In late 2020, the presidency of the Council of the European Union (EU) released its conclusions on artificial intelligence and human rights. In contrast to the American and Chinese approaches, this effort formalizes what has been dubbed as "a third way" for artificial intelligence -- tech regulation that prioritizes shared "European values." The EU document focuses on the "underlying idea of human dignity" as the key element of a "human-centric approach to AI." While it states that AI-based solutions can "perpetuate and amplify discrimination, including structural inequalities," it also notes that "one Member State continued to object to the use of the term'gender equality'" in the final draft. This dissenting voice, it was later reported, was that of Poland.

Google is doing its part to restore several lost pieces of art that got destroyed during WW2. In order to restore the art, the search engine giant is using artificial intelligence, according to Mashable. It is said that these pieces were part of the loot collected by the German army, which was stored at a castle in Austria. During the last few months of the war, this castle played host to a still-unconfirmed number of artworks by the Austrian artist Gustav Klimt, with the most valuable ones being part of a series called the "Faculty Paintings." However, the Faculty Paintings have been largely destroyed, and only black and white photographs of them exist.

Shots for kids near approval, more vaccine mandates go into effect, and the US's pandemic strategy evolves. Here's what you should know: Want to receive this weekly roundup and other coronavirus news? Yesterday Pfizer-BioNTech asked the FDA to issue an emergency use authorization for its vaccine in kids ages 5 to 11. The drugmakers are submitting relevant data, including information on how it will formulate the two pediatric doses, which are each one-third of those given to adults. The agency is tentatively scheduled to discuss this in an October 26 meeting, and a CDC advisory panel meeting has been scheduled for November 2 and 3, which means shots for children in this age group could be available shortly after that.

There are many great companies that could benefit from the surge in artificial intelligence (AI) in the coming years, so how should investors play it? In this Fool Live video clip, recorded on Sept. 23, Fool.com contributor Rachel Warren discusses why Nvidia (NASDAQ:NVDA) is her top AI stock to buy now. Rachel Warren: Today, I'm going to be talking about Nvidia, which is ticker symbol NVDA. I think it's a really interesting company to consider if you're looking for a high-growth tech company that's very much intertwined with AI, but that's also really established in the space that it's in and has a really diversified business structure. For anyone who is newer to the stock, Nvidia was founded in 1993.

In the past decade, data-driven technologies have transformed the world around us. We've seen what's possible by gathering large amounts of data and training artificial intelligence to interpret it: computers that learn to translate languages, facial recognition systems that unlock our smartphones, algorithms that identify cancers in patients. Eric Lander is science adviser to the president and director of the White House Office of Science and Technology Policy. Alondra Nelson is deputy director for science and society at the White House Office of Science and Technology Policy. But these new tools have also led to serious problems.

Top investigative agencies in the United States like the FBI have reported an increase of 300% in cyberattacks since the COVID-19 outbreak. Most of these attackers use deception, which is why predictive artificial intelligence (AI) becomes essential for cybersecurity. A predictive AI model collects data, analyzes and offers recommendations that can prevent various cyber attacks. Many organizations reconsider using Artificial Intelligence due to the high initial cost and need for infrastructure. However, according to an IBM report, businesses lost $3.86 million in 2020, with a total of more than 200 days spent on finding the actual breach. In 2021, data breach costs rose from $3.86 million to $4.24 million, the highest average total cost in the 17-year history of that report.

But a key ingredient was the National Geospatial-Intelligence Center, … told Army Times that the event "achieved machine to machine learning at scale.".

Healthcare and Life Sciences continues to experience an explosion in the use of Artificial Intelligence to deliver precision medicine, enhance quality of care, improve operational efficiencies, and drive breakthroughs in biomedical research to treat disease. Healthcare Providers, in particular, are looking to the areas of Smart Hospitals and Medical Imaging in this regard. There is an array of interconnected medical devices, sensors and applications that create the Internet of Medical Things (IoMT) which produce significant amounts of data needed to feed these AI models. In this webinar, OMDIA, Hewlett Packard Enterprise and NVIDIA experts will focus on how AI will act as a catalyst to enable the new wave of capabilities and the investments being made now to take advantage of machine learning and state-of-the-art computing. If you have already registered, click here to access.

AI is at the heart of digital disruption and on its way to becoming one of the biggest game-changers in the next few years. Early adopters of AI are reaping significant benefits and have differentiated themselves from the rest. As a result, the AI sector is garnering the attention of numerous investors globally, increasing the number of AI unicorns in just a few years. In India itself, as many as 11 startups earned unicorn tags during the black swan year 2020. This article lists all the AI companies that have reached a valuation of $1 billion or more. A technology platform company, Argo AI, is creating integrated self-driving systems. These are manufactured at scale for safe and reliable deployment in ride-sharing and goods delivery services. Along with Ford and Lyft, Argo AI is planning to launch a self-driving ride-hailing service in the US.

We present a literature survey on non-interactive computational story generation. The article starts with the presentation of requirements for creative systems, three types of models of creativity (computational, socio-cultural, and individual), and models of human creative writing. Then it reviews each class of story generation approach depending on the used technology: story-schemas, analogy, rules, planning, evolutionary algorithms, implicit knowledge learning, and explicit knowledge learning. Before the concluding section, the article analyses the contributions of the reviewed work to improve the quality of the generated stories. This analysis addresses the description of the story characters, the use of narrative knowledge including about character believability, and the possible lack of more comprehensive or more detailed knowledge or creativity models. Finally, the article presents concluding remarks in the form of suggestions of research topics that might have a significant impact on the advancement of the state of the art on autonomous non-interactive story generation systems. The article concludes that the autonomous generation and adoption of the main idea to be conveyed and the autonomous design of the creativity ensuring criteria are possibly two of most important topics for future research.