Generation Artificial Intelligence Research Articles

Beyond Chat-GPT: Next Generation Artificial Intelligence Tools for Nephrologists.

Beyond Chat-GPT: Next Generation Artificial Intelligence Tools for Nephrologists.

Rapid On-Site Histology of Lung and Pleural Biopsies Using Higher Harmonic Generation Microscopy and Artificial Intelligence Analysis

Lung cancer is one of the most prevalent and lethal cancers. To improve health outcomes while reducing health care burden, it becomes crucial to move toward early detection and cost-effective workflows. Currently, there is no method for the on-site rapid histologic feedback on biopsies taken in diagnostic, endoscopic, or surgical procedures. Higher harmonic generation (HHG) microscopy is a laser-based technique that provides images of unprocessed tissue. In this study, we report the feasibility of an HHG portable microscope in the clinical workflow in terms of acquisition time, image quality, and diagnostic accuracy in suspected pulmonary and pleural malignancy. One hundred nine biopsies of 47 patients were imaged and a biopsy overview image was provided within a median acquisition time of 6 minutes after excision. The assessment by pathologists and an artificial intelligence algorithm showed that image quality was sufficient for a malignancy or nonmalignancy diagnosis in 97% of the biopsies, and 87% of the HHG images were correctly scored by the pathologists. HHG is therefore an excellent candidate to provide a rapid pathology outcome on biopsy samples, enabling immediate diagnosis and (local) treatment.

Generation of Artificial Intelligence (AI) during the acquisition of a working profession

Generation of Artificial Intelligence (AI) during the acquisition of a working profession

Regulatory Frameworks for AI-Enabled Medical Device Software in China: Comparative Analysis and Review of Implications for Global Manufacturer.

The China State Council released the new generation artificial intelligence (AI) development plan, outlining China's ambitious aspiration to assume global leadership in AI by the year 2030. This initiative underscores the extensive applicability of AI across diverse domains, including manufacturing, law, and medicine. With China establishing itself as a major producer and consumer of medical devices, there has been a notable increase in software registrations. This study aims to study the proliferation of health care-related software development within China. This work presents an overview of the Chinese regulatory framework for medical device software. The analysis covers both software as a medical device and software in a medical device. A comparative approach is employed to examine the regulations governing medical devices with AI and machine learning in China, the United States, and Europe. The study highlights the significant proliferation of health care-related software development within China, which has led to an increased demand for comprehensive regulatory guidance, particularly for international manufacturers. The comparative analysis reveals distinct regulatory frameworks and requirements across the three regions. This paper provides a useful outline of the current state of regulations for medical software in China and identifies the regulatory challenges posed by the rapid advancements in AI and machine learning technologies. Understanding these challenges is crucial for international manufacturers and stakeholders aiming to navigate the complex regulatory landscape.

Comparing Audiological Outcomes of Conventional and AI-Upgraded Cochlear Implant Speech Processors.

In current age of technology, artificial intelligence is used in the medical field to improve the quality and accuracy in patient care and achieve better clientele satisfaction. The use of artificial intelligence in the field of hearing rehabilitation and cochlear implantation has an immense scope and it enhances the accuracy in placement of electrode array, forecasting site of surgical location and optimization of speech processing. This study aims to compare the audiological outcomes of conventional versus artificial intelligence technology enabled cochlear implant speech processors. Additionally, it compares the individual performance and satisfaction level with use of both types of speech processors. All children who underwent upgradation of their cochlear implant speech processors at a tertiary care cochlear implant centre with artificial intelligence enabled speech processors were included in the study. The comparison of audiological outcomes of conventional versus artificial intelligence integrated speech processors were assessed by using Aided Audiometry, Categories of Auditory Perception Score and Speech Intelligibility Rating scale. Children using the basic model cochlear implant speech processor which was provided at the time of implantation are referred as conventional cochlear implant speech processor user. Their speech processors were subsequently upgraded with current generation artificial intelligence integrated speech processors which is referred here as artificial intelligence upgraded cochlear implant speech processor. During the study, a total of thirty-four (34) patients underwent upgradation of cochlear implant speech processors. The mean categories of auditory perception score were 11.58 and 11.94 using conventional and artificial intelligence upgraded speech processor respectively. The mean speech intelligibility rating score was 4.5 and 4.6 respectively. The audiological outcomes of conventional speech processors are comparable with those using artificial intelligence enabled speech processors. However, the clientele satisfaction in respect to quality of sound, ease of listening in difficult listening environment, smart connectivity options for both phone and television is available and better with the artificial intelligence enabled cochlear implant speech processor. This also has the advantages of auto switching of programming with change in ambient noise, better signal to noise ratio and better 360* hearing.

