When the coronavirus crisis erupted in 2020, it became apparent that the medical emergency was accompanied by severe shortages, especially in some medical devices. The pattern was first observed for ventilators: demand spiked everywhere and the supply chain was disrupted. This was because production of the devices spanned multiple countries, with each part dependent on other parts manufactured in different locations. The longer the chain and the more complex the dependence, the greater the exposure of any point to the disruption of another one, and to mandated shutdowns. Now, two years since COVID first hit, this pattern has affected almost every sector of the global economy.
'Business is an art and business leaders are artists', a well said a statement that is proving to be true every time a top leader takes amazing decisions for his organization. Although businesses rise and fall as times change, leaders never fail to be at the forefront to give their best. However, the key to long-term sustained success is great leadership and the ability of an executive to embrace the evolving trends. While talking about trends, the first thing that comes to our mind is artificial intelligence and disruptive technologies that are driving the next generation towards major digitization. The idea of technology came to practical usage when men thought that they needed machines to replace human activities. The core of such machines is to mimic or outperform human cognition. Although the concept of artificial intelligence came into existence in the 1950s, it didn't get fruition till the 1990s when technology hit the mainstream applications. Since then, the rise of technology has been enabled by exponentially faster and more powerful computers and large, complex datasets. Today, we have many futuristic technologies like machine learning, autonomous systems, data analytics, data science, and AR/VR in play. On the other hand, the enormous inflow of data has also contributed to this growth. In the digital world, development is highly reliant on technological advancement. Organizations across diverse industries are processing data to find insights and data-driven answers. Apart from laymen and consumers, it is the business leaders and corporate executives who have joined the bandwagon of the population to use artificial intelligence to the fullest. These trailblazing leaders are now increasingly using technology to optimize performance and experiment with new explorations. Their success story is what the world needs to hear. Analytics Insight has listed the top 100 such interviews that describe the journey of tech leaders and companies. Engineering and mining companies have faced a growing range of pressures in recent years, including price volatility, the need to drill down deeper to find new resources, and an industry-wide skills shortage. To address these challenges, many mining companies have embraced digital technology to enhance engineering design and develop smart mines'. Ausenco is a tech-savvy engineering company that delivers innovative, value-add consulting services, project delivery, asset operations, and maintenance solutions to the mining and metals, oil and gas, and industrial sectors….
Artificial Intelligence Speeds Up The Planet's Financial System Both the financial crisis of 2008 and the COVID-19 pandemic stressed the financial markets. They resulted in uncertainties, market declines, and negative economic growth. Yet the financial market recovered much faster after the COVID-19 outbreak than the 2008 crisis. The main differences in recovery speeds between the two crises are the timing of the Fed's support, fintech innovations, and technology developments on trading and on general productivity. These factors change the data flow, market dynamics, and recovery speed.
AI in finance broadly refers to the applications of AI techniques in financial businesses. This area has been lasting for decades with both classic and modern AI techniques applied to increasingly broader areas of finance, economy and society. In contrast to either discussing the problems, aspects and opportunities of finance that have benefited from specific AI techniques and in particular some new-generation AI and data science (AIDS) areas or reviewing the progress of applying specific techniques to resolving certain financial problems, this review offers a comprehensive and dense roadmap of the overwhelming challenges, techniques and opportunities of AI research in finance over the past decades. The landscapes and challenges of financial businesses and data are firstly outlined, followed by a comprehensive categorization and a dense overview of the decades of AI research in finance. We then structure and illustrate the data-driven analytics and learning of financial businesses and data. The comparison, criticism and discussion of classic vs. modern AI techniques for finance are followed. Lastly, open issues and opportunities address future AI-empowered finance and finance-motivated AI research.
While this will yield increased profits for companies who can effectively leverage these technologies into new business models, what makes these developments truly revolutionary is their ability to tackle some of the world's most pressing challenges, ranging from education to health. Experts and fellows from the World Economic Forum's Centre for the Fourth Industrial Revolution weigh in with their predictions for the most exciting ways in which new technologies will improve the state of the world in the coming year. When I was born in 1992, I arrived four months premature with every joint in my body bent together as tightly as possible -- from my head being pressed down on my right shoulder all the way down to my toes being pressed against the bottom of my feet and my ankles collapsed against the back of shins like a broken golf club. My twin sister had shared the same environment with me and was 100% healthy. There was only one culprit: a genetic mutation.
When Mr. Dudley took the helm in 2009, the financial crisis had left the New York Fed's reputation as a regulator damaged. The institution had not done enough to address the severe weaknesses at the banks it oversaw, like Citigroup. Early on, Mr. Dudley commissioned a review of the New York Fed's bank supervision department and then overhauled it. But in 2012, JPMorgan Chase, also overseen by the New York Fed, suffered huge trading losses in what was known as the London Whale scandal. The New York Fed was faulted.
By Amitabh Kant The ancient Chinese game Go, which has a very high number of possible moves, was considered almost impossible for a computer to beat humans two years ago. Last year Alpha Go (a Go programme designed by two Go players) beat the best professional Go Player Lee Sedol in a five game match. Machine learning had breached even the bastion of strategic thought. Impossible Foods, a fourth industrial revolution technology company, makes a plant based food that smells, tastes, looks like real meat. It threatens the future of the $90 billion meat industry.