With the turmoil in cybersecurity and the mind-blowing advances in AI, it is only natural that cybersecurity practitioners consider further employing learning techniques to help secure their organizations and improve the efficiency of their security operation centers. But with great fears come great opportunities for both the good and the evil, and a myriad of bad deals. This paper discusses ten issues in cybersecurity that hopefully will make it easier for practitioners to ask detailed questions about what they want from an AI system in their cybersecurity operations. We draw on the state of the art to provide factual arguments for a discussion on well-established AI in cybersecurity issues, including the current scope of AI and its application to cybersecurity, the impact of privacy concerns on the cybersecurity data that can be collected and shared externally to the organization, how an AI decision can be explained to the person running the operations center, and the implications of the adversarial nature of cybersecurity in the learning techniques. We then discuss the use of AI by attackers on a level playing field including several issues in an AI battlefield, and an AI perspective on the old cat-and-mouse game including how the adversary may assess your AI power.

Autonomous agents are limited in their ability to observe the world state. Partially observable Markov decision processes (POMDPs) formally model the problem of planning under world state uncertainty, but POMDPs with continuous actions and nonlinear dynamics suitable for robotics applications are challenging to solve. In this paper, we present an efficient differential dynamic programming (DDP) algorithm for belief space planning in POMDPs with uncertainty over a discrete latent state, and continuous states, actions, observations, and nonlinear dynamics. This representation allows planning of dynamic trajectories which are sensitive to structured uncertainty over discrete latent world states. We develop dynamic programming techniques to optimize a contingency plan over a tree of possible observations and belief space trajectories, and also derive a hierarchical version of the algorithm. Our method is applicable to problems with uncertainty over the cost or reward function (e.g., the configuration of goals or obstacles), uncertainty over the dynamics (e.g., the dynamical mode of a hybrid system), and uncertainty about interactions, where other agents' behavior is conditioned on latent intentions. Benchmarks show that our algorithm outperforms popular heuristic approaches to planning under uncertainty, and results from an autonomous lane changing task demonstrate that our algorithm can synthesize robust interactive trajectories.

Apple is working on technology for the perfect selfie. The tech giant acquired Spectral Edge, a UK-based AI startup that uses machine learning to make smartphone pictures crisper, with more accurate colors. The system captures and blends an infrared shot with a standard shot to enhance a photograph's overall depth, detail and color. The startup uses a process that completely relies on machine learning that can be combined with both hardware and software to improve pictures. The news was first revealed by Bloomberg, which obtained secret documents'that Apple now controls Spectral.'

Edge computing provides groundbreaking innovations to enterprise cloud organizations, including nearly instant code transfer, reduced latency, and enhanced performance. The lightning speed of edge compute is due to the placement of the platform. Unlike public cloud, edge compute is placed as close as possible to the point of interaction with humans, electronics, and various connected devices. Edge compute becomes more and more relevant to companies as applications evolve, including virtual reality, augmented reality, and video analytics, which rely on artificial intelligence. With real-time code transfer that AI needs to be extremely precise, and as AI evolves, every millisecond counts, according to Paul Savill (pictured), senior vice president of core network and technology solutions at CenturyLink Inc.

It's that time when we start to look ahead to what next year holds for the life science sector...Lu Rahman outlines 2020s big medtech players A decade ago the healthcare advances create by AI would have seemed the stuff of dreams. But back in 2018 Theresa May announced plans to use artificial intelligence and data to transform the way certain diseases like cancer. The technology is moving at a pace – this year we heard that a team led by the University of Surrey had filed the first ever patent for inventions autonomously created by AI without a human inventor. Professor Ryan Abbott explained the implications this had for the life science sector: "These filings are important to any area of research and development as well as any area that relies on patents. Patents are more important in the life sciences than in many other areas, particularly for drug discovery. AI has also been used extensively in the drug discovery process for a long time for tasks like screening of compounds and in silico analysis. These tasks can be the foundation for patent filings. "As AI is becoming increasingly sophisticated, it is likely to play an increasing role in R&D including in the life sciences.

WIRE)--Citrine Informatics has been named an Enterprise of the Year Gold winner in the Best in Biz Awards, the only independent business awards program judged by prominent editors and reporters from top-tier publications in North America. Citrine Informatics' artificial intelligence technology is used by the world's largest materials and chemicals companies to accelerate the product development cycle. Since 2011, Best in Biz Awards' entrants have spanned the spectrum, from the most innovative local companies and start-ups to some of the most recognizable global brands. With more than 700 entries, the 9th annual program attracted a record number of entries from an impressive array of public and private companies of all sizes and spanning all geographic regions and industries in the U.S. and Canada. Best in Biz Awards 2019 honors were conferred in 80 different categories, including Company of the Year, Fastest-Growing Company, Most Innovative Company, Best Place to Work, Customer Service Department, Executive of the Year, Most Innovative Product, Enterprise Product, Best New Service, CSR Program, Event and Blog of the Year.

Marc Andreessen famously said that "Software is eating the world" and everyone gushed into the room. This was as much a writing on the wall for many traditional enterprises as it was wonderful news for the software industry. Still no one actually understood what he meant. "Today, the world's largest bookseller, Amazon, is a software company -- its core capability is its amazing software engine for selling virtually everything online, no retail stores necessary. On top of that, while Borders was thrashing in the throes of impending bankruptcy, Amazon rearranged its web site to promote its Kindle digital books over physical books for the first time. Now even the books themselves are software."

The age of conversational AI is here and it's completely redefining how organisations, employees and consumers are communicating with one another. Thanks to its ability to use natural language processing (NLP) to map spoken or written words to intent, conversational AI is no longer just a gimmick. Instead, conversational AI is making an impact across nearly every sector -- in our homes, cars, call centres, banks, online shops, and hospitals--and the use cases are growing. Combining complex NLP, cognitive learning abilities, autonomic task management, and emotional intelligence, conversational AIs can both learn from and respond to text or voice in an engaging, personalised and emotionally cognisant manner. The potential is immense and so it's unsurprising that recent research found that the global conversational AI market is expected to increase from $4.2 billion in 2019 to $15.7 billion by 2024.

More than 13,000 artificial intelligence mavens flocked to Vancouver this week for the world's leading academic AI conference, NeurIPS. The venue included a maze of colorful corporate booths aiming to lure recruits for projects like software that plays doctor. Google handed out free luggage scales and socks depicting the colorful bikes employees ride on its campus while IBM offered hats emblazoned with "I A ." Tuesday night, Google and Uber hosted well-lubricated, over-subscribed parties. At a bleary 8:30 the next morning, one of Google's top researchers gave a keynote with a sobering message about AI's future. Blaise Aguera y Arcas praised the revolutionary technique known as deep learning that has seen teams like his get phones to recognize faces and voices.

Artificial Intelligence is on everyone's lips right now. It is the fastest growing branch of the high-tech industry. The German government sees AI as a key strategy for mastering some of the greatest challenges of our time, such as climate change and pollution. It is difficult to establish a clear differentiation of Artificial Intelligence or even a precise definition. AI is often used in connection or sometimes even synonymous with the terms machine learning, big data, or deep learning.