World Of Artificial Intelligence Research Articles

Research on Zero knowledge with machine learning

This research paper explores the intersection of zero-knowledge proofs (ZKPs) and machine learning (ML), presenting a comprehensive overview of recent advancements, applications, and challenges in this fast growing area. The jointers of ZKPs and ML techniques shall go a meter further to fuse privacy, security, and integrity in a number of solutions, which include forming of groups for data sharing and safe machine learning. Through the investigation of the well-respected sites in that area and also the thorough description of formulas and their experimental outcome, this paper looks for the clarification of the current state of affairs and the possible future directions of ZKPs in the AI world. By inserting the verification mechanism of ZKPs into machine learning ecosystem, it allows devising novel solutions for the problems of privacy and confidentiality that have for long been not solved. With this approach, the concatenation of parties collectively performs the process of dealing with private inputs without revealing any of these data and this, in return, opens the possibilities of secure multi-party computation. Furthermore, ZKPs protect data sharing as it gives people the opportunity to construct confidential data and share them to model training without compromising any one’s private details. Being a part of the dynamic conversations, which focus on the game-changing capacity of transparent zero-knowledge proofs (ZKPs), this paper brings the role of ZKPs in preserving the confidentiality and integrity of artificial intelligence (AI) applications into the centre of attention. As scientists still fight to improve protocols and circumvent computational complications, ZKPs are likely to establishment as critical tools in the effort to increase ML systems in the digital sphere.

Brave New World of Artificial Intelligence: Its Use in Antimicrobial Stewardship-A Systematic Review.

Antimicrobial resistance (AMR) is a growing public health problem in the One Health dimension. Artificial intelligence (AI) is emerging in healthcare, since it is helpful to deal with large amounts of data and as a prediction tool. This systematic review explores the use of AI in antimicrobial stewardship programs (ASPs) and summarizes the predictive performance of machine learning (ML) algorithms, compared with clinical decisions, in inpatients and outpatients who need antimicrobial prescriptions. This review includes eighteen observational studies from PubMed, Scopus, and Web of Science. The exclusion criteria comprised studies conducted only in vitro, not addressing infectious diseases, or not referencing the use of AI models as predictors. Data such as study type, year of publication, number of patients, study objective, ML algorithms used, features, and predictors were extracted from the included publications. All studies concluded that ML algorithms were useful to assist antimicrobial stewardship teams in multiple tasks such as identifying inappropriate prescribing practices, choosing the appropriate antibiotic therapy, or predicting AMR. The most extracted performance metric was AUC, which ranged from 0.64 to 0.992. Despite the risks and ethical concerns that AI raises, it can play a positive and promising role in ASP.

Impact of Artificial Intelligence on New Global Order: A Nepalese Security Perspective

The novelty of Artificial Intelligence (AI) and nascent geo-tech interests of powerful countries have largely influenced foreign policy, while ‘techno-geopolitics’ and the emergence of the ‘AI world order’ have constantly challenged the world order milieu. The changing global power dynamics, including the escalating Russia-Ukraine war, the Israel-Palestine conflict and China’s rising clout in tech and diplomatic spheres have induced specific geo-political challenges to the US-led global order. In this context, this research primarily unfolds whether the remaking of new global order can fundamentally be signified by the end of bipolar or unipolar world order, while the advancement of AI technology and geo-tech interests of tech powers have contributed to a remaking of new global order. As the powerful countries have fundamentally concentrated on marshaling AI in foreign policy, both AI and foreign policy have been closely interlinked. This research aims to explore the impact of AI on new global order and corresponding security concerns, particularly Nepalese security concerns. Since both AI and the new global order are relatively vast fields, this research focuses on tech foreign policy that is directly linked with the balance of power and the corresponding international order. This study adopts an analytical descriptive research method. It relates AI ethics and global tech concerns, considering the global need, beginning with the notion of multilateral tech diplomacy, and inquiring whether the tech foreign policy is truly functional. Despite varying challenges to the new global order, rational ‘geopolitical balancing’ and techno-economic cooperation in ‘better-functioning relations’ with immediate neighbors and other superpowers drive Nepal’s security architecture.

