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) …
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Banks have been in the business of deciding who is eligible for credit for centuries. But in the age of artificial intelligence (AI), machine learning (ML), and big data, digital technologies have the potential to transform credit allocation in positive as well as negative directions. Given the mix of possible societal ramifications, policymakers must consider what practices are and are not permissible and what legal and regulatory structures are necessary to protect consumers against unfair or discriminatory lending practices. In this paper, I review the history of credit and the risks of discriminatory practices. I discuss how AI alters the dynamics of credit denials and what policymakers and banking officials can do to safeguard consumer lending.
Who's involved: German re/insurer Talanx and US-headquartered automation software provider, WorkFusion. What's happening: Talanx and WorkFusion have agreed a strategic partnership. In an initial step, the software from WorkFusion is being used for automated checking and processing in the claims division at Talanx's subsidiary HDI. The software will initially be used for invoices dealing with glass breakage and motor insurance. Significance of development: Talanx has described the new software as "automation 4.0" because the artificial intelligence platform can take end-to-end decisions, known as Intelligent Process Automation.
Gluware Automation v3.6 extends the platform API capabilities including integrations with the Mist and Ansible platforms and introduces industry-first lifecycle management and infrastructure integration enhancements. The new version was developed in response to a growing list of global enterprise customers seeking to scale their network automation capabilities to work in their current environment and across more nodes to be faster within their complex networks. Unique in the industry, Gluware is the only solution that offers this level of Intent-Based network automation capabilities without coding or scripting and in support of a tapestry of automation solutions for multi-vendor, brownfield and greenfield networks. For the first time, companies can use the new Intelligent Model Discovery (IMD) Workflow in the Gluware platform to read in an existing device configuration. This puts the power of "infrastructure as code" into the hands of network engineers enabling powerful automation with no IT staff coding required.
Through the expansive healthcare system in the U.S., few providers are actively using artificial intelligence technology. However, more organizations are getting ready to take advantage of the technology, says Michael Muelly, a radiologist and product manager at Google Cloud Healthcare. By 2005, AI got a boost from rapid advances in computing technology, and that helped usher in more advanced robotics, which led to computers learning from the data itself, Muelly explained during an educational session at the Medical Group Management Association's 2019 conference in New Orleans. Now, machine learning, also known as machine intelligence, is coming into the industry, again via early adopters, says Josh Siegel, chief technology officer and chief clinical architect at Care Cloud, an electronic health records vendor. "Focus your goals and learn what is machine intelligence and what is not," he counsels.
SAS Institute is successfully differentiating itself from tech giants like IBM and Google when it comes to the development of artificial intelligence, according to one of IDC's research leaders The analytics vendor has invested heavily in its AI business and research and development in the past year, and IDC data suggests the investment is paying off. SAS's AI business has seen year-over-year growth at a rate nearly four times that of the overall market, which saw a growth rate of roughly 27 per cent. While a couple of other companies listed in the study had slightly higher growth rates than SAS's 104.6 per cent, none of those companies had higher revenues overall. Warren Shiau, who serves as a research vice-president at IDC Canada, spoke with IT World Canada about the topic and said he believes SAS's big customers, which includes Lockheed Martin, Royal Bank of Scotland, and Honda, have been demonstrated how practical its AI capabilities can be for day-to-day business operations. Shiau specifically cited manufacturing as an example, where AI can be used in conjunction with cognitive capabilities for such procedures such as production lines monitoring and quality control.
Imagine a visit to your doctor's office in which your physician asks you how you've been feeling, whether your medication is working or if the shoulder pain from an old fall is still bothering you -- and his or her focus is entirely on you and that conversation. The doctor is looking at you, not at a computer screen. He or she isn't moving a mouse around hunting for an old record or pecking on the keyboard to enter a diagnosis code. This sounds like an ideal scenario, but as most people know from their own visits to the doctor, it's far from the norm today. But experts say that in an exam room of the future enhanced by artificial intelligence, the doctor would be able to call up a lab result or prescribe a new medicine with a simple voice command.
Because AI learns from the data sets that it is given, there is always a risk of bias setting in. Bias in these data sets is likely to perpetuate the lack of diversity in global workplaces. In this article, we turn the spotlight on the issue of AI bias in HR, with exclusive insights shared by experts from ADP, AVTAR Group, Plum, Job.com, and HireVue. Your HCM System controls the trinity of talent acquisition, management and optimization - and ultimately, multiple mission-critical performance outcomes. Alongside the rise of artificial intelligence (AI) in different sectors, questions around the possibility of bias have also increased.
Today's commercial aircraft are typically manufactured in sections, often in different locations--wings at one factory, fuselage sections at another, tail components somewhere else--and then flown to a central plant in huge cargo planes for final assembly. But what if the final assembly was the only assembly, with the whole plane built out of a large array of tiny identical pieces, all put together by an army of tiny robots? That's the vision that graduate student Benjamin Jenett, working with Professor Neil Gershenfeld in MIT's Center for Bits and Atoms (CBA), has been pursuing as his doctoral thesis work. It's now reached the point that prototype versions of such robots can assemble small structures and even work together as a team to build up a larger assemblies. The new work appears in the October issue of the IEEE Robotics and Automation Letters, in a paper by Jenett, Gershenfeld, fellow graduate student Amira Abdel-Rahman, and CBA alumnus Kenneth Cheung SM '07, Ph.D. '12, who is now at NASA's Ames Research Center, where he leads the ARMADAS project to design a lunar base that could be built with robotic assembly.