Hessian in the proposed estimator is essential. We will add this result in the future version. The stored parameter is first loaded to the model, and then the gradient for each instance is computed. The comparison is therefore essential to show that our estimator is more suitable for DNNs. We are grateful for a suggestion for clarifying our contribution.

Currently, the United States healthcare system has a "cruel tendency to delay or deny high-quality care to those who are most in need of it but can least afford its high cost," (Shmerling) resulting in rampant disparities in health outcomes throughout the nation. The news of today is riddled with stories of people receiving poor care due to systematic biases present in the modern healthcare system and the effect of the increasingly unaffordable cost of life-saving medication. In order to better understand the degree to which this inequality exists, we investigated which socioeconomic indicators model health outcomes best.

DIGITIMES Research report shows that Taiwan's ICT industry development has shifted from focusing on hardware to hardware/software integration models. The industry is combining big data analysis and AI applications in public IoT to facilitate the development of smart city management. Tools such as IoT, AI, cloud computing, and communications technologies are efficiently integrated with urban infrastructure to ultimately produce economic benefits and improve quality of life. It is estimated that the business opportunities of smart cities will reach $2.6 trillion in 2025, mainly in the Asia Pacific region. This includes sectors such as smart poles, building, parking, monitor, government, transportation, fire protection, water conservancy and WITMED.

With the advancement of technology, artificial intelligence and machine learning (AI/ML) is on the verge of becoming an integral part of every industry, and education is no exception. "With AI being enabled, learning can be customised for students. In the last few years, due to the emergence of machine learning, data has been treated as a prime knowledge resource and it is valued. Simultaneously, tech-based industry has upped the demand for AI/ML rapidly, therefore more students are taking up the course due to good career opportunities," Rajesh Khanna, professor, president, NIIT University, said. Besides courses, it is has been observed that the such technology is being leveraged by ed-tech platforms as an business strategy enhancing tool.

The worlds of AI and BI occupy distinct places in the analytics continuum, which is most often understood with concepts like descriptive analytics, predictive analytics, and prescriptive analytics. Users can leverage descriptive analytics and BI tools to explore what happened in the past, while predictive analytics makes use of ML models trained on real-world data to generate an educated guess about what will happen next. However, the lines separating these two camps are getting more blurry by the month. For years, Gartner has talked about how BI tool vendors are adding more ML and AI capabilities to their wares. In its latest Magic Quadrant for Analytics and BI Platforms, the firm talked about how the next generation of "augmented analytic" products will bring ML and AI to bear on things like data prep, query generation, and insight generation.

If you have seen the Terminator movies, you have probably wondered whether your smart refrigerator will one day become self-aware and plot a world takeover with other artificial intelligence-powered tech. But Ayesha Khanna, co-founder and CEO of artificial intelligence solutions firm ADDO AI, does not see AI that way. Instead, she sees the possibilities in applying AI to make people's lives better, particularly in building smart cities that are people-focused in terms of giving everyone access to basic services and goods. "More than anything else, AI has the potential to democratize access and make growth inclusive," she said in her keynote during the Southeast Asia Development Symposium 2021 organized by the Asian Development Bank in March. Countries need to make sure their cities are livable since each second, five people join the ranks of the middle class, most of them through migration to cities, said Khanna.

Data is at the core of today's digital revolution, but its refinement processes have become the real points of differentiation for enterprises. As companies convert raw data into actionable insights, artificial intelligence signals a burgeoning ecosystem of management models. The current wave of AI startup investment has received $16.5 billion in capital over the three months of the fourth quarter 2020, according to financial analysis from PitchBook Data Inc. The boom is continuing, with the latest figures from International Data Corp. showing a 16.4% year over year growth for the overall AI and machine learning market in 2021, with the AI software platforms market coming in strongest at a predicted compound annual growth rate of 32.7% between 2020 and 2024. AI has already become an essential part of many enterprise technology solutions. The McKinsey & Company Inc. 2020 "The State of AI in 2020″ survey found that 50% of companies had incorporated AI into at least one process, with marketing and sales the most common functions.

Three years ago, Amazon's HQ2 competition showed the world just how many local politicians would happily sell their first-born child if it meant bringing tech jobs to their community. Hundreds of cities and regions made bids to land the everything store's new headquarters, offering all manner of subsidies and perks to one of the most powerful corporations on Earth with the hope that, by the grace of Jeff Bezos, they could one day become the next Seattle. Most of them never had a chance. Amazon largely ignored the offers from midsized contenders, instead selecting New York City and the Virginia suburbs outside of Washington, D.C., places with already-flourishing tech scenes where it would be easy to recruit talent. Although Amazon also promised to put a smaller office in Nashville, the outcome was a stark illustration of how, left to its own devices, the tech industry would likely continue concentrating itself in a handful of already-rich cities.

Dr. Khanna believes that the purpose of #AI is to amplify the human potential. After a 10-year stint in Wall Street developing large scale trading, risk management and data analytics systems, Dr. Khanna pursued her PhD in Information Systems and Innovation at the The London School of Economics and Political Science (LSE). Since then, she has become one of Asia's leading #FemaleEntrepreneurs and #fintechexpert. Under ADDO AI, Dr. Khanna has been a strategic advisor on AI smart cities and fintech to leading corporations and governments. Dr. Khanna also serves on the Board of Infocomm Media Development Authority (IMDA), helping to power its #SmartNation vision.