Artificial Intelligence System-based Chatbot as a Hotel Agent

Background: The idea of being able to communicate with an electronic device in a similar way as human beings is now the new big thing in the world of Artificial Intelligence. The fusion of AI and Cloud computing has given rise to a new technology that can understand and learn conversations in the natural language used by humans. In this Era, where automation is taking over the world, the invention of smart chat-bots has made it possible to imitate humans in various applications to reduce human effort and thereby perform at maximum efficiency. Objective: The objective is to replace a human-constituted assignment with an error-free technology. By using the intent modular concept of dialog flow, the role of the hotel receptionist is eliminated. The purpose of using an API of Google Cloud Platform namely Dialog flow in this project is to conveniently perform NLP (Natural Language Processing) i.e. training a robot to perform according to our instructions and understand the natural language spoken by humans and the hardware attached to the device enables the listening and speaking of the smart bot. Methods: Utilization of Dialog flow Enterprise Edition to make “Hotel Agent” with the use of intents comprising of a general hotel glossary. Results: Dialog flow as a natural language processing recognizer running on the processor Raspberry pie with Python as its constituent language. Finally, it is connected to Google Assistant to make it publicly available in the execution phase. Conclusion: The successful testing of the Artificial Intelligence-based device has ensured that manpower could be conveniently replaced by Machine Intelligence by using knowledge-based databases.

Artificial Intelligence: A forward-looking vision for a better future for humanity Analytical theoretical study

The world is witnessing a tremendous Revolution in terms of Technological Development, entry into the world of Artificial Intelligence, and the possession of modern technologies in automation and algorithms that are useful for computers and robots, which is certainly necessary and indispensable, as; Progress and development in various fields require the necessity of relying on artificial intelligence technologies and its multiple uses. Despite the advantages of using artificial intelligence, it faces many challenges and risks that face humans as a result of these uses. They are not limited to the various aspects (economic, social, and media) that affect humans from Where only the labor market and unemployment rates, but there are also other risks according to the nature and specificity of the social and cultural context of our Arab societies that must be taken into account when entering the world of artificial intelligence? All of these reasons made the researcher address the research issue and the current research topic This Research aims to Learn the Science of Artificial Intelligence, and provide a forward-looking vision of what a better future for humanity may look like in the future. This is because it is a modern Science that has gained great Importance in recent years for its many applications in various fields. It also aims to identify its importance, benefits, types and concepts associated with it, and reveal the areas of use of Artificial Intelligence applications, how to use them, and the challenges facing its use. This research was devoted to studying the reality of artificial intelligence. In light of the developments to identify the challenges and address them automatically, to develop a future vision about artificial intelligence in the twenty-first century, the research was entitled: Artificial Intelligence: A forward-looking vision for a better future for humanity Keywords:) A Proposed Vision - Artificial Intelligence - Forward-looking vision - Applications of Artificial Intelligence – Technology (

Investigation of Radial and Tangential Stresses Occurring in Epoxy (T300) Material Disc with Different Methods

In this study, a composite disc with Epoxy (T300) material was considered. It is possible to come across different studies to examine the stress field on disks rotating or stationary under thermal loads. Discs play a vital role in the assembly of machine parts in industry. Knowing the behavior of machine parts against temperature allows very good data to be transferred to today’s artificial intelligence world. Epoxy materials are very important today. Epoxies are made up of very strong fibers. They are used in unmanned aerial vehicles, spacecraft and the rocket industry. In addition, their maximum and minimum hardening properties, good adhesion properties and wear resistance are also quite high. In this study, an Epoxy disk (T300) subjected to linear increasing temperature was modeled. The stresses obtained on the discs were determined by different methods. As can be seen from the results, for a temperature of 150 °C, the average stress, strain and compression occurring sequentially in the inner and outer regions of the disk acts as 215.06 and –443.90 MPa. According to the results obtained, it was concluded that there are parallel increases in stresses as the temperature increases, and this can be proven by other different studies in the literature.

Transformative Horizons: Navigating the Evolution of HR through AI and Cloud Technologies

Artificial intelligence (AI) and cloud computing are transforming human resources (HR) throughout the digital revolution. This white paper examines how these technologies are converging and how they affect HR practices. First, the report charts the evolution of HR technology from manual methods to complex digital ecosystems. This essay stresses the vital moment when AI and cloud technologies drive HR innovation, altering talent acquisition, employee engagement, performance management, and other areas. This article discusses AI’s position in HR and its applications throughout HR. Real-world case studies show how AI-powered recruitment improves candidate screening and predictive analytics informs HR decisions. Cloud HR solutions, fundamental to modern HR technology, are targeted. This article discusses cloud-based HR systems’ versatility, cost savings, and ability to adapt to changing demands. Additionally, this section features companies that have improved HR procedures using cloud technology. Cloud platforms provide AI-powered HR solutions, according to the paper. Addressing bias and ensuring AI fairness are ethical considerations in the analysis. It also stresses cloud-based HR system data privacy and security. HR experts are crucial to this transformation. The paper discusses HR teams’ changing roles in an AI and cloud-centric HR world and offers upskilling and reskilling techniques to maximise HR functions’ strategic value.

A basic introduction to artificial intelligence for eye care professionals

Australia based researchers and academics, Md Mahmudul Hasan, Erik Meijering, Arcot Sowmya, Michael Kalloniatis and Jack Phu, offer an introduction to the world of artificial intelligence. The authors describe and define key terminologies and processes, helping ECPs understand this new and rapidly changing field. The article forms the first of a short series looking at AI and its growing role within eye care

Tutors� Column: The People Make the Place: Reminding Tutors of Their Value in a World of Artificial Intelligence

Tutors� Column: The People Make the Place: Reminding Tutors of Their Value in a World of Artificial Intelligence

Transforming Education in the World of Artificial Intelligence

Introduction: Artificial Intelligence (AI) and Machine Learning (ML) are key drivers of innovation and growth among all industries, and the education sector is no exemption. AI is considered as a powerful tool to facilitate new examples for technological development, instructional design and educational research that are otherwise not possible to develop in the traditional education techniques. With the development in information processing and computing techniques, artificial intelligence has been widely applied in educational practices (Artificial Intelligence in Education; AIEd), such as teaching robots, human-computer interactions intelligent tutoring systems, learning analytics dashboards and adaptive learning systems. It has the ability to maximize both teaching and learning, helping the education sector to evolve for better thus benefitting students and teachers both

Advanced neuromonitoring powered by ICM+ and its place in the Brand New AI World, reflections at the 20th anniversary boundary

IntroductionAdoption of the ICM+® brain monitoring software by clinical research centres worldwide has been continuously growing over the past 20 years. This has necessitated ongoing updates to accommodate evolving neuromonitoring research needs, including recent explosion of artificial intelligence (AI). Research questionWe sought to provide an update on the current features of the software. In particular, we aimed to highlight the new options of integrating AI models. Material and methodsWe reviewed all currently available ICM+ analytical areas and discussed potential AI based extensions in each. We tested a proof-of-concept integration of an AI model and evaluated its performance for real-time data processing. ResultsICM+ current analytical tools serve both real-time (bed-side) and offline (file based) analysis, including the calculation engine, Signal Calculator, Custom Statistics, Batch tools, ScriptLab and charting. The ICM+ Python plugin engine allows to execute custom Python scripts and take advantage of complex AI frameworks. For the proof-of-concept, we used a neural network convolutional model with 207,000 trainable parameters that classifies morphology of intracranial pressure (ICP) pulse waveform into 5 pulse categories (normal to pathological plus artefactual). When evaluated within ICM+ plugin script on a Windows 10 laptop the classification of a 5 min ICP waveform segment took only 0.19s with a 2.3s of initial, one-off, model loading time required. ConclusionsModernised ICM+ analytical tools, reviewed in this manuscript, include integration of custom AI models allowing them to be shared and run in real-time, facilitating rapid prototyping and validating of new AI ideas at the bed-side.

Behind OpenAI CEO Dismissal: An Ethical Dilemma And ANew AI Revolution

The world of Artificial Intelligence and Silicon Valley have been rocked in Nov. 2023 by the sudden ouster of OpenAI CEO, Sam Altman, by the company's board. OpenAI is the 2015 start-up behind ChatGPT and GPT-4, which enabled generating content and media-altered by AI. While nothing much was revealed by the board, the official statement mentioned that he wasn't transparent about his communication to the board about the developments of the company, which led the board to lose trust in him and deciding to fire him. Backed up by 700 OpenAI staffers who threatened to resign in solidarity with their fired leader and a supportive offer from Microsoft CEO Satya hiring Altman to lead significant AI Research Lab in Microsoft, Altman was back again as CEO in 5 days along with a revamped new board. While this dramatic story that entertained the software industry for a week could be seen as mere news, it is indeed more than that; and the significance of this story is not Sam Altman himself as an AI business figure. The back story of this fiasco and what happened behind the scene is what interest us as a Software professionals. The purpose of this article is bring some pointers for our learning.