FIWARE-Compatible Smart Data Models for Satellite Imagery and Flood Risk Assessment to Enhance Data Management

The increasing rate of adoption of innovative technological achievements along with the penetration of the Next Generation Internet (NGI) technologies and Artificial Intelligence (AI) in the water sector are leading to a shift to a Water-Smart Society. New challenges have emerged in terms of data interoperability, sharing, and trustworthiness due to the rapidly increasing volume of heterogeneous data generated by multiple technologies. Hence, there is a need for efficient harmonization and smart modeling of the data to foster advanced AI analytical processes, which will lead to efficient water data management. The main objective of this work is to propose two Smart Data Models focusing on the modeling of the satellite imagery data and the flood risk assessment processes. The utilization of those models reinforces the fusion and homogenization of diverse information and data, facilitating the adoption of AI technologies for flood mapping and monitoring. Furthermore, a holistic framework is developed and evaluated via qualitative and quantitative performance indicators revealing the efficacy of the proposed models concerning the usage of the models in real cases. The framework is based on the well-known and compatible technologies on NGSI-LD standards which are customized and applicable easily to support the water data management processes effectively.

Development of New Generation of Artificial Intelligence in China: When Beijing’s Global Ambitions Meet Local Realities

ABSTRACT How did China become one of the leaders in AI development, and will China prevail in the ongoing AI race with the US? Existing studies have focused on the Chinese central government’s role in promoting AI. Notwithstanding the importance of the central government, a significant portion of the responsibility for AI development falls on local governments’ shoulders. Local governments have diverging interests, capacities and, therefore, approaches to promoting AI. This poses an important question: How do local governments respond to the central government’s policies on emerging technologies, such as AI? This article answers this question by examining the convergence or divergence of central and local priorities related to AI development by analysing the central and local AI policy documents and the provincial variations by focusing on the diffusion of the New Generation Artificial Intelligence Development Plan (NGAIDP) in China. Using a unique dataset of China’s provincial AI-related policies that cite the NGAIDP, the nature of diffusion of the NGAIDP is examined by conducting content analysis and fuzzy-set Qualitative Comparative Analysis (fsQCA). This study highlights the important role of local governments in China’s AI development and emphasises examining policy diffusion as a political process.

이미지 자동 생성 인공지능의 원리와 현황

This study identifies the principles of image generation artificial intelligence, examines its performance and limitations, and examines the innovative changes that have occurred in image production methods. Specifically, we reveal the structure of the Generative Adversarial Network (GAN), trace its technical improvement process in detail, and classify the types of subsequent models developed later. The tasks performed by GAN’s successor models are diverse. GAN is steadily evolving, completing amazing tasks that were impossible with existing generative models, such as high-resolution image generation, image substitution such as drawings and photos, and face synthesis. The principles of GAN are, first, data learning through adversarial competition between generator and discriminator, second, calculation of accurate probability distribution through Maximum Likelihood Estimation, and third, calculation of fine features of images through deep convolution structure. The most important characteristic of GAN as a generative model is its ability to create realistic images similar to photographs. Humans have been producing images using hands and tools, but with the invention of photography, humans began producing images using camera devices. Now, generative artificial intelligence is becoming another means of image production as technology continues to improve rapidly.

