We trust you've had a suitably enjoyable week, especially those in the UK enjoying the hot weather. Let's journey back and look at some of the digital marketing stats you might have missed. The roundup includes news about GDPR, personalisation, AI, and lots more. As always, be sure to check out the Internet Statistics Compendium for further facts and figures. When it comes to digital experiences, personalisation is way down on the list of things consumers care about.

This tutorial is an excerpt from "Deep Learning Essentials" by Wei Di, Anurag Bhardwaj, Jianing Wei and published by Packt. Use the code ORKDNA10 at checkout to get the recommended eBook for just $10 until May 31, 2018. Like in many other cases, the representation of the data, which is how the information is encoded and shown to machine learning algorithms, is often the most important and fundamental part in all pipelines of learning or AI. The effectiveness and scalability of the representation largely determine for the performance of the downstream machine learning model and application. As mentioned in the previous section, traditional NLP often uses one-hot encoding to represent the word in a fixed vocabulary and uses a BoW to represent documents.

There is an enduring fear in the music industry that artificial intelligence will replace the artists we love, and end creativity as we know it. As ridiculous as this claim may be, it's grounded in concrete evidence. Last December, an AI-composed song populated several New Music Friday playlists on Spotify, with full support from Spotify execs. An entire startup ecosystem is emerging around services that give artists automated songwriting recommendations, or enable the average internet user to generate customized instrumental tracks at the click of a button. But AI's long-term impact on music creation isn't so cut and dried.

This market research report was originally published at Tractica's website. It is reprinted here with the permission of Tractica. The 2018 Consumer Electronics Show (CES) was dominated by the central theme of artificial intelligence (AI) becoming much more visible and tangible. AI had a dedicated marketplace and the impact of AI could be felt across the show floor. Ironically, the biggest news coming out of this year's "AI themed" CES was the power blackout caused by a result of the deluge of rain that hit Las Vegas during its opening days.

Engineering firm Arup and architecture studio CLS Architetti have used a portable robot to 3D print a concrete house, which is on show for Milan design week. Printed onsite on Milan's Piazza Cesare Beccaria, the 100-square-metre house was formed over the course of a week. Made up of 35 modules, the house features curved walls, a living area, bedroom, kitchen and bathroom. The walls were was built by a robot designed by Cybe Construction, a 3D printing company from Poland, using a special mix of concrete and additives developed by Italcementi, one of the world's largest cement suppliers. The roof, windows and doors were added afterwards.

URL: tthttp://www.cs.ru.nl/B.Jacobs This paper describes a new algorithm for exact Bayesian inference that is based on a recently proposed compositional semantics of Bayesian networks in terms of channels. The paper concentrates on the ideas behind this algorithm, involving a linearisation ('stretching') of the Bayesian network, followed by a combination of forward state transformation and backward predicate transformation, while evidence is accumulated along the way. The performance of a prototype implementation of the algorithm in Python is briefly compared to a standard implementation (pgmpy): first results show competitive performance.

December is the perfect month to predict the key insurtech trends for the year to come and to think of New Year's resolutions: what specific trends to tap into to enhance the digital strategies. We believe these trends should relate to what an insurance carrier would like to accomplish, to what a'winning insurance firm of the future' would look like. We believe that that such winning insurance firms will have four essential elements. Fast changing customer behaviour and new market dynamics make it essential for insurance carriers to increase the contact frequency and provide more added value in these contacts. Fortunately, connectivity, all sorts of connected devices offer an unprecedented entry in customers' daily life. Adding value is about solving the real problem. People don't want a mortgage; they want a nice house to live in. Insurance is usually just part of a solution, but rarely the entire solution to the real problem a customer is facing.

We frequently hear about Machine Learning in the media, especially since the recent wave of interest in deep-learning. The perpetual improvement of Machine Learning techniques combined with the ever increasing amount of data that are stored suggests endless new applications. Many innovative solutions emerge: autonomous driving, next generation supermarkets with implicit payment, next generation chatbots that can interact with you as human beings would do, and so on. More than ever, the future seems within reach. But the more extravagant and original the application is, the more the layman is put off.

We reached out to expert analyst Sanj Bhayro, SVP EMEA Commercial Sales at Salesforce, to highlight the urgent need for SMEs to be primed for automation and build a future-proof IT infrastructure. Like me, you may have recently read that fintech provider iZettle has received €30 million in funding from the European Investment Bank (EIB) to increase its use of emerging technologies such as Artificial Intelligence (AI). This part of the EIB's strategy, one element of its Investment Plan for Europe, aims to provide funding to start-ups and SMEs that will help boost the region's tech economy. I'm particularly excited to see how this funding can help small businesses innovate and grow rapidly. Over the years I've worked with hundreds of small companies across Europe and, more often than not, I find they make tech investment decisions based on what they need right now, rather than what they will need in the future.

As the sandbox of artificial intelligence expands, Asian countries are increasing their stake in AI development. "Companies in Asia can be a bit cautious when it comes to new technology. But once they understand it, they may embrace it faster than counterparts in the U.S or Europe," said Maximilian Vollmar, Bloomberg News Market Specialist. Financial institutions in particular are looking to machine learning, a subset of artificial intelligence that focuses on teaching computer systems to "learn" independently with data, as a way to automate processes and increase efficiency. Of the countries in Asia who are diving into the field, South Korea has made some high-profile strides in recent years.