Artificial Intelligence: From Buzzword to Useful Tool in Clinical Pharmacology.

The advent of artificial intelligence (AI) in clinical pharmacology and drug development is akin to the dawning of a new era. Previously dismissed as merely technological hype, these approaches have emerged as promising tools in different domains, including health care, demonstrating their potential to empower clinical pharmacology decision making, revolutionize the drug development landscape, and advance patient care. Although challenges remain, the remarkable progress already made signals that the leap from hype to reality is well underway, and AI promises to offer clinical pharmacology new tools and possibilities for optimizing patient care is gradually coming to fruition. This review dives into the burgeoning world of AI and machine learning (ML), showcasing different applications of AI in clinical pharmacology and the impact of successful AI/ML implementation on drug development and/or regulatory decisions. This review also highlights recommendations for areas of opportunity in clinical pharmacology, including data analysis (e.g., handling large data sets, screening to identify important covariates, and optimizing patient population) and efficiencies (e.g., automation, translation, literature curation, and training). Realizing the benefits of AI in drug development and understanding its value will lead to the successful integration of AI tools in our clinical pharmacology and pharmacometrics armamentarium.

The AI Galaxy: A Comparative Study of Cutting-Edge AI Technology

Abstract: The world of artificial intelligence (AI) has evolved into a vast array of technologies. The purpose of this paper is to explore a range of AI models and products, including GPT-4, GPT4-0613, GPT-3.5-Turbo, GPT-3.5-Turbo-0613, Claude-1, Claude-2, Claude-Instant-1, GPT-4-32K, GPT-4-32K-0613, GPT-3.5-Turbo-16K, GPT-3.5-Turbo-16K-0613, Claude-1-100K, Claude-1-100K, Claude-1-Instant-1-100K, Google BardAI, Microsoft Bing, and Perplexity. It will cover their capabilities, use cases, and what makes them unique in today's ever-expanding world of artificial intelligence. A comparison of these models and products will also be presented, highlighting the strengths and weaknesses of each.

Ian Mcewan’ın Benim Gibi Makineler Romanında Simülasyon Yoluyla Anlamı Şekillendirme ve Alternatif Gerçeklik Oluşturma

Ian McEwan uses elements of science-fiction and puts forwards some vague issues about artificial intelligence in Machines Like Me, thus leaving the reader in a technologically advanced, sci-fi utopia dominated by hyperrealism, subjectivity, and consumerism, which later turns into a moral dystopia with discrepancies of humankind’s interaction with AI humanoid robots. He offers a retro-futuristic universe where notions such as morality, human nature, and free will are challenged in an environment generated by postmodern tactics of historiographic metafiction and intertextuality as well as simulation. McEwan also provides us with a postmodern picture of contemporary individuals and conditions in which thin lines between the intrusion of artificial intelligence into our lives and the representation of truth and reality are blurred.
 Making use of theoretical concepts such as postmodern simulation, historicity, and production of knowledge under how McEwan presents the major subject matters in the novel with the reflection and depiction of a futuristic world of artificial intelligence, this article tries to answer the questions about the condition of the postmodern individual who struggles with the issues of discerning reality and truth haunted by the existence and intrusion of AI Adams and Eves.

Machine learning based tensile strength prediction and analysis on friction stir welded dissimilar joints (AA6082-AA5083) using conventional and hybrid tool pin profiles

Friction stir welding technique is considered to produce weldments with promising strengths. Owing to the minimum set of parameters only to be controlled during welding, this green welding technology possesses noticeable advantages over other welding techniques. As the world of Artificial Intelligence is taking great leaps, the application of machine learning is serving as a great advantage in several research domains. This paper focuses on comparing different ensemble learning-based boosting approaches and implementing an optimum regression model for predicting tensile strength. This was trained upon the experimented data along with the analysis comprehending the influence of parameters involved during the process of welding with the concept of Explainable AI. The results obtained were competent with a 0.985 R2 error and 5.292 RMSE.

The effectiveness of artificial intelligence in contemporary digital graphic design

In our world, technological development has become inherent in all walks of life and is characterized by its speed in performance and uses. This development required the emergence of new technologies that represent a future revolution for a fourth industrial revolution in various fields, which contributed to finding many alternatives and innovative technical solutions that shortened time and space in terms of making Machines are smarter, more accurate, and faster in accomplishing the tasks intended for them, and we find the emergence of what is called artificial intelligence (artificial intelligence), which is the technology of the future, which is one of the most important outputs of the fourth industrial revolution, and artificial intelligence has become a comprehensive term for applications that perform complex tasks that required in the past human inputs such as Communicating with customers via the Internet and various digital applications, as it saved a lot of time, effort, and money thanks to its various capabilities, specifically in the field of graphic design. in graphic design The study aimed to identify the effectiveness of artificial intelligence in contemporary digital graphic design and to benefit from its applications through its employment in the field of graphic design. And the techniques used to design and develop artificial intelligence applications 4- The importance of artificial intelligence and its effectiveness in developing graphic design skills. Its effective capabilities enable and facilitate contemporary digital graphic design processes. The research also came out with conclusions, recommendations and proposals that came from it. Results: 1- Artificial intelligence for the graphic designer shortens the implementation of various designs and analyzes problems with accuracy and high speed, which allows achieving creativity and developing his skills. 2- Artificial intelligence can process a huge amount of data and information in a short period of time compared to time spent on traditional digital design. 3- Artificial intelligence enables the graphic designer to find solutions to unfamiliar problems that he faces when executing the design work. The researcher came out with conclusions, including: 1 - The revolution in the world of artificial intelligence in the future will make applications capable of carrying out various tasks of graphic design and most areas of our lives. 2- Artificial intelligence helps users create new patterns and different designs with less experience and knowledge in the field of design. The researcher also recommended directing graphic designers and students to work and make use of artificial intelligence techniques in the various stages of design to save time and effort and avoid making mistakes. The researcher also suggested studying the applications of artificial intelligence and their uses in the digital graphic achievement. The search was also included in the list of Arab and foreign sources

Role of Emotional Intelligence in the World of Artificial Intelligence

Role of Emotional Intelligence in the World of Artificial Intelligence

CNN and Keras based Road Safety Traffic Signs Recognition System

Accident rates increased due to non-compliance with traffic signs and non-compliance with traffic rules. By using synthetic training data from images of train signs, we can overcome the problem of analysis of traffic data, which varies by country and region. This method is used to create files containing synthetic images to detect traffic signs from different perspectives. With this knowledge and a well-designed Convolutional Neural Network (CNN), we can create a data-driven train recognition and detection system that has accurate detection accuracy and still has action. This article presents the process of recognizing and classifying road signs and traffic signs to create their inventory to help great engineers replace and maintain them. It uses images captured by a camera from a moving car. The system is based on three main stages: color segmentation, recognition and classification. Many researchers in the world of artificial intelligence and technology and Tesla, Uber, Google, Mercedes-Benz, Toyota, Ford, Audi etc. big companies like self-driving cars and self-driving cars. Therefore, in order for this technology to be used correctly, vehicles must be able to interpret traffic signs and make decisions accordingly. This reduces accidents and also helps drivers concentrate on driving rather than looking at every traffic card. The purpose of this document is to provide an effective way of discovering and recognizing traffic signs in India.

Joint Latent Space and Label Inference Estimation with Adaptive Fused Data and Label Graphs

Recently, structured computing has become an interesting topic in the world of artificial intelligence, especially in the field of machine learning, as most researchers focus on the development of graph-based semi-supervised learning models. In this article, we present a new framework for graph-based semi-supervised learning. We present a powerful method for simultaneous label inference and linear transform estimation. The targeted linear transformation is used to obtain a discriminant subspace. To improve semi-supervised learning, our framework focuses on exploiting the data structure and soft labels of the available unlabeled samples. In the iterative optimization scheme used, the prior estimation of the label increases the supervision information indirectly through an introduced informative matrix called the label graph, thus avoiding the use of hard confidence-based decisions as used in self-supervised methods. In addition, the estimation of labels and projected data is made more robust by using smoothing concepts based on hybrid graphs. For each type of smoothing, the hybrid graph is an adaptive fusion of the two graphs encoding the similarity of the data and the similarity of the labels. The proposed method leads to an improved discriminative linear transformation. Several experimental results on real image datasets confirm the effectiveness of the proposed method. They also show superior performance compared to semi-supervised methods that use integration and label inference simultaneously.