In recent years, deep learning and machine learning have gained traction in so many areas that have a direct positive effect on our lives as well as complex tasks such as computer vision (image recognition), machine translation, and natural language processing. And with like so many other technologies that are changing our lives for good, it has the destructive potential to change it for bad, there is no reason why it won't also be used for malicious activities as well. Up until now, we haven't seen the use of AI for malicious activities in cybersecurity due to the high costs, lack of skills and the tools available. But just like any other technology, it's a matter of time before it happens in cybersecurity. Think about what would happen when attackers start using the power of deep learning and machine learning for their advantage?

What does the use of artificial intelligence look like in everyday health life? What is already possible today, where are the challenges and opportunities? This Meetup is supported by Aicura Medical, IBM PowerAI Vision and WWK Versicherungen and is a teaser event for this year's www.healthhackathon.com at the Xpomet from 10-12 October in Berlin. The focus of the hackathon will be on medical technology, hospital management, care and health insurance and will bring together about[masked] working medical-affine programmers and digital-affine physicians from hospitals, companies and insurance companies. We want to integrate Deep and Machine Learning as well as Blockchain and other technologies into today's health challenges.

If you thought the battle between machines and jobs – the dislocation of labor and society resulting from digitization or automation – has been one-sided so far, just wait. The next wave of attack is well underway, and it's called AI. Artificial Intelligence, most simply, refers to computers that perform tasks that normally require human intelligence – things like visual perception, speech recognition, even decision-making. Earlier this year the management consulting firm McKinsey famously wrote that "25 percent of the global workforce will either need to find new professional activities by 2020 or significantly broaden their technological skills. The World Economic Forum's "Future of Jobs Report: 2018" states, "By 2022, the skills required to perform most jobs will have shifted significantly… [and] no less than 54% of all employees will require significant re- and upskilling." The greatest concerns are not just that AI destroys jobs, but that it increases inequality – that low-wage employees get displaced, while high-wage employees maintain or even extend their value that's more difficult to replace with a machine. Of course, new technologies have disrupted existing processes for centuries. Will the experience with AI be different than with previous technologies? Most importantly, what can governments, corporations, small businesses and individual workers do to not just avoid massive disruption, but rather position themselves to take outsized advantage of the opportunities? To find out, I recently hosted an excellent roundtable discussion at Clayton, Dubilier & Rice with NYU Professor Robert Seamans. Prof. Seamans' studies how technology and governance structures affect strategic interactions between firms, affect incentives to innovate, and ultimately shape market outcomes. Previously he served under President Obama as a Senior Economist at the White House Council of Economic Advisers.

As confusion reigned among Shanghai citizens over the correct classification of waste since the city's trash sorting regime kicked in on July 1, China's tech giants have been quick to jump in with solutions. Shanghai was the first Chinese city to enforce new regulations for waste management, as the superpower attempts to curb its trash production that has already overtaken the United States'. Chinese e-commerce giant JD.com announced last week that it had launched artificial intelligence (AI) solutions to make trash classifications smarter. The Snapshop trash sorting function can be found in the JD Finance app. Users may search for "垃圾分类(trash sorting)" to open it.

In the fall of 1975, I entered medical school with ninety other students, most of us fresh out of college. We were an idealistic lot. Marcus Welby, M.D., about the kind family doctor with the ultimate bedside manner, was the hot medical TV show at the time, and Dr. Kildare reruns were still showing frequently. It was a simpler world of medicine--one with time to have a genuine relationship with patients. There were few medical procedures or fancy scans (beyond X-rays) or lab tests that could be ordered.

Wikifriend offers a platform which uses artificial intelligence-driven conversational technology to facilitate access to digital content that would otherwise require articulated steps for enjoyment. The platform allows businesses to offer a continuous support service guaranteeing a personalized conversational level improving the customer experience. Wikifriend is a human-to-machine conversational interface that facilitates the use of complex computer applications for any person, simply by using voice commands. From brand reputation management in digital media and fake news recognition to Health Care, Financial Services, Home Automation, and Computer Vision, Wikifriend brings disruptive innovation to the industry. Merge German semantic engine and high-security level sounds good to customers?

Since the American Recovery and Reinvestment Act of 2009 incentivized the adoption and use of electronic health records (EHRs), EHRs have become ubiquitous in the health care industry. Recent federal reports show about 84% adoption in hospitals and about 86% adoption in office-based practices. Patient information that was once captured on paper is now being regularly recorded and stored in EHRs, creating new opportunities for analyzing and drawing insights from these increasingly rich data sets. While EHRs can support easier access to and sharing of information by individual providers and patients, larger efforts (e.g. Why is EHR data complex?

The National Security Commission on Artificial Intelligence -- which is tasked with researching ways to advance the development of AI for national security and defense purposes -- released its initial report to Congress July 31. The group was established under the fiscal year 2019 National Defense Authorization Act. The legislation required the commission to release an initial report to Congress within 180 days of the NDAA's enactment. The panel has 15 members, led by Chairman Eric Schmidt, the former head of Google's parent company Alphabet, and Vice Chairman Robert O. Work, a former deputy secretary of defense who served in the Obama administration. The initial report provided a summary of the group's activities and its plans for the future but did not offer any recommendations to Congress.

There could be a time in the not too distant future whereby AI has replaced many of our jobs, but rather than mean we are all out of work, such a move would allow us to focus on doing more meaningful jobs that don't need to have an impact on the economy for the world to still operate. "You always see jobs opening up in previous industrial revolutions, but I think at some point AI is going to be capable of doing pretty much anything," explains Dr Alex Allan, the CTO and founder of AI London startup Kortical to Pocket-lint in an interview for the Pocket-lint podcast. "The potential advantage of that is that the cost of living could go to virtually nothing for everyone. Imagine if you have an AI doctor in your phone that could be just as good as a GP? It means anyone in the world who has got a smartphone, which is more than 50 per cent of people, would have access to healthcare. "There will be challenges of how we transition from a society where everyone has to have a job, to one where potentially you might not need that many jobs that directly influence the economy.