A rule-based system may be viewed as consisting of three basic components: a set of rules [rule base], a data base [fact base], and an interpreter for the rules. In the simplest design, a rule … can be viewed as a simple conditional statement, and the invocation of rules as a sequence of actions chained by modus ponens.
– from The Origin of Rule-Based Systems in AI. Randall Davis and Jonathan J. King, reprinted as Ch. 2 of Rule Based Expert Systems: The Mycin Experiments of the Stanford Heuristic Programming Project (The Addison-Wesley Series in Artificial Intelligence). Bruce G. Buchanan and Edward H. Shortliffe (Eds.). Addison-Wesley Longman Publishing Co., Inc., Boston, MA, USA, 1984.
Fraugster, a German and Israeli startup that has developed Artificial Intelligence (AI) technology to help eliminate payment fraud, has raised $5 million in funding. Earlybird led the round, alongside existing investors Speedinvest, Seedcamp and an unnamed large Swiss family office. The new capital will be used to add to Fraugster's headcount as it expands internationally. Founded in 2014 by Max Laemmle, who previously co-founded payment gateway company Better Payment, and Chen Zamir, who I'm told has spent more than a decade in different analytics and risk management roles including five years at PayPal, Fraugster says it's already handling almost $15 billion in transaction volume for "several thousand" international merchants and payment service providers, including (and most notably) Visa. Its AI-powered fraud detection technology learns from each transaction in real-time and claims to be able to anticipate fraudulent attacks even before they happen.
Industry 4.0 is impacting not only Operational Technology, but Information Technology as well. This can most readily be seen, perhaps, when one considers how machine learning and artificial intelligence is driving efficiencies in business processes that begin with physical documents, digitize them, and then classify, enrich and dispatch them to workflows before they are, finally, archived in document management systems. "Digital" is now firmly embedded in every business. But even with technology as an integral part of the organization and its strategy, it is people who will ensure success in a world that continues to reinvent itself at an unprecedented rate. Simply adding more technology to the enterprise is insufficient; we must focus instead on enabling people to do more with that technology.
As enterprises look to deploy distributed ledgers, the industry's largest IT providers have launched blockchain-as-a-service (BaaS), offering a way to test the nascent technology without the cost or risk of deploying it in-house. The BaaS offerings could help companies who don't want to build out new infrastructure or try to find in-house developers, which are in hot demand. "The thing to be thinking about is that we're still in the early innings of this blockchain wave," said Bill Fearnley Jr., IDC's research director for Worldwide Blockchain Strategies. "There are very few people with multiple years of deep, hands-on experience." While heavily hyped, blockchain technology – which gained its initial notoriety from bitcoin cryptocurrency – has the potential to offer a new paradigm for the way information is shared; tech vendors and companies are rushing to figure out how they can use the distributed ledger technology to save time and admin costs.
McCullough also addresses the fact that Penrose's argument rests on the assumption that human reasoning is consistent and that human beings can be sure of their own consistency. He argues that this assumption is not beyond doubt and presents a thought experiment in order to show how inconsistencies could turn up even during careful and justified reasoning. He proposes to imagine an interrogator asking questions that can be answered by yes or no, and an experimental subject that can answer these questions by pressing a'yes' button or a'no' button. If the interrogator asks the question "Will you push the'no' button", then this question cannot be answered truthfully. The subject knows that the true answer is'no', but he cannot communicate this answer by pressing the'no' button.
The huge coverage devoted to the topics of AI and edge computing sparked an idea when I recently visited JFK Airport. My journey coincided with a severe weather storm that disrupted travel along the East Coast. This situation illustrates how customer service agents assist passengers (at the edge) when dealing with uncertainty and changing circumstances (relying predictive analysis and intelligent decision-making under uncertainty). The IoT is imminent – and so are the security challenges it will inevitably bring. Get up to speed on IoT security basics and learn how to devise your own IoT security strategy in our new e-guide.
According to Cory Janssen, Data Migration scenarios are routine IT activities, and most organizations migrate data on a quarterly basis. However, there is nothing routine about Data Migration, and there are a tremendous number of issues that arise when a migration is designated as a purely "IT activity". When 83% of data migration projects either fail or exceed their budgets and schedules, how does a responsible organization avoid or minimize the risk of being part of those statistics? The answer is not a simple one, but a combination of different aspects that need to be factored in and managed as early as inception. There are common pitfalls that, once identified and properly addressed, will pave the road for a less painful Data Migration Project.
Much has been made about the rise of artificial intelligence (A.I.) and the effects it has on our society. So far, lately with its explosion especially throughout the last 5 years -- it has been used a political weapon designed to really scare peers, constituents and even go so far as to generate animosity, fear and ignorance. A.I. is real and will continue to grow as it moves to harness and leverage its own power in numerous industries. We are facing it every single day in our lives within the current smartphone era. The most notable A.I. interaction the mass market had faced?
WASHINGTON – Education Department officials opened formal negotiations on Monday to rewrite federal rules meant to protect students from fraud by colleges and universities. The talks with university representative and student advocates are taking place as the department faces criticism for delaying consideration of tens of thousands of loan forgiveness claims from students who say they were defrauded by for-profit colleges. The 1994 rule, known as borrower defense, allowed loan forgiveness if it was determined that the college had deceived them. But the rule was rarely used until the demise of the Corinthian and ITT Tech for-profit chains several years ago, when thousands of students flooded the department with requests to cancel their loans. In 2016, the Barack Obama administration passed revisions to the rule, which clarified the process and added protections for students.
Education Department officials opened formal negotiations on Monday to rewrite federal rules meant to protect students from fraud by colleges and universities. The talks with university representative and student advocates are taking place as the department faces criticism for delaying consideration of tens of thousands of loan forgiveness claims from students who say they were defrauded by for-profit colleges. The 1994 rule, known as borrower defense, allowed loan forgiveness if it was determined that the college had deceived them. But the rule was rarely used until the demise of Corinthian and ITT Tech for-profit chains several years ago, when thousands of students flooded the department with requests to cancel their loans. In 2016, the Obama administration passed revisions to the rule, which clarified the process and added protections for students.
The dynamic nature of the cloud means that change is a constant when it comes to modern cloud-based infrastructure. Delivering modern applications to end users, therefore, is a constantly shifting challenge. Delivery automation helps IT Ops teams ensure that apps are providing an optimal end user experience over hybrid-cloud and multi-cloud environments, no matter what the current state of the infrastructure is. To employ a delivery automation strategy that reflects your business rules, making real-time decisions based on a combination of real user monitoring, synthetic testing, APM, NGINX / local load balancers, and other data sources, is critical. In his session at 21st Cloud Expo, Simon Jones, Evangelist and head of marketing for Cedexis, showed you how easy it can be to leverage these disparate data sources to automate your hybrid-cloud app delivery and ensure your end users enjoy their app experience.