Inisiasi Pembentukan Angkatan Siber dan Digital dalam Organisasi Tentara Nasional Indonesia

In the era of digital transformation, every country in the world must be able to adapt and adopt these changes as a strategy to strengthen national defense because cyberspace in relation to international relations can be a source of various potential threats, vulnerabilities, and insecurity in the international order. China recognized the importance of AI in shaping the future global economic, military and geopolitical environment, and launched the "Next Generation Artificial Intelligence Development Plan." which aims to become a global leader in AI by 2030. The research method used is prescriptive analysis and qualitative data analysis. Based on the results of the study, there are 4 (four) important points to realize this, namely the alignment of regulations related to cyber and digital in Indonesia with the initiation with revisions both in the form of proposed new articles and / or reviews in Law Number 34 of 2004 concerning the Indonesian National Army, then digital infrastructure development in Indonesia, digital literacy development in Indonesia, and appropriate personnel mobilization strategies based on the state of human resources in Indonesia.

Brain-Inspired Learning, Perception, and Cognition: A Comprehensive Review.

The progress of brain cognition and learning mechanisms has provided new inspiration for the next generation of artificial intelligence (AI) and provided the biological basis for the establishment of new models and methods. Brain science can effectively improve the intelligence of existing models and systems. Compared with other reviews, this article provides a comprehensive review of brain-inspired deep learning algorithms for learning, perception, and cognition from microscopic, mesoscopic, macroscopic, and super-macroscopic perspectives. First, this article introduces the brain cognition mechanism. Then, it summarizes the existing studies on brain-inspired learning and modeling from the perspectives of neural structure, cognitive module, learning mechanism, and behavioral characteristics. Next, this article introduces the potential learning directions of brain-inspired learning from four aspects: perception, cognition, understanding, and decision-making. Finally, the top-ten open problems that brain-inspired learning, perception, and cognition currently face are summarized, and the next generation of AI technology has been prospected. This work intends to provide a quick overview of the research on brain-inspired AI algorithms and to motivate future research by illuminating the latest developments in brain science.

A Double-Direction Cognitive Interaction Security Architecture for CPSS: A Case Study

With the development of big data analytics, new generation artificial intelligence, and other technologies, Cyber-Physical-Social Systems (CPSSs) have gradually come into people’s view. However, the complex integration brings about more complex security issues, especially the risks and problems in double-directional cognition triggered by the interactive integration of humans and Artificial Intelligence (AI). Therefore, based on the security analysis architecture and methodology for CPSSs, this paper carries out a case study with the help of the power operation and maintenance (O&M) system, which is a typical CPSS, to verify the validity of the relevant architecture and methodology and to propose reasonable security protection measures.

Artificial Intelligence Applications in Prostate Cancer Management: Success Stories and Future Ahead

Summary This review summarizes and provides an outlook for developments around the use of artificial intelligence (AI) in the diagnosis and treatment of prostate cancer. We searched existing literature on the design and development of new AI-based systems using a non-systematic approach. Areas targeted by AI include the diagnosis, Gleason scoring, biomarker identification, and prognosis of prostate cancer (PCa) from digitised histopathology, segmentation, detection, and classification of PCa from magnetic resonance imaging, AI applications for prostate ultrasound, AI in radiotherapy for PCa including synthetic computed tomography generation and treatment planning and AI in measuring and improving surgical outcomes and education. Recent work has focused on deep learning techniques. Algorithms have achieved results that outperform or are similar to those of experts. However, few proposed algorithms are clinically oriented and can be practically deployed. Future progress needs to be made in data availability, prospective evaluation, regulation, responsible AI, explainability, and practical aspects of clinical deployment.

Технологические инновации и применение искусственного интеллекта в развитии мирохозяйственных процессов: опыт стран БРИКС

The aim of the study is to analyze technological innovation in the field of artificial intelligence in the global economy with a focus on the experience of the BRICS countries. In the course of the study, the authors set the following objectives: to assess the impact of AI implementation on the economic and social growth of these countries; the positions of the BRICS countries in the world rankings in the field of artificial intelligence (Global AI Index and Stanford AI Index); and the participation of the BRICS countries in the application of generative AI. The results of the study have allowed to assess the impact of technological innovation and application of artificial intelligence on the economic and social growth of the BRICS countries as positive, especially on China, which has realized significant progress in the field of artificial intelligence over the past 10 years, as well as on India’s breakthrough over the past 2 years in the use of generative AI. China, based on sound long-term strategic planning and large financial injections, is already breaking into a leading position in the world 5 years after adopting the fundamental “Next Generation Artificial Intelligence Development Plan” in 2017. In 2021, Chinese researchers ranked first in the world in terms of cited publications in Q1 peer-reviewed scientific journals (top 25 % of journals). Chinese tech giants are recording a sharp rise in AI publications in 2022, outpacing university researchers on the index. Since 2021, India has significantly increased its position in the leading AI ratings and is becoming a world leader in the application of generative AI. The analysis of the level of development of AI technologies in the BRICS countries conducted within the framework of this article shows that, having all the necessary resources for the successful implementation of AI technologies, in the near future the BRICS countries are planning to apply AI technologies on a larger scale in medicine, education, finance and agriculture, which will significantly improve the economic performance of the state.

A Study on Cubist Art Makeup Design Creation Using Artificial Intelligence Based Image Generation Model

This study extracted six works from representative artists of Cubism and analyzed the characteristics and expression techniques of the works to construct text prompts. Then, using Bing Image Creator model, an artificial intelligence based image generation model, art makeup design images were generated. The art makeup design created by the image generation model shows original style and expression compared to other studies, and has practicality and completeness that can be implemented as actual art makeup. The aim is to present a new way of creation and result through the integration of AI technology and art. In addition, by analyzing the creation process and result, the aim is to present a new perception and possibility of diversity and expandability of art makeup. This method can increase the accessibility and efficiency of art makeup, and provide new ideas and inspiration to creators. In conclusion, this study is a useful study that shows what role and possibility image generation artificial intelligence model has in the field of art, and it is expected to provide a basis for more in-depth and diverse studies in the future.

Unveiling the Future Navigating Next-Generation AI Frontiers and Innovations in Application

As a representative of the information revolution, the Internet began in the 1960s when ARPANET was born, and after decades of development and evolution, today it has formed a global information connection and interaction network. The greatest value of the Internet is that everyone can communicate and cooperate in real time across the limitations of time and space, which greatly improves the efficiency of group communication and collaboration, and then changes the organization and operation mode of people's work, business and social activities, and ultimately promotes the advancement of human social productivity. Therefore, the major research program of interpretable and universal next generation artificial intelligence methods faces the major strategic needs of the country in the development of artificial intelligence, takes the basic science issues of artificial intelligence as the core, develops the new method system of artificial intelligence, promotes the basic research and personnel training of artificial intelligence in China, and supports China's leading position in the new round of international scientific and technological competition. In this paper, the next generation of artificial intelligence innovation and application space are summarized, and the application of advanced algorithms is analyzed.

첨단 과학 기술의 국제정치

Why do states cooperate on emerging and critical technologies? The existing studies tend to focus on technological competition between great powers, such as the United States and China, drawing on securitization or perspectives of realism. This research, however, sheds light on why states cooperate on such high-tech areas and argues that states seek technological innovation in order to ensure the national security and industrial competitiveness, and such innovation is more likely to be promoted through the international division of labor that accompanies specialization and standardization across cooperating states. International high-tech cooperation also often involves mechanisms that are conducive to thwarting the technological development of adversaries. The plausibility case study examines incipient US-ROK cooperation initiatives in high-tech areas, such as next generation networks and artificial intelligence technologies. This research makes the theoretical contribution to the field, simultaneously urging policymakers to ponder why they have to cooperate and what to aim in their high-tech cooperation strategy.

