The Bank of England's chief economist, Andy Haldane, has warned that artificial intelligence and machines have the potential to make a huge number of jobs obsolete, with thousands of UK workers facing unemployment due to new technology. Mr Haldane told the BBC that the "Fourth Industrial Revolution" would be on a "much greater scale" than the previous three, and said the UK will need a skills revolution to avoid unemployment on a mass scale. He said that previous industrial revolutions had "a wrenching and lengthy impact on the jobs market, on the lives and livelihoods of large swathes of society". "Jobs were effectively taken by machines of various types, there was a hollowing out of the jobs market, and that left a lot of people for a lengthy period out of work and struggling to make a living," he said. "That heightened social tensions, it heightened financial tensions, it led to a rise in inequality. This is the dark side of technological revolutions and that dark side has always been there."

Hong Kong has a very special place in our hearts. It's the safest place on the planet, with beautiful local people who are shy and endearing, who harbor a fondness for taking pictures of their food, who believe in ghosts, who despise "those uncouth mainlanders", and who invent some strange cartoon characters – like McDull the pig and his friend Excreman that's literally a turd that crawled out of the toilet. If you're someone who noticeably speaks English, don't expect the Hong Kong police to ticket you for jaywalking. They're too shy about their English to approach you. Of course these are the same people who won't hesitate to tell you that you look fat when you return from holiday.

During the 2016 U.S. presidential election, inaccurate and misleading articles burned through social networks. Since then, tech companies--from behemoths like Facebook and Google to scrappy startups--have built tools to fight misinformation (including what many call "fake news," though that term is highly politicized). Most companies have turned to artificial intelligence (AI) in hopes that fast and automated computer systems can deal with a problem that's seemingly as big as the Internet. "They're all using AI because they need to scale," says Claire Wardle, who leads the misinformation-fighting project First Draft, based in Harvard University's John F. Kennedy School of Government. AI can speed up time-consuming steps, she says, such as going through the vast amount of content published online every day and flagging material that might be false.

Since dinosaurs went extinct 66 million years ago, we've never experienced them as living, breathing animals. We can look at their bones in a museum, or we can watch recreations of them in films like this summer's Jurassic World: Fallen Kingdom. But both those options lack that visceral feel you get from seeing a real creature in a zoo. Though it's unlikely you'll ever live long enough to see a dinosaur in the flesh, you can still pretend to have one as a pet, thanks to Mattel's new Alpha Training Blue robot. She roars, coos and even responds to your commands like her movie inspiration -- but is far less deadly.

Samsung has taken the wraps off a range of new televisions powered by AI that promise to provide pictures with greater clarity than ever. The whopping 65" to 85" screens in the new QLED 900R range are capable of displaying images in 8K resolution – the next frontier in ultra high definition viewing. This newest resolution has four times as many pixels vertically and horizontally as current top-end 4K Ultra HD screens, and 16 times more than standard 1080p HD. Samsung is using Artificial Intelligence (AI) to'upgrade' the quality of any video content viewed on the screen, including older television shows, and movies. The AI analyses the low-resolution content – checking the pixel location, colour, shape of 33 million pixels inside the frame – to detect objects it recognises.

Google's big, premium Apple HomePod rival the Home Max is finally being released in the UK today, bringing Google Assistant to the high-end smart speaker market. Announced in October 2017 and on sale in the US since November, the Home Max joins Google's smaller Home and smallest Home Mini smart speakers as the big one. Google Assistant sorts voice commands, controls and questions exactly the same as Google's smaller smart speaker offerings, but the way it sounds couldn't be more different. The Home Max is relatively large box speaker, by smart speaker standards, with a white or black smooth plastic body and grey or charcoal coloured fabric front. In white and grey it's simple fabric front and rounded corners make the Home Max look a bit bland up next to a Sonos Play:5 or an Apple HomePod, but it might be easier to blend in with soft home furnishings.

The man who hacked into hundreds of iCloud accounts of Hollywood stars and others before leaking their nude photos across the internet has been sentenced. Connecticut man George Garafano became infamous when he stole private photos from people including Jennifer Lawrence and made them available across the internet. He was sentenced to eight months in prison this week, in federal court in Bridgeport. After prison, he must serve three years of supervised release and perform 60 hours of community service. The I.F.O. is fuelled by eight electric engines, which is able to push the flying object to an estimated top speed of about 120mph.

Nowadays we hear very often the words "Recommender systems" and mainly it's because they are quite often used by companies for different purposes, such as to increase sales (items' suggestion while purchasing Amazon: user that have bought this as also bought this) or in suggestions to customers to give them a better customer experience (film suggestion Netflix) or also in advertising to target the right people based on preferences similarities. The recommender systems are basically systems that can recommend things to people based on what everybody else did. Here there is an example of film suggestion taken from an online course. I want to thank Frank Kane for this very useful course on Data Science and Machine Learning with Python. Here there is the course's link in case you would like to go deeper with Data Science.

Before long, machine learning will be as omnipresent in our lives as the internet. Like the internet, it will improve every industry and every business. Our grandchildren won't even know they are using it, and they probably will never appreciate how much it has simplified their lives. The companies that apply this machine learning technology to business problems correctly will transform their organizations by achieving business impact. Business impact is defined by increasing revenue and/or decreasing cost.

Convolutional Neural Networks (CNNs) models have been recently introduced in the domain of top-$N$ session-based recommendations. An ordered collection of past items the user has interacted with in a session (or sequence) are embedded into a 2-dimensional latent matrix, and treated as an image. The convolution and pooling operations are then applied to the mapped item embeddings. In this paper, we first examine the typical session-based CNN recommender and show that both the generative model and network architecture are suboptimal when modeling long-range dependencies in the item sequence. To address the issues, we propose a simple, but very effective generative model that is capable of learning high-level representation from both short- and long-range dependencies. The network architecture of the proposed model is formed of a stack of holed convolutional layers, which can efficiently increase the receptive fields without relying on the pooling operation. Another contribution is the effective use of residual block structure in recommender systems, which can ease the optimization for much deeper networks. The proposed generative model attains state-of-the-art accuracy with less training time in the session-based recommendation task. It accordingly can be used as a powerful session-based recommendation baseline to beat in future, especially when there are long sequences of user feedback.