GDPR coming into effect coincides with the more widespread adoption of artificial intelligence as the technology becomes embedded in more and more enterprise applications. There is a palpable excitement around AI for its potential to revolutionize seemingly every facet of every industry. Studies reveal that 80% of executives believe AI boosts productivity. In the immediate future, execs are looking for AI to alleviate repetitive, menial tasks such as paperwork (82%), scheduling (79%) and timesheets (78%). By 2025, the artificial intelligence market is reported to surpass $100 billion.

The Chinese tech giant Huawei has pleaded not guilty to U.S. charges that it stole trade secrets from T-Mobile. A company representative entered the pleas Thursday in federal court in Seattle, where a 10-count indictment was unsealed in January. Charges include conspiracy to steal trade secrets, attempted theft of trade secrets, wire fraud and obstruction of justice. Prosecutors say Huawei stole the technology behind a robotic device that Bellevue, Wash.-based T-Mobile used to test smartphones. Huawei has also been charged in New York with bank fraud and sanctions violations.

The Northern District of California confirmed this approach by invalidating claims directed to automatically generating an "ensemble" of machine learning models under § 101 stating that it was directed towards "mathematical processes that not only could be performed by humans but also go to the general abstract concept of predictive analytics rather than any specific application."

Artificial intelligence is taking automation to a new level at an increasing number of companies. Here are five things to know about this technology, often called AI. Related: Ready to work with a smart robot? It can process massive amounts of data, come to conclusions about it and make decisions. Related: Here's how local companies use artificial intelligence right now They include the University of Dayton, Evanhoe & Associates, Mile Two, Galois Inc., Tangram Flex Inc., LexisNexis Legal and Professional, Yaskawa America Inc.'s Motoman Robotics Division, Huntington Bancshares, Kroger Co., Premier Health and Kettering Health Network.

Current advances in research, development and application of artificial intelligence (AI) systems have yielded a far-reaching discourse on AI ethics. In consequence, a number of ethics guidelines have been released in recent years. These guidelines comprise normative principles and recommendations aimed to harness the "disruptive" potentials of new AI technologies. Designed as a comprehensive evaluation, this paper analyzes and compares these guidelines highlighting overlaps but also omissions. As a result, I give a detailed overview of the field of AI ethics. Finally, I also examine to what extent the respective ethical principles and values are implemented in the practice of research, development and application of AI systems - and how the effectiveness in the demands of AI ethics can be improved.

A leading computer scientist has invented a way for artificial neural networks to recognize objects it sees, even if they're partially obscured. "Machines can readily accomplish tasks we think difficult, but they cannot yet accomplish among the simplest of tasks for humans," said Dr. Stuart H. Rubin of the Naval Information Warfare Center in San Diego. "That's where the game changer lies." On Tuesday, the U.S. Patent and Trademark Office granted Rubin U.S. Patent 10,217,023. The document, which can be downloaded below, describes Rubin's application of cameras connected to an artificial intelligence system, which uses arrays of spatial light modulators to repetitiously examine the camera's imagery and determine if it matches anything in its memory.

Intellectual property continues to be the coin of the realm for technology companies, and in few data-driven industries is this truer than the booming field of machine learning. In its annual canvas of the fastest growing technologies, IFI Claims Patent Services reports that machine learning was again among the hottest commodities based on the number of patent applications. The patent tracker said ML applications jumped 116 percent in 2018 to 2,498. Machine learning is defined as "computer systems based on biological models.") As it has for decades, IBM (NYSE: IBM) remained the leader in the number of patents granted last year with 9,100, a 1 percent annual increase, followed by Samsung Electronics (OTCMKTS: SSNLF), which remained flat at 5,850 patent awards.

Steve and Nick examine how increasingly complex Artificial Intelligence and neural networks have been developed using games as the testing grounds. They also interview Pedro Pavón, a thought leader in AI, about the legal and policy implications AI has for the future. Nick: Hello and welcome to the LAN Party Lawyers Podcast, where we tackle issues at the intersection of video games, law and business. Nick: And we are your hosts. We are lawyers at the firm of Carlton Fields who represent gamers and companies in the gaming space. Nick: Today we're going to talk about artificial intelligence in gaming. With us, we're so excited to have Pedro Pavón, Assistant General Counsel at Honeywell and a thought leader in artificial intelligence.

A two-day High-Level Conference "Governing the Game Changer – Impacts of artificial intelligence development on human rights, democracy and the rule of law" opened in Helsinki today. "New technology, the collection of massive amounts of data, and the use of information, has already changed the lives of people all over the world. Yet, I believe that the "Big Bang" has yet to come. Questions to be raised include: Are some groups neglected or do they face special challenges due to biased algorithms? What happens to democracy, security and accountability? What are the impacts of artificial intelligence on justice systems? How can we ensure that artificial intelligence supports the advancement of democracy and the rule of law?, said the Minister for Foreign Affairs of Finland Timo Soini, in his opening speech. "The Artificial Intelligence revolution long forecast is no longer something for the future.

While data may'want to be free' from a societal perspective, from a company perspective, private data, intellectual property and trade secrets are proprietary knowledge. Such knowledge, mated with domain expertise and smart execution, can be a competitive market advantage, which in a well-run, lean, continuously-improving operation, will ultimately provide market power. To protect data from leaking out, via both external and internal influences, a comprehensive, multi-layered security framework is always essential. And some of the first traces of security breaches, both physical and cyber, can be picked up in the minute signals hidden in the tea-leaves of operations. While IT (Information Technology) typically doesn't have the tools, budget or domain expertise to pick-up such signals across Operations, OT (Operations Technology) conversely has such knowledge but not the time or resources, as they're constantly focused on keeping operations up and running smoothly for the next hour, shift or day.