Japan will begin research on using artificial intelligence to bolster surveillance by naval patrol aircraft, as a changing national security environment forces the Self-Defense Forces to take on wider roles despite a personnel shortage. The AI would help ascertain whether a target spotted by conventional radar is an enemy vessel or some other threat. Machine learning through previous data would be used to develop the ability to identify a vessel from images that are difficult for the human eye to decipher. Currently, radar data converted to black-and-white images are scrutinized by experienced SDF personnel. The Defense Ministry will use a budget of about 900 million yen ($8.25 million) for development in the fiscal year starting in April, with the goal of outfitting Maritime SDF patrol planes with the technology as early as fiscal 2024.

We recently had the opportunity to catch up with Attila Toth, CEO, zesty.ai, the Silver Winner of the 2019 Zurich Innovation World Championship, to discuss how Artificial Intelligence is impacting the Property & Casualty Insurance market across personal and commercial lines. Click the link to have a listen. You can also read the full transcript of the conversation below. With me today is Attila Toth, CEO of zesty.ai Today we have an interesting show planned for you where we're going to talk about the global insurance industry as it undergoes a digital transformation. As insurance companies find themselves trying to make sense of all these new technologies – artificial intelligence, natural language processing, machine learning, computer vision, – understanding the business case for each can be extremely confusing and daunting. With insurance companies being held to higher customer expectations, the time is now to embrace new technologies to leapfrog the competition. Being status quo is no longer an option. Technology is driving diversity across many industries – insurance included – as it reshapes the value chain. Age-old processes are being disrupted, while new market entrants and changing business models are bringing new threats, as well as opportunities for those who act on them. Some of the questions we'll cover today include: What is the value that AI is delivering to the insurance industry, and how are insurance providers reacting to these seismic changes?

The sad truth is that it's happening in every city in America,

Several cities in Quebec including Gatineau, Montreal, and Rimouski, as well as Windsor, London and Thunder Bay, ON and Halifax, NS, have been participating in the project. Renato explains, that the reasons pipes break include frost, aging, as well as soil corrosion. However, a very important, yet often overlooked problem, is pressure build-up in the system -- with too much variation, pressure weakens pipes. Renato is developing a method to model pressure, which is not currently used in modeling predictions. He adds that this type of modelling can be of tremendous value to municipalities.

Standing onstage in an ornate conference room at the Delta Bessborough Hotel in downtown Saskatoon, former Saskatchewan premier Dr. Grant Devine pitched the agri-food industry on a new idea: a wheat tube. More specifically, a hypothetical hyperloop Devine says could fire shipments of wheat from Moose Jaw to Langley, B.C. at hundreds of kilometres an hour. He says students at the University of Saskatchewan, where he is a professor, had priced the idea at around $18 billion. "You'd load it like you would any other hopper car, load it in the capsule and -- zoom! -- it's out there in a matter of hours," Devine said. Dr. Grant Devine speaks at the AIC2019 conference in Saskatoon, SK on Wednesday, November 6, 2019.

The healthcare industry continues to be a major driver of the U.S. economy, with more than $3.5 trillion spent on healthcare in 2018 alone. Researchers believe that the industry will contribute more than $5.6 trillion to the economy by 2025. Much of this revenue comes from the medical research field, which is responsible for improving drug research, disease diagnosis and treatment protocols. Major research companies are collaborating with software development services to integrate deep learning technology into their investigations. Deep learning promises to transform the way that doctors review medical tests and make diagnoses, helping them identify diseases and start treatment quicker.

The National Institute for Occupational Safety and Health (NIOSH) announced a competition for programmers to develop artificial intelligence (AI) capable of analyzing safety reports and assigning occupational safety and health classification codes. Submissions are due by November 21. When a worker is injured or becomes ill on the job, a person records free-form narrative text explaining how the injury or illness occurred. Currently, human evaluators read the reports and assign codes classifying injuries and illnesses. Reports can contain large amounts of information, and assigning codes is a costly and time-consuming task subject to human error.

This image shows the profile of an electron beam at Berkeley Lab's Advanced Light Source synchrotron, represented as pixels measured by a charged coupled device (CCD) sensor. When stabilized by a machine-learning algorithm, the beam has a horizontal size dimension of 49 microns (root mean squared) and vertical size dimension of 48 microns (root mean squared). Demanding experiments require that the corresponding light-beam size be stable on time scales ranging from less than seconds to hours to ensure reliable data. Synchrotron light sources are powerful facilities that produce light in a variety of "colors," or wavelengths – from the infrared to X-rays – by accelerating electrons to emit light in controlled beams. Synchrotrons like the Advanced Light Source at the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) allow scientists to explore samples in a variety of ways using this light, in fields ranging from materials science, biology, and chemistry to physics and environmental science.

The adoption of technology in the NHS is more closely tied to meeting a "political or commercial imperative" rather than improving care, according to about a dozen stakeholders from across the health system who were interviewed for a new report. Published by the Royal Society for the encouragement of Arts, Manufactures and Commerce, or RSA, the "Patient AI" paper - first covered by the Health Service Journal - sought to identify how the introduction of emerging technologies was "influencing commissioning and clinical practice" across the NHS. The RSA said understanding and agreeing on the purposes for the deployment of new tools and systems needed to be the "starting point for a more constructive conversation" in order to tackle the "embedded scepticism" that it was not being done for the right reasons. The organisation carried out interviews under the Chatham House Rule with professionals involved in the development, procurement and use of data-driven technologies for the health service in England earlier this year. It outlined the work done in partnership with NHSX, the unit for digital, data and technology, and found interviewees believed that a lot of the challenges in embedding new tools stemmed from the fact that the NHS did not see itself as a "digital organisation".

The rise of artificial intelligence has quickly revolutionized significant portions of the economy, including the transportation, health care, and financial sectors. As technology progresses, the United States must develop a comprehensive framework that addresses the opportunities and challenges within AI. The Bipartisan Policy Center has teamed up with Reps. Will Hurd (R-TX) and Robin Kelly (D-IL) to create an AI initiative aimed at establishing a national strategy for how the United States can continue its leadership in developing these technologies while also providing recommendations for how Congress should adapt to ongoing advancements. Hurd announced the work at an October 2019 event and in a subsequent press release.