This paper introduces ACC-NVS1, a specialized dataset designed for research on Novel View Synthesis specifically for airborne and ground imagery. Data for ACC-NVS1 was collected in Austin, TX and Pittsburgh, PA in 2023 and 2024. The collection encompasses six diverse real-world scenes captured from both airborne and ground cameras, resulting in a total of 148,000 images. ACC-NVS1 addresses challenges such as varying altitudes and transient objects. This dataset is intended to supplement existing datasets, providing additional resources for comprehensive research, rather than serving as a benchmark.

Global executives are increasingly worried about the long term viability of their businesses, a pre-Davos survey by PricewaterhouseCoopers showed, with pressures mounting from generative artificial intelligence and climate disruption. Some 45% of more than 4,700 global CEOs surveyed do not believe their businesses will survive, barring significant changes, in the next 10 years, the "Big Four" auditor said. "There's the 55% who think they don't have to change radically, and I would argue that's a little naive because the world is changing so fast around them," PwC Global Chairman Bob Moritz told the Reuters Global Markets Forum (GMF) ahead of the World Economic Forum's annual meeting in Davos.

That is to say, we're in the dot-com boom, circa 2000. Many companies will go bust. It may take years before we see this era's Facebook (now Meta), Twitter (now X), or TikTok emerge. "People are reluctant to imagine what could be the future in 10 years, because no one wants to look foolish," says Alison Smith, head of generative AI at Booz Allen Hamilton, a technology consulting firm. "But I think it's going to be something wildly beyond our expectations."

As artificial intelligence (AI) is integrated into various services and systems in society, many companies and organizations have proposed AI principles, policies, and made the related commitments. Conversely, some have proposed the need for independent audits, arguing that the voluntary principles adopted by the developers and providers of AI services and systems insufficiently address risk. This policy recommendation summarizes the issues related to the auditing of AI services and systems and presents three recommendations for promoting AI auditing that contribute to sound AI governance. Recommendation1.Development of institutional design for AI audits. Recommendation2.Training human resources for AI audits. Recommendation3. Updating AI audits in accordance with technological progress. In this policy recommendation, AI is assumed to be that which recognizes and predicts data with the last chapter outlining how generative AI should be audited.

Welcome to the sixth edition of the AI Index Report! This year, the report introduces more original data than any previous edition, including a new chapter on AI public opinion, a more thorough technical performance chapter, original analysis about large language and multimodal models, detailed trends in global AI legislation records, a study of the environmental impact of AI systems, and more. The AI Index Report tracks, collates, distills, and visualizes data related to artificial intelligence. Our mission is to provide unbiased, rigorously vetted, broadly sourced data in order for policymakers, researchers, executives, journalists, and the general public to develop a more thorough and nuanced understanding of the complex field of AI. The report aims to be the world's most credible and authoritative source for data and insights about AI.

The AI field took a turn with the release of powerful Generative Artifical Intelligence (AI) models, and as a result, the world is seeing the automation of some skills around creativity and imagination sooner than many expected. For some organizations, Generative AI holds valuable potential for higher order opportunities, like new services and business models. Deloitte offers a method for selecting Generative AI use cases, as well as some next steps for business leaders in the Age of With . Generative AI has captured attention in global media and the public square, prompting questions and discussions around this transformative technology. Businesses, research organizations, and even lay users are experimenting with Generative AI, and given the excitement and interest, it is important to look more closely at the potential capabilities and implications for business.

In the following sections, we discuss some of the ways that the Accenture Velocity team has been using CodeWhisperer in more detail. CodeWhisperer helps developers unfamiliar with AWS to ramp up faster on projects that use AWS services. New developers in Accenture were able to write code for AWS services such as Amazon Simple Storage Service (Amazon S3) and Amazon DynamoDB. In a short amount of time, they were able to be productive and contribute to the project. CodeWhisperer assisted developers by providing code blocks or line-by-line suggestions.

AI has exploded in popularity in recent years, to the point where it's no longer considered a luxury in the business world, but a necessity. A PricewaterhouseCoopers (PwC) study revealed that the adoption of AI will fuel a 14 percent increase in the global GDP by 2030, representing an additional $15.7 trillion surge to the global economy.1 Businesses using AI solutions are discovering new ways to tap into vast amounts of data to get clear insights and accelerate innovation. Thanks to advancements in graphics processing unit (GPU) computational power and the availability of tech services through cloud marketplaces, AI is now more accessible than ever. As companies look to do more with less, AI will play an increasingly critical role--particularly generative AI, a category of AI algorithms that generate new outputs based on data. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI can analyze large data sets and create entirely new content in a variety of media formats--including text, images, audio, and data--based on what's described in the input.

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