September period, narrowing from a $980 million setback last year as Alphabet imposed more expense controls.