Science topics: Computer Science and EngineeringArtificial Intelligence
Science topic
Artificial Intelligence - Science topic
Artificial Intelligence
Questions related to Artificial Intelligence
Will the rise of artificial intelligence (AI) revolutionize research development, or will it have a negative impact on the research process? On one hand, AI could streamline research, accelerate discovery, and enhance the quality of research outputs. On the other hand, widespread reliance on AI could lead to a decrease in critical thinking skills, originality, and the value of hard work. What are the potential benefits and drawbacks of integrating AI in research, and how can we ensure that AI is used in a way that complements human creativity and innovation?
Hey everyone,
I'm writing my master thesis on the impact of artificial intelligence on business productivity.
This study is mainly aimed at those of you who develop AI or use these technologies in your professional environment.
This questionnaire will take no more than 5 minutes to complete, and your participation is confidential!
Thank you in advance for your time and contribution!
To take part, please click on the link below: https://forms.gle/fzzHq4iNqGUiidTWA
Assuming an AI system is provided with the required data and computing resources to achieve a complex task. This task would not be achieved unless the machine is powered with a well written algorithm. Since an algorithm is a program or set of instructions that a machine executes, therefore, applying it defies the concept of machine intelligence. Do you agree?
In the Netherlands, there is much concern about the distance between citizens and government and the lack of mutual trust in each other. Some say this is a result of technology - algorithms and automation of many activities are making the relationship between government and citizen (national but also local) increasingly businesslike and formal. AI could further increase this distance. There are also those who believe that AI can actually help make government more human and improve government-citizen contact. What do you guys think about this and are there people here who know of concrete examples or studies where AI is helping to make government more trusting and human?
What is the role of artificial intelligence in business management?
How should the development of AI technology be regulated so that this development and its applications are realized in accordance with ethics?
How should the development of AI technology be regulated so that this development and its applications are realized in accordance with ethics, so that AI technology serves humanity, so that it does not harm people and does not generate new categories of risks?
Conducting a SWOT analysis of the applications of artificial intelligence technology in business, in the business activities of companies and enterprises, shows that there are both many already and developing many more business applications of the said technology, i.e., many potential development opportunities are recognized in this field of using the achievements of the current fourth and/or fifth technological revolution in various spheres of business activity, as well as there are many risks arising from inappropriate, incompatible with the prevailing social norms, standards of reliable business activity, incompatible with business ethics use of new technologies. Among some of the most recognized negative aspects of improper use of generative artificial intelligence technology is the use of AI-equipped graphic applications available on the Internet that allow for the simple and easy generation of photos, graphics, images, videos and animations that, in the form of very realistically presented images, photos, videos, etc., depict something that never happened in reality, i.e., they graphically present images or videos presenting what could be described as “fictitious facts” in a very professional manner. In this way, Internet users can become disinformation generators in online social media, where they can post the said generated images, photos, videos, etc. with added descriptions, posts, comments, in which the said “fictitious facts” presented in the photos or videos will also be described in an editorially correct manner. Besides, the mentioned descriptions, posts, entries, comments, etc. can also be edited with the help of intelligent chatbots available on the Internet like Chat GPT, Copilot, Gemini, etc. However, misinformation is not the only serious problem as it has significantly intensified after OpenAI released the first versions of ChatGPT chatbot online in November 2021. A new category of technical operational risk associated with the new AI technology applied has emerged in companies and enterprises that implement generative artificial intelligence technology into various spheres of business. In addition, there is a growing scale of risks arising from conflicts of interest between business entities related to not fully regulated copyright issues of works created using applications and information systems equipped with generative artificial intelligence technology. Accordingly, there is a demand for the development of a standard of a kind of digital signature with the help of which works created with the help of AI technology will be electronically signed, so that each such work will be unique, unrepeatable and whose counterfeiting will thus be seriously hampered. However, these are only some of the negative aspects of the developing applications of AI technologies, for which there are no functioning legal norms. In the middle of 2023 and then in the spring of 2024, European Union bodies made public the preliminary versions of the developed legal norms on the proper, business-ethical use of technology in business, which were given the name AI Act. The legal normatives, referred to as the AIAct, contain a number of specific, defined types of AI technology applications deemed inappropriate, unethical, i.e. those that should not be used. The AIAct contains classified according to different levels of negative impact on society various types and specific examples of inappropriate and unethical use of AI technologies in the context of various aspects of business as well as non-business activities. An important issue to consider is the scale of the commitment of technology companies developing AI technologies to respect such regulations so that issues of ethical use of this technology are also defined as much as possible in technological aspects in companies that create, develop and implement these technologies. Besides, in order for AIACT's legal norms, when they come into force, not to be dead, it is necessary to introduce both sanction instruments in the form of specific penalties for business entities that use artificial intelligence technologies unethically, antisocially, contrary to AIAct. On the other hand, it would also be a good solution to introduce a system of rewarding those companies and businesses that make the most proper, pro-social, in accordance with the provisions of the AIAct, fully ethical use of AI technologies. In view of the fact that AIACT is to come into force only in more than 2 years so it is necessary to constantly monitor the development of AI technology, verify the validity of the provisions of AIAct in the face of dynamically developing AI technology, successively amend the provisions of the said legal norms, so that when they come into force they do not turn out to be outdated. In view of the above, it is to be hoped that, despite the rapid technological progress, the provisions on the ethical applications of artificial intelligence technology will be constantly updated and the legal normatives shaping the development of AI technology will be amended accordingly. If AIAct achieves the above-mentioned goals to a significant extent, ethical applications of AI technology should be implemented in the future, and the technology can be referred to as ethical generative artificial intelligence, which is finding new applications.
