A new report published this week (18 November 2019) looking at the intersection of AI and journalism has issued a warning to global newsrooms: collaborate with your competitors or face extinction. A global survey of journalism and artificial intelligence' is a joint project between Polis, the international journalism think-tank at London School of Economics and Political Science, and the Google News Initiative, who has funded the research. It surveyed 71 international news organisations on their on use of artificial intelligence for editorial purposes across a seven-month period, showing that just 37 per cent of them have a dedicated AI strategy. Charlie Beckett, director, Polis, London School of Economics and Political Science, said that newsrooms have between two and five years to develop a meaningful strategy, or risk fading out of the digital landscape. "This is a marathon, not a sprint - but they've got to start running now," he said.

Although you haven't figured it out, we usually use artificial intelligence (AI) in Digital Marketing to optimize user experience and automate several everyday processes, without dispensing with the human factor, which is still essential for making strategic decisions. In this post we tell you what applications have artificial intelligence in the different areas of Digital Marketing. Artificial intelligence allows you to create useful and personalized content for users of your website. Mass media such as BBC, The New York Times, Reuters or The Washington Post use this technology to write soft news, such as, sports results, weather forecasts, etc., from data sources with the aim of journalists have more time to produce quality information that requires interpretation and contextualization. In addition, AI is used to make recommendations based on the tastes and browsing habits, same as Amazon and Netflix do, offering relevant suggestions for products that may interest to their users.

I've been thinking about how Amazon takes a chaos-energy attitude towards developing ecosystems around its products. When it's trying to get third parties to work with its products, Amazon throws open the doors and invites all comers. When it's making new products itself, Amazon is much more likely than anybody else to just do whatever it wants, sometimes aggressively. Sometimes that leads to hilarious Alexa products like rings that listen to your whisper when you push a button on it, IR blasters, and Alexa party games. Other times it leads to corporate synergy with a burgeoning police interest in surveillance.

In this chapter, we give an introduction to symbolic artificial intelligence (AI) and discuss its relation and application to multimedia. We begin by defining what symbolic AI is, what distinguishes it from non-symbolic approaches, such as machine learning, and how it can used in the construction of advanced multimedia applications. We then introduce description logic (DL) and use it to discuss symbolic representation and reasoning. DL is the logical underpinning of OWL, the most successful family of ontology languages. After discussing DL, we present OWL and related Semantic Web technologies, such as RDF and SPARQL. We conclude the chapter by discussing a hybrid model for multimedia representation, called Hyperknowledge. Throughout the text, we make references to technologies and extensions specifically designed to solve the kinds of problems that arise in multimedia representation.

Texts like news, encyclopedias, and some social media strive for objectivity. Yet bias in the form of inappropriate subjectivity - introducing attitudes via framing, presupposing truth, and casting doubt - remains ubiquitous. This kind of bias erodes our collective trust and fuels social conflict. To address this issue, we introduce a novel testbed for natural language generation: automatically bringing inappropriately subjective text into a neutral point of view ("neutralizing" biased text). We also offer the first parallel corpus of biased language. The corpus contains 180,000 sentence pairs and originates from Wikipedia edits that removed various framings, presuppositions, and attitudes from biased sentences. Last, we propose two strong encoder-decoder baselines for the task. A straightforward yet opaque CONCURRENT system uses a BERT encoder to identify subjective words as part of the generation process. An interpretable and controllable MODULAR algorithm separates these steps, using (1) a BERT-based classifier to identify problematic words and (2) a novel join embedding through which the classifier can edit the hidden states of the encoder. Large-scale human evaluation across four domains (encyclopedias, news headlines, books, and political speeches) suggests that these algorithms are a first step towards the automatic identification and reduction of bias.

Stadia's potential derives from the massed power of Google's data centers and Google's deep expertise in machine learning and natural language …

Automated camera systems have enabled scientists to quickly track traits of thousands of plants.

San Diego, Calif., November 14, 2019 -- From companies worth billions of dollars to startups employing a small number of people, UC San Diego engineering alumni are at the core of the robotics ecosystem here in San Diego County. This was clearly evident at the sixth annual robotics forum organized by the UC San Diego Contextual Robotics Institute Nov. 7. The forum focused exclusively on local companies this year and was dubbed the San Diego Robotics Forum for the occasion. The goal was to showcase the breadth and depth of the region's robotics strengths, and solidify San Diego's reputation as Robot Beach. "We have an important mission here to showcase how strong San Diego is in the area of robotics," said Henrik Christensen, director of the UC San Diego Contextual Robotics Institute.

A business that leverages virtual process analysis to accelerate digital transformation through imitation learning is one of three startups to win ISG Startup Challenges at events hosted this fall by Information Services Group (ISG) (Nasdaq: III), a leading global technology research and advisory firm. FortressIQ, the San Francisco-based startup that uses AI-based computer vision to "learn" business tasks as they occur in real time, won the ISG Startup Challenge at the inaugural ISG Agile Enterprise Summit October 28 in Boston. Beth Bourg, FortressIQ's marketing director, delivered the winning pitch to an independent panel of judges, and was chosen the winner in a live audience poll. "The first-ever ISG Agile Enterprise Summit explored the benefits of becoming an agile organization and building a culture of continuous improvement," said Karen Healy, partner and global leader, ISG Events. "We were thrilled to hear compelling pitches on emerging solutions that increase efficiency and agility in new and exciting ways. The audience choice, FortressIQ, offers an innovative, automated solution to discover and document processes that are ripe for automation, saving both time and money."