If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Mentions of artificial intelligence within the filings of companies in the aerospace and defence sector rose 332% between the first and second quarters of 2022. In total, the frequency of sentences related to artificial intelligence between July 2021 and June 2022 was 592% higher than in 2016 when GlobalData, from whom our data for this article is taken, first began to track the key issues referred to in company filings. When companies in the aerospace and defence sector publish annual and quarterly reports, ESG reports and other filings, GlobalData analyses the text and identifies individual sentences that relate to disruptive forces facing companies in the coming years. Artificial intelligence is one of these topics - companies that excel and invest in these areas are thought to be better prepared for the future business landscape and better equipped to survive unforeseen challenges. To assess whether artificial intelligence is featuring more in the summaries and strategies of companies in the aerospace and defence sector, two measures were calculated.
Artificial intelligence (AI) provides thorough data analysis, automates business processes, and engages with customers and employees. The adoption of AI has been particularly widespread in the business world. From workflow management to trend predictions, AI has numerous use cases. Sometimes, I feel like companies view AI the same way, like they are hedging their bets and maybe even expecting defeat. Today I want you to weigh in.
Legal Considerations for PropTech Startups Below we will highlight some legal considerations that proptech startups should begin to pay attention to as this can either make or mar their potential to scale and reap the benefits that technology has provided in the property and real estate space. New types of contract -It is cliché to say that the real estate sector is undergoing a tremendous digital change. With the advent of smart buildings, real estate fintechs, the use of digital printing, robotics, drones, property management solutions, a shared economy which is always ready to match users of space with sellers through digital platforms and other technical innovations. It goes without saying that there will be a need for smarter contracts different from the legacy property agreements. There will be a need for legal agreements that can inclusively cover technologies such as AI, IoT, Data protection clauses, intellectual property concerns, blockchain and other innovative augmentation that proptech will require to deliver on its promises. Data protection - As with the majority of emerging technologies, the use of data in the property tech space is inevitable.
Technology has started to play an even bigger role in the revenue cycle as staffing shortages seem to have hit a high. To this point, more than 57% of health systems and hospitals have more than 100 open roles to fill, with one in four finance leaders needing to hire more than 20-plus employees to fully staff their revenue cycle departments, according to a recent survey. Automation has been a clear solution to not only alleviating staffing issues in revenue cycle but making the administrative process more efficient overall. While, according to survey, the use of automation in revenue cycle operations increased in 2021 from 66% to 78%, there remains a demand for further implementation to relieve the burden on staff. In fact, one recent revenue cycle leader HealthLeaders spoke to about its automation journey was Jamie Davis, executive director of revenue cycle management at Banner Health.
On Monday, employees across Activision Blizzard executed a protest during the virtual hearing, with several dozen workers attending the Zoom hearing with their pictures saying "ABK Stop Union Busting," or changing their display name to "stop union busting," which irked Activision Blizzard's lawyers. Polk, the Reed Smith lawyer, objected to the protesters, calling them potentially "disruptive" and asking that the NLRB remove those images and have people change their names. In response, the board hearing officer Basantes said the virtual hearing was akin to an in-person one, where anyone could attend and those in attendance wouldn't know others' names on sight. Basantes then allowed protesters to rename themselves to "Guest," which allowed more than one Activision Blizzard employee to rejoin the meeting without worrying about their employer noting their real names.
Peloton Interactive plans to cut about 800 jobs as it looks to reduce its operating footprint and cut costs, the company said Friday. The New York-based company said it would eliminate its North American field operations warehouses and make cuts within its member-support team, among other changes, resulting in the loss of 784 jobs. It also plans to scale back the retail operations it had been building out and raise the prices on some of its products in the U.S.
Yesterday evening, the Washington Post broke the blockbuster news that FBI agents who searched former President Trump's Mar-a-Lago residence on Monday were looking for "nuclear documents," a phrase that immediately set off alarms inside national security circles. The nation's nuclear systems and plans are considered among the most sensitive and most narrowly known secrets. Trump denied the report, calling the "nuclear weapons issue" a "hoax." But assuming the Post's reporting is correct, what could such a vague phrase as "nuclear documents" mean, and what could we learn about such a category? Broadly speaking, the US intelligence and defense communities would possess four different categories of files that might be considered "nuclear documents": nuclear weapon science and design; other countries' nuclear plans, including the nuclear systems and command of allied nations (UK, France) and adversaries (Russia, China, North Korea, Iran), as well as countries whose nuclear programs exist in a more gray zone (Israel, India, Pakistan); details on the United States' own nuclear weapons and deployments; and details on US nuclear command & control procedures, known in Pentagon parlance as NC2.
Looking at all of the very large convolutional neural networks such as ResNets, VGGs, and the like, it begs the question on how we can make all of these networks smaller with less parameters while still maintaining the same level of accuracy or even improving generalization of the model using a smaller amount of parameters. One approach is depthwise separable convolutions, also known by separable convolutions in TensorFlow and Pytorch (not to be confused with spatially separable convolutions which are also referred to as separable convolutions). Depthwise separable convolutions were introduced by Sifre in "Rigid-motion scattering for image classification" and has been adopted by popular model architectures such as MobileNet and a similar version in Xception. In this tutorial, we'll be looking at what depthwise separable convolutions are and how we can use them to speed up our convolutional neural network image models. Before diving into depthwise and depthwise separable convolutions, it might be helpful to have a quick recap on convolutions.
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Mentions of artificial intelligence within the filings of companies in the maritime industry rose 67% between the first and second quarters of 2022. In total, the frequency of sentences related to artificial intelligence between July 2021 and June 2022 was 295% higher than in 2016 when GlobalData, from whom our data for this article is taken, first began to track the key issues referred to in company filings. When companies in the maritime industry publish annual and quarterly reports, ESG reports and other filings, GlobalData analyses the text and identifies individual sentences that relate to disruptive forces facing companies in the coming years. Artificial intelligence is one of these topics - companies that excel and invest in these areas are thought to be better prepared for the future business landscape and better equipped to survive unforeseen challenges. To assess whether artificial intelligence is featuring more in the summaries and strategies of companies in the maritime industry, two measures were calculated.