High precision of sign language recognition based on In2O3 transistors gated by AlLiO solid electrolyte

In recent years, the synaptic properties of transistors have been extensively studied. Compared with liquid or organic material-based transistors, inorganic solid electrolyte-gated transistors have the advantage of better chemical stability. This study uses a simple, low-cost solution technology to prepare In2O3 transistors gated by AlLiO solid electrolyte. The electrochemical performance of the device is achieved by forming a double electric layer and electrochemical doping, which can mimic basic functions of biological synapses, such as excitatory postsynaptic current, paired-pulse promotion, and spiking time-dependent plasticity. Furthermore, complex synaptic behaviors such as Pavlovian classical conditioning is successfully emulated. With a 95% identification accuracy, an artificial neural network based on transistors is built to recognize sign language and enable sign language interpretation. Additionally, the handwriting digit’s identification accuracy is 94%. Even with various levels of Gaussian noise, the recognition rate is still above 84%. The above findings demonstrate the potential of In2O3/AlLiO TFT in shaping the next generation of artificial intelligence.

Hyper Progressive Single Shot Detector; HPSSD

Studies into intelligent production and the implementation of smart factories have been promising in recent years, first generation artificial intelligence is out and all major companies are trying to integrate some form of machine learning into their systems. In the field of Machine vision, promising architectures have been built to strengthen the literature, this paper proses the development of a Neural Network called HPSSD (Hyper Progressive Single Shot Detector) to serve as the computational backbone for Machine vision applications specifically for Inspection. HPSSD is a Single Shot Detector that was built on the basis of a RCBAM, an MDCM, and a PAM module. The improvements shown after the development of HPSSD shows that there is no extent that machine Learning cannot take us through the Lens of Machine Vision. The tests demonstrates encouraging outcomes and enhancing the inspection accuracy in intelligent workshops.

Exploring large language model for next generation of artificial intelligence in ophthalmology

In recent years, ophthalmology has advanced significantly, thanks to rapid progress in artificial intelligence (AI) technologies. Large language models (LLMs) like ChatGPT have emerged as powerful tools for natural language processing. This paper finally includes 108 studies, and explores LLMs’ potential in the next generation of AI in ophthalmology. The results encompass a diverse range of studies in the field of ophthalmology, highlighting the versatile applications of LLMs. Subfields encompass general ophthalmology, retinal diseases, anterior segment diseases, glaucoma, and ophthalmic plastics. Results show LLMs’ competence in generating informative and contextually relevant responses, potentially reducing diagnostic errors and improving patient outcomes. Overall, this study highlights LLMs’ promising role in shaping AI’s future in ophthalmology. By leveraging AI, ophthalmologists can access a wealth of information, enhance diagnostic accuracy, and provide better patient care. Despite challenges, continued AI advancements and ongoing research will pave the way for the next generation of AI-assisted ophthalmic practices.

Study on the Copyright Protection of Artificial Intelligence Generated Objects

With the emergence of a new round of scientific and technological revolution characterized by intelligence, China has made rapid progress in the field of artificial intelligence. However, this new concept of artificial intelligence has not yet been fully integrated into the existing legal system, leading to legal dilemmas and systemic obstacles such as unclear attribution of the work, uncertain subject of the right, and unclear path of protection for the content generated by it. The traditional copyright protection model, concerning the generation of artificial intelligence, shows obvious maladaptation in terms of copyright generation, protection period, and content. Hence, there is a need to explore a copyright protection model suitable for artificial intelligence, namely the neighboring rights protection model, while considering relevant legislative practices from other countries dealing with AI-generated content. This paper aims to investigate the neighboring right protection model, which is an adaptable copyright protection model for AI-generated objects, and to draw insights from overseas legislative practices on AI-generated objects.