Objectives: The integration of Artificial Intelligence (AI) in healthcare promises to revolutionize patient care, diagnostics, and treatment protocols. Collaborative efforts among healthcare systems, research institutions, and industry are pivotal to leveraging AI's full potential. This study aims to characterize collaborative networks and stakeholders in AI healthcare initiatives, identify challenges and opportunities within these collaborations, and elucidate priorities for future AI research and development. Methods: This study utilized data from the Chinese Society of Radiology and the Chinese Medical Imaging AI Innovation Alliance. A national cross-sectional survey was conducted in China (N = 5,142) across 31 provincial administrative regions, involving participants from three key groups: clinicians, institution professionals, and industry representatives. The survey explored diverse aspects including current AI usage in healthcare, collaboration dynamics, challenges encountered, and research and development priorities. Results: Findings reveal high interest in AI among clinicians, with a significant gap between interest and actual engagement in development activities. Despite the willingness to share data, progress is hindered by concerns about data privacy and security, and lack of clear industry standards and legal guidelines. Future development interests focus on lesion screening, disease diagnosis, and enhancing clinical workflows. Conclusion: This study highlights an enthusiastic yet cautious approach toward AI in healthcare, characterized by significant barriers that impede effective collaboration and implementation. Recommendations emphasize the need for AI-specific education and training, secure data-sharing frameworks, establishment of clear industry standards, and formation of dedicated AI research departments.

To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, this report presents a comprehensive assessment of their frontier risks. Drawing on the E-T-C analysis (deployment environment, threat source, enabling capability) from the Frontier AI Risk Management Framework (v1.0) (SafeWork-F1-Framework), we identify critical risks in seven areas: cyber offense, biological and chemical risks, persuasion and manipulation, uncontrolled autonomous AI R\&D, strategic deception and scheming, self-replication, and collusion. Guided by the "AI-$45^\circ$ Law," we evaluate these risks using "red lines" (intolerable thresholds) and "yellow lines" (early warning indicators) to define risk zones: green (manageable risk for routine deployment and continuous monitoring), yellow (requiring strengthened mitigations and controlled deployment), and red (necessitating suspension of development and/or deployment). Experimental results show that all recent frontier AI models reside in green and yellow zones, without crossing red lines. Specifically, no evaluated models cross the yellow line for cyber offense or uncontrolled AI R\&D risks. For self-replication, and strategic deception and scheming, most models remain in the green zone, except for certain reasoning models in the yellow zone. In persuasion and manipulation, most models are in the yellow zone due to their effective influence on humans. For biological and chemical risks, we are unable to rule out the possibility of most models residing in the yellow zone, although detailed threat modeling and in-depth assessment are required to make further claims. This work reflects our current understanding of AI frontier risks and urges collective action to mitigate these challenges.

This article explores the concept of technological singularity and the factors that could accelerate or hinder its arrival. The butterfly effect is used as a framework to understand how seemingly small changes in complex systems can have significant and unpredictable outcomes. In section II, we discuss the various factors that could hasten the arrival of technological singularity, such as advances in artificial intelligence and machine learning, breakthroughs in quantum computing, progress in brain-computer interfaces and human augmentation, and development of nanotechnology and 3D printing. In section III, we examine the factors that could delay or impede the arrival of technological singularity, including technical limitations and setbacks in AI and machine learning, ethical and societal concerns around AI and its impact on jobs and privacy, lack of sufficient investment in research and development, and regulatory barriers and political instability. Section IV explores the interplay of these factors and how they can impact the butterfly effect. Finally, in the conclusion, we summarize the key points discussed and emphasize the importance of considering the butterfly effect in predicting the future of technology. We call for continued research and investment in technology to shape its future and mitigate potential risks.

The Global AI Research Agenda recommends principles, priorities, and practices for AI research and development to advance safe, secure, and trustworthy development of AI systems in international contexts. It aims to strengthen collaboration in researching the interactions between individuals, communities, and society with AI systems, foster innovation, and support equitable access to the benefits of AI. The conclusions presented serve as a starting point to align a global research vision, in which research communities continuously assess the state of AI research, review current publications addressing the presented priorities, and identify gaps to guide future research, focusing on global needs. The document contains a section outlining research priorities to advance safe, secure, inclusive, and trustworthy AI.

