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.

A Justice Ministry statement said Wednesday that after an almost yearlong investigation the State Attorney's office summoned top Aeronautics Ltd. officials, including its chief executive, for a hearing pending indictment.

Among the scant books in my tiny rented room in San Francisco, I've kept a spine-worn copy of Romeo and Juliet. It's the one I read in my high school English class, the pages yellowed, the margins filled with scribbled notes. Since the play was written in the 1590s, Shakespeare's portrayal of the nature of love--irrational, all-consuming--has been told and retold in countless movie adaptations. I hold onto the book to revisit those insights, and also because I'm prone to nostalgic literary tendencies like keeping old books. I am also a personal tech writer in 2018. It's my job to keep tabs on how our rapidly shifting technology is shaping not only how we communicate, but how we empathize, trust, show affection.

What keeps Jamie Dimon up at night? JPMorgan Chase just made another hire that proves it's serious about artificial intelligence. Apoorv Saxena, a Google executive in charge of cloud-based AI products, joins the bank later this week as head of artificial intelligence and machine learning services. The role also places him in charge of asset and wealth management artificial intelligence technology, according to an internal memo seen by CNNMoney. Saxena, who will work in Palo Alto, is the company's second high-profile AI hire in recent months.