Industry has always been in the pursuit of becoming more economically efficient and the current focus has been to reduce human labour using modern technologies. Even with cutting edge technologies, which range from packaging robots to AI for fault detection, there is still some ambiguity on the aims of some new systems, namely, whether they are automated or autonomous. In this paper we indicate the distinctions between automated and autonomous system as well as review the current literature and identify the core challenges for creating learning mechanisms of autonomous agents. We discuss using different types of extended realities, such as digital twins, to train reinforcement learning agents to learn specific tasks through generalization. Once generalization is achieved, we discuss how these can be used to develop self-learning agents. We then introduce self-play scenarios and how they can be used to teach self-learning agents through a supportive environment which focuses on how the agents can adapt to different real-world environments.

Amplion, a leading precision medicine intelligence company, has released Dx:Revenue, a groundbreaking software solution that enables test providers to identify ideal pharmaceutical partnership opportunities at the right time to advance precision medicine collaboration. Dx: Revenue is an extension of Amplion's core business intelligence platform that leverages proprietary machine learning to deliver tailored insights into pharma and test developer activities. The platform draws from more than 34 million evidence sources such as clinical trials, scientific publications, conference abstracts, FDA cleared and approved tests, lab developed tests, diagnostic and drug pipelines and more in real time, producing prioritized and timely partnering opportunities that are a precise match between a test provider's capabilities and pharma's specific needs. "Precision medicine has a problem," says Chris Capdevila, CEO, Amplion. "There is an insurmountable volume of information with the potential to drive the realization of precision medicine for patients, but accessing that information strategically, effectively and quickly to make the best pharma partnering decisions is beyond human scale. Our company was founded to address this issue by providing critical evidence-based intelligence that supports the strategic decisions pharmaceutical and test developers need to make to be successful."

At the beginning of June, the German Weather Service counted 177,000 lightning bolts in the night sky within a few days. The natural spectacle had consequences: Several people were injured by gusts of wind, hail and rain. Together with Germany's National Meteorological Service, the Deutscher Wetterdienst, computer science professor Jens Dittrich and his doctoral student Christian Schön from Saarland University are now working on a system that is supposed to predict local thunderstorms more precisely than before. It is based on satellite images and artificial intelligence. In order to investigate this approach in more detail, the researchers will receive 270,000 euros from the Federal Ministry of Transport.

BMO Capital Markets is a trade name used by BMO Financial Group for the wholesale banking businesses of Bank of Montreal, BMO Harris Bank N.A. (member FDIC), Bank of Montreal Europe p.l.c, and Bank of Montreal (China) Co. Ltd and the institutional broker dealer businesses of BMO Capital Markets Corp.

We thank Twist Bioscience for synthesizing and cloning ChR sequences, D. Wagenaar (California Institute of Technology) and the Caltech Neurotechnology Center for building the mouse treadmill, J. Brake (California Institute of Technology) for performing spectrometer measurements, J. Bedbrook for critical reading of the manuscript and the Gradinaru and Arnold laboratories for helpful discussions. This work was funded by the Institute for Collaborative Biotechnologies grant no. W911NF-09-0001 from the US Army Research Office (F.H.A) and the National Institutes of Health (NIH) (V.G.): NIH BRAIN grant no. RF1MH117069, NIH Director's Pioneer Award grant no. DP1NS111369, NIH Director's New Innovator Award grant no.

Europe a century ago was a global powerhouse of innovation, but it has started to lose its edge: today, despite some notable exceptions, many innovative companies are found elsewhere. Europe is falling behind in growing sectors as well as in areas of innovation such as genomics, quantum computing, and artificial intelligence, where it is being outpaced by the United States and China. A discussion paper from the McKinsey Global Institute (MGI), suggests five paths that could help the continent regain its competitive edge. The paper, Innovation in Europe: Changing the game to regain a competitive edge (PDF--395KB), focuses on ways that Europe could seek to build on its strengths rather than trying to play catch-up, given that it is hindered by fragmentation and lack of scale. This article is a condensed version of the original paper, which draws from MGI research as well as from a recent collaboration with the World Economic Forum. Given Europe's relatively high wage costs and low reliance on natural resources, innovation remains of fundamental importance for the continent's economic and social system. European companies still account for one-quarter of total industrial R&D in the world, but over the past ten years US companies have continued to increase their share, reinforcing their leadership position.

Machine learning technology is poised to be huge thing in financial services. In fact, two-thirds of UK-based firms are already using it. That is according to two of the UK's top financial regulators. The Financial Conduct Authority (FCA) and the Bank of England have taken a deep dive into how the financial services industry in the country is using machine learning. The research is based on a survey sent out to 300 firms, including banks, credit brokers, e-money institutions, financial market infrastructure firms, investment managers, insurers, non-bank lenders and principal trading firms.

Artificial intelligence (AI) technologies are commonly used to cope with the growing number of cyber threats.

Every summer there is a mass exodus from New York City towards the white beach at Jones Beach State Park. Here, looking out over the Atlantic Ocean, you can sunbathe, catch a concert or play a game of mini-golf. And get away from the bustle of the city. But you have to get there first. And there's something odd about the route you take. The flyovers over the Southern State Parkway that leads to Jones Beach are low.

Benefits claimants could soon be using robots to claim cash as the Government speeds up the development of an AI system by working with a billionaire tech boss who declared recently: 'I want a bot for every person'. The Department for Work and Pensions has employed more than 1,000 new IT staff and created an £8million-a-year'intelligent automation garage' to develop up to 100 new robots to help support Britain's welfare system - used by 7million people each year. The UK government is working with New York-based UiPath, co-founded by billionaire Daniel Dines, whose £7billion company is viewed as a future Google of robotics and Artificial Intelligence. Mr Dines' software is already used by Walmart, Toyota and many banks and now will help the DWP develop systems to check benefits claims with tech giants IBM, Tata Consultancy and Capgemini also involved. Developers believe a'virtual workforce' could handle simpler welfare cases and payments faster and with fewer mistakes than today - while more complicated cases would still be dealt with by human staff.