Deputy Secretary of Defense Kathleen Hicks addressed the plan and how the U.S. will continue to counter the rising aggression from China. The Pentagon has started to assess the possibility of developing an artificial intelligence (AI)-powered fleet of drones and autonomous systems that officials argue will allow the U.S. to compete with and counter threats from China. We are not seeking to be at war, but we have to be able to get this department to move with that same kind of urgency because the PRC isn't waiting," Kathleen Hicks, the deputy secretary of defense, said during an interview earlier this week with The Wall Street Journal. Hicks spoke about the potential uses of such an AI fleet during a speech on Wednesday, revealing the department would spend hundreds of millions of dollars on the project, aiming to produce thousands of systems for use over land, air and sea ready for first deployment within two years. China has focused heavily on AI research and development, producing ...

As the world continues to advance technologically, there has been a growing concern about the impact of Artificial Intelligence (AI) on society. This concern is particularly relevant in third-world countries like Zimbabwe, where many people are already struggling to make ends meet. It is important to understand what AI is and how it works. AI refers to the development of computer systems that can perform tasks that would normally require human intelligence, such as learning, problem-solving, and decision-making. These systems use algorithms and data to analyze information and make predictions or recommendations based on that analysis. One of the main concerns about AI is that it could lead to job losses as machines replace human workers.

OpenAI has been known for its mission to develop and promote artificial intelligence in a safe and ethical manner. However, the organization recently announced that it will no longer be open sourcing its AI code. This decision has raised concerns about the potential dangers of limiting access to AI research and development. One of the biggest dangers of not open sourcing AI code is the potential for decreased transparency and accountability. Open sourcing code allows other researchers to verify the accuracy and safety of AI models, which can lead to improvements and prevent the deployment of harmful systems. Without open sourcing, there is less transparency and accountability for the development of AI models, which could lead to unintended consequences and the deployment of unsafe AI systems.

The Union Budget 2023, recently presented by the Indian government, has big plans for the future of Artificial Intelligence (AI) in the country. The government has set aside a substantial amount of funding for AI research and development, and has also introduced several new initiatives aimed at promoting the growth and development of the AI industry in India. One of the major initiatives announced in the budget is the setting up of a National AI Portal. This portal will serve as a single point of reference for all AI-related information and resources in the country. It will provide a platform for researchers, developers, and businesses to share their work and collaborate on AI projects.

Today, the National Artificial Intelligence Research Resource (NAIRR) Task Force released its final report, a roadmap for standing up a national research infrastructure that would broaden access to the resources essential to artificial intelligence (AI) research and development. While AI research and development (R&D) in the United States is advancing rapidly, opportunities to pursue cutting-edge AI research and new AI applications are often inaccessible to researchers beyond those at well-resourced companies, organizations, and academic institutions. A NAIRR would change that by providing AI researchers and students with significantly expanded access to computational resources, high-quality data, educational tools, and user support--fueling greater innovation and advancing AI that serves the public good. "AI advances hold tremendous promise for tackling our hardest problems and achieving our greatest aspirations," said Arati Prabhakar, OSTP Director and Assistant to the President for Science and Technology. "We will only realize this potential when many more kinds of researchers have access to the powerful capabilities that underpin AI advances."

Today, the National Artificial Intelligence Research Resource (NAIRR) Task Force released its final report, a roadmap for standing up a national research infrastructure that would democratize access to the resources essential to artificial intelligence (AI) research and development. Established by the National AI Initiative Act of 2020, the NAIRR Task Force is a federal advisory committee. Co-chaired by the U.S. National Science Foundation and the White House Office of Science and Technology Policy, the Task Force has equal representation from government, academia, and private organizations. Following its launch in June 2021, the Task Force embarked on a rigorous, open process that culminated in this final report. This process included 11 public meetings and two formal requests for information to gather public input.