The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How should the development of AI technology be regulated so that this development and its applications are carried out in accordance with the principles of ethics?
How should the development of AI technology be regulated so that this development and its applications are realized in accordance with ethics?
How should the development of AI technology applications be regulated so that it is carried out in accordance with ethics?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
We submitted a paper Large Language Models: Assessment for Singularity.
We investigated whether modern LLM technology can create the conditions for the singularity of AI, which has been discussed mainly in the field of philosophy, and modeled and discussed what kind of design is possible at the implementation level, as well as the conditions for an intelligence explosion and accelerated AI population growth.
If an autonomous AI can be created in a safe manner, the benefits to mankind are likely to be enormous, so we have begun research on prototypes of the RSI_RPF and other products proposed in this study with great care.
We are open to a wide range of opinions, including interest and discussion, and hope you will feel free to contact us to discuss about this theme.
Hey everyone,
I'm currently writing my thesis on The Role of AI in Recruitment and I'm looking for professional participants for my survey. Would you mind taking a few minutes to fill it out? Your insights would be incredibly valuable to my research.
Here's the link to the survey: https://forms.gle/85wjLYqaCMnCUHwd7
As a token of appreciation, there's also a chance to win an Amazon Voucher!
Thank you so much for your time and support! 💙
2024 4th International Conference on Computer, Remote Sensing and Aerospace (CRSA 2024) will be held at Osaka, Japan on July 5-7, 2024.
Conference Webiste: https://ais.cn/u/MJVjiu
---Call For Papers---
The topics of interest for submission include, but are not limited to:
1. Algorithms
Image Processing
Data processing
Data Mining
Computer Vision
Computer Aided Design
......
2. Remote Sensing
Optical Remote Sensing
Microwave Remote Sensing
Remote Sensing Information Engineering
Geographic Information System
Global Navigation Satellite System
......
3. Aeroacoustics
Aeroelasticity and structural dynamics
Aerothermodynamics
Airworthiness
Autonomy
Mechanisms
......
All accepted papers will be published in the Conference Proceedings, and submitted to EI Compendex, Scopus for indexing.
Important Dates:
Full Paper Submission Date: May 31, 2024
Registration Deadline: May 31, 2024
Conference Date: July 5-7, 2024
For More Details please visit:
Invitation code: AISCONF
*Using the invitation code on submission system/registration can get priority review and feedback
Guest Editors:
Abdulqadir Nashwan, MSc, RN, Hamad Medical Corporation, Qatar
Kathrin Seibert, DPH, MSc, RN, University of Bremen, Germany
Submission Status: Open | Submission Deadline: 27 January 2025
BMC Nursing is calling for submissions to our Collection, Artificial intelligence and nursing practice. This collection explores the diverse applications of AI in nursing; ranging from innovative clinical interventions to ethical considerations and implications for healthcare delivery.
for more details ⬇
Dear Colleagues,
Ready to showcase your research on cutting-edge crop yield predictions?
We are thrilled to announce a special issue dedicated to the intersection of artificial intelligence and remote sensing in predicting crop yields.
This special issue focuses on AI and remote sensing technologies to provide early and precise yield estimations, thereby revolutionizing farming practices.
Researchers are invited to submit their innovative solutions and research findings on a wide array of topics, including:
🚜 IAI and LiDAR precision agriculture.
📡 satellite imagery for crop monitoring and yield estimation.
🌿 multispectral and hyperspectral imaging in horticulture.
🌦️ Machine learning models for weather impact on crop yields.
🦠 AI-driven pest and disease detection .
💧 Optimization of irrigation systems using remote sensing.
🤖 Deep learning for crop classification.
🌱 Predictive analytics for soil health impact on crop yields.
🔢 Automated crop counting and size estimation.
🌍 Impact of climate change on crop yields.
Don't miss the chance to contribute to this exciting field! Submit your research now: mdpi.com/si/199287
Hey everyone,
I'm currently writing my thesis on The Role of AI in Recruitment and I'm looking for professional participants for my survey. Would you mind taking a few minutes to fill it out? Your insights would be incredibly valuable to my research.
Here's the link to the survey: https://forms.gle/85wjLYqaCMnCUHwd7
As a token of appreciation, there's also a chance to win an Amazon Voucher!
Thank you so much for your time and support! 💙
Call for Papers
CMC-Computers, Materials & Continua new special issue“Emerging Trends and Applications of Deep Learning for Biomedical Signal and Image Processing”is open for submission now.
Submission Deadline: 31 March 2025
Guest Editors
- Prof. Batyrkhan Omarov, Al-Farabi Kazakh National University, Kazakhstan
- Prof. Aigerim Altayeva, International Information Technology University,Kazