Large language models have been widely applied in many aspects of real life, bringing significant efficiency to businesses and offering distinctive user experiences. In this paper, we focus on exploring the application of ChatGPT, a chatbot based on a large language model, to support higher educator in generating quiz questions and assessing learners. Specifically, we explore interactive prompting patterns to design an optimal AI-powered question bank creation process. The generated questions are evaluated through a "Blind test" survey sent to various stakeholders including lecturers and learners. Initial results at the Banking Academy of Vietnam are relatively promising, suggesting a potential direction to streamline the time and effort involved in assessing learners at higher education institutes.

Apple Watch is one of the best-designed smartwatches out there and it provides you with a lot more functionality than just tracking your activities and showing time. There are a lot of hidden Apple watch tips and tricks that you may not know about, so here’s a guide on how to enable them. Ease of use is often the focus for many of Apple’s consumer products and Apple Watch is not that different. The Apple Watch packs a lot of functions and you can actually use it for things other than checking the time or tracking your workouts. For most of the part, you may be familiar with many basic functions on the watch but there are some hidden features and recent improvements that enable you to get more out of your watch.  Here are some Apple Watch Uses, tips and tricks that you should try: Continue Reading . . . . . . . . . . . . . . . . . . . . . . . . Apple (AAPL), Wearable Tech, Technology, Gear&gadgets, S&P 500, Corporate Finance, Nasdaq, iPhone, Apple Music, Smartwatches, Wearable Tech, Investing, Stock Markets, Phones, Financial Markets, App Stores, iOS Apps, Capital Markets, Dow Jones Industrial Average, Warren Buffett, Apple Watch, Stocks, iOS, Mobile Payments, iPad, Microsoft, iPhone Apps, Trading, Apple (AAPL), Emerging Technology, Tech Trends, Artificial Intelligence, Innovation, Technology (Israel), Machine Learning, Technology (China), Education Technology, Computer Science, Big Data, Internet of Things, Problem-solving, Augmented Reality, E-Learning, Technology (Australia), Technology (Africa), Startups, Business Technology, Technology (New Zealand), Robotics, Virtual Reality, Analytics, Technology, Technology (India), Technology (UK), Apple (AAPL), Wearable Tech, Technology, Gear&gadgets, S&P 500, Corporate Finance, Nasdaq, iPhone, Apple Music, Smartwatches, Wearable Tech, Investing, Stock Markets, Phones, Financial Markets, App Stores, iOS Apps, Capital Markets, Dow Jones Industrial Average, Warren Buffett, Apple Watch, Stocks, iOS, Mobile Payments, iPad, Microsoft, iPhone Apps, Trading, Apple (AAPL), Emerging Technology, Tech Trends, Artificial Intelligence, Innovation, Technology (Israel), Machine Learning, Technology (China), Education Technology, Computer Science, Big Data, Internet of Things, Problem-solving, Augmented Reality, E-Learning, Technology (Australia), Technology (Africa), Startups, Business Technology, Technology (New Zealand), Robotics, Virtual Reality, Analytics, Technology, Technology (India), Technology (UK), Apple (AAPL), Wearable Tech, Technology, Gear&gadgets, S&P 500, Corporate Finance, Nasdaq, iPhone, Apple Music, Smartwatches, Wearable Tech, Investing, Stock Markets, Phones, Financial Markets, App Stores, iOS Apps, Capital Markets, Dow Jones Industrial Average, Warren Buffett, Apple Watch, Stocks, iOS, Mobile Payments, iPad, Microsoft, iPhone Apps, Trading, Apple (AAPL), Emerging Technology, Tech Trends, Artificial Intelligence, Innovation, Technology (Israel), Machine Learning, Technology (China), Education Technology, Computer Science, Big Data, Internet of Things, Problem-solving, Augmented Reality, E-Learning, Technology (Australia), Technology (Africa), Startups, Business Technology, Technology (New Zealand), Robotics, Virtual Reality, Analytics, Technology, Technology (India), Technology (UK), Apple (AAPL), Wearable Tech, Technology, Gear&gadgets, S&P 500, Corporate Finance, Nasdaq, iPhone, Apple Music, Smartwatches, Wearable Tech, Investing, Stock Markets, Phones, Financial Markets, App Stores, iOS Apps, Capital Markets, Dow Jones Industrial Average, Warren Buffett, Apple Watch, Stocks, iOS, Mobile Payments, iPad, Microsoft, iPhone Apps, Trading, Apple (AAPL), Emerging Technology, Tech Trends, Artificial Intelligence, Innovation, Technology (Israel), Machine Learning, Technology (China), Education Technology, Computer Science, Big Data, Internet of Things, Problem-solving, Augmented Reality, E-Learning, Technology (Australia), Technology (Africa), Startups, Business Technology, Technology (New Zealand), Robotics, Virtual Reality, Analytics, Technology, Technology (India), Technology (UK)

Algorithms rule the world … or, at least, the world is headed that way. How can you prepare your company and its financial underpinnings not only to survive but also thrive under this new big data paradigm? In his new book, Deep Finance: Corporate Finance in the Information Age, author Glenn Hopper provides a clear guide for finance professionals and non-technologists who aspire to digitally transform their companies into modern, data-driven organizations streamlined for success and profitability. Hopper, who comes to this subject armed with a unique background in finance and technology, contends that the finance department is perfectly placed to lead the digital revolution – bringing companies of all sizes into a new era of efficiency while future-proofing the role of chief financial officer. Deep Finance is written for a wide audience, ranging from those who don't know AI from A/R to those who are already working with data to drive business decisions.

Global corporations face a difficult task in predicting credit ratings. In this case, Massaron employs deep learning techniques to forecast credit ratings for global corporations. Luca Massaron, Senior Data Scientist, Kaggle Master and Google Developer Expert on ML, spoke at the Deep Learning Devcon 2021, organised by The Association of Data Scientists, earlier this month. In his talk on "Deep Learning for Credit Rating", Massaron covered topics, such as how deep learning techniques may be used to forecast credit ratings for worldwide business organisations; obligations are compared to the most widely used traditional machine-learning approaches, such as linear models and tree-based classifiers. According to Massaron, in an article titled "An artificial intelligence approach to shadow rating," the study's objective was to demonstrate that neural networks may be a more effective technique for calibrating and predicting ratings than other modelling approaches currently used in the banking industry. Luca proceeded further by explaining the significance of credit ratings.

We've seen companies make strides in how they use artificial intelligence (AI) technology throughout their businesses. As 2019 ended, I reflected on what to expect with AI in 2020. I reviewed the results from a research report we'll publish soon, and I also reached out to colleagues and friends to get their thoughts. Here's what to pay attention to in the new year for AI. As companies take incremental steps to adopt AI and machine learning, the expectation is that AI will eventually be used in all parts of the business.

In a recent report published by Protiviti and North Carolina State University, analysts found just how important technology and innovation are becoming for corporate executives. Their December 2018 survey found "digital readiness" to be the c-suite's top priority for 2019, with executives also reflecting their concern that the biggest risks their companies face are intensifying. "The perceived increase in the magnitude and severity of risks in today's ever-changing landscape should prompt boards and senior executives to closely scrutinize the approaches to proactively address emerging risks," said North Carolina State University Enterprise Risk Management (ERM) Initiative Director and ERM Professor Dr. Mark Beasley, quoted in Protiviti's release. "Boards of directors and executive management teams cannot afford to manage risks casually on a reactive basis, especially considering the rapid pace of disruptive innovation and technological developments in an ever-advancing digital world." Separate research last month also examined how corporate finance expects are bracing for this digital disruption.

The continuous integration of data, processes, and algorithms is profoundly reshaping finance organizations. However, confusion on how far-reaching the possibilities can be remains prevalent among CFOs and finance leaders. For this reason, SAP and the University of Applied Sciences Berlin (HTW Berlin) joined forces to research how artificial intelligence (AI) is changing finance organizations all over the world. I want to thank the 164 professionals, which included finance specialists, CFOs, and other top executives, who participated in our study. With their insight, we uncovered how the true potential of AI is going beyond teaching machines to think, converting image and speech into captured information, and automating rules-based tasks and process.

Discussion around the impact of intelligent automation often centers on what it means for consumers, or its implications for the workplace and the changing nature of jobs. But what does it mean in practice for finance professionals? As the CFO of an S&P 500 company with more than three decades of finance and business experience, I find that the aspect of robotics and artificial intelligence that has most surprised me is the extent to which we have come to implement these technologies in corporate finance. Digital transformation to this degree is something that has been talked about for years. Now, however, seeing the impact on the individual, day-to-day functions of my team makes transformation seem much more real.

When you mention robots, most people think of Star Wars or those car-manufacturing assembly lines where giant, agile machines move heavy parts, make spot welds or secure bolt-on chassis. Robots have developed to the point where robotic process automation (RPA) is now coming to the world of corporate finance. In finance, we've automated by implementing general ledger and enterprise resource planning (ERP) systems, as well as spreadsheet programs like Microsoft Excel. Yet many corporate financial processes are still stuck in the 20th century. Corporate finance teams spend about 80% of their time manually gathering, verifying and consolidating data, leaving only about 20% for higher-level tasks like analysis and decision making.

The history of robots taking over human jobs is long and littered with doomsday predictions. Just last May, mega-manufacturer Foxconn reportedly replaced 60,000 workers with automated technology. Amazon's warehouses thrive on machines that can move packages. And as Martin Ford, author of the New York Times bestseller Rise of the Robots tells it, this tech will only replace more jobs in the coming decade -- even in traditional white-collar office roles. Ford keynoted Orange Silicon Valley's "A.I. and the Future of Corporate Finance" event, which welcomed a panel of experts to OSV's Spear Street space to discuss the role that artificial intelligence has to place in bookkeeping and auditing operations.