The financial services sector is undergoing digital transformation, and the driving force behind it is machine learning (ML). ML provides systems with the ability to automatically learn and improve from experience without being explicitly programmed. As the finance sector operates on tons of personal data and billions of critical transactions every second, it becomes especially vulnerable to fraudulent activities. Scammers are always seeking to crack the servers to get valuable data for blackmailing. According to PwC's Global Economic Crime and Fraud Survey 2020, respondents reported losses of a whopping $42 billion over the past 24 months due to fraudulent activities.

A study carried out jointly by Stanford University, SLAC National Accelerator Laboratory, the Massachusetts Institute of Technology, and the Toyota Research Institute (TRI) demonstrated the use of machine learning algorithms to understand the lifecycle of lithium-ion batteries. Until now, machine learning in battery technology was limited to identifying patterns in data to speed up scientific analysis. The latest discovery will help researchers in designing and developing longer-lasting batteries. The research team has been working to develop a long-lasting electric vehicle battery that can be charged in 10 minutes. "Battery technology is important for any type of electric powertrain. By understanding the fundamental reactions that occur within the battery we can extend its life, enable faster charging and ultimately design better battery materials. We look forward to building on this work through future experiments to achieve lower-cost, better-performing batteries," said Patrick Herring, a senior scientist of Toyota Research Institute.

Machine learning and artificial intelligence are often used interchangeably since the former is a subset of the latter. Along with professional and industrial usage of machine learning, now a layman is getting used to the perks of machine learning in routine tasks. With the arrival of machine learning manual labor has become obsolete and now due to the superintelligence of those very machines, mental labor and capabilities would also be performed through machine learning. Machine learning is a popular application of artificial intelligence where the devices possess cognitive abilities similar to those of humans. The machines learn based on data and input provided to them daily.

The COVID-19 crisis has forced millions of teachers around the world to rapidly learn how to use technology to effectively support student learning and assessment, stay connected with their students, experiment with teaching models, and reduce the workload so they can focus on teaching. There are many promising solutions that are helping teachers become more effective, including new technologies such as machine learning (ML), artificial intelligence (AI) and optimised workflows. For example, Revisely is an education company that helps teachers give better feedback on students' writing assignments, such as essays and papers. It saves teachers time by offering built-in comment sets and doing a plagiarism check on student work, among other features. In addition, teachers can track the performance of students on all assignments throughout their learning journey.

Paul Grist, Head of Education, International, Amazon Web Services (AWS) Future of Apprenticeships This week (14-18 Sept) is Artificial Intelligence (#AI) and Machine Learning (#ML) Week @AWS_Edu, Head of Education, Paul Grist explains how Machine Learning can help teachers and improve student outcomes. The COVID-19 crisis has forced millions of teachers around the world to rapidly learn how to use technology to effectively support student learning and assessment, stay connected with their students, experiment with teaching models, and reduce the workload so they can focus on teaching. There are many promising solutions that are helping teachers become more effective, including new technologies such as machine learning (ML), artificial intelligence (AI) and optimised workflows. For example, Revisely is an education company that helps teachers give better feedback on students' writing assignments, such as essays and papers. It saves teachers time by offering built-in comment sets and doing a plagiarism check on student work, among other features.

Machine learning could help complete research tasks usually given to citizen scientists. A new study shows how teaching a computer specific image recognition skills can be used in projects that require classification of large amounts of image data. For years scientists have taken advantage of volunteers who help them sort through massive datasets that are too large for small research teams. Previously this work was needed to be done by humans because the technology for a machine to do it didn't exist. But that is all about to change.

In Part 1 of this series, we reviewed the continued disconnect between corporate IT security spending and the cause of most security incidents. Most breaches are known to be caused by the misuse or takeover of user-access authorizations. In this blog, we suggest some machine-learning-based approaches to user access that will help improve organizational security. Machine learning uses constraint-based and pattern-matching algorithms. These techniques are ideal for analyzing behavioral patterns of people signing in to systems that contain sensitive information.

As our businesses become more digital in all dimensions, high-profile information security breaches are making the news headlines with increasing frequency. The recently-announced card hacking activity at online travel service Orbitz is just one of the latest examples. On March 20, 2018 Orbitz announced a security breach that exposed information derived from at least 880,000 customer payment cards. The breach took place between October and December of 2017, involving customer transaction records dating from 2016 and 2017. Although data captured on Orbitz.com was not affected, the company advised customers using Orbitz travel services within the past two years to check their credit and debit card billing statements from this period and to contact their banks if fraudulent charges were identified.

In Part 1 of this series, we reviewed the continued disconnect between corporate IT security spending and the cause of most security incidents. Most breaches are known to be caused by the misuse or takeover of user access authorizations. In this concluding chapter, we suggest some machine-learning based approaches to user access that will help improve organizational security. In addition, we highlight SAP's delivery of related machine-learning components that address improved information security. Fortunately for SAP customers, machine learning has been embedded in SAP S/4HANA to monitor breach activity from social media and the "dark" (non-indexed) web.

Bob, CFO of ABC Inc is about to get on an earnings call after just reporting a 20% miss on earnings due to slower revenue growth than forecasted. Company ABC's stock price is plummeting, down 25% in extended hour trading. The board is furious and investors demand answers on the discrepancies. Inaccurate revenue forecast remains one of the biggest risks for CFOs. In a recent study, more than 50% of companies feel their pipeline forecast is only about 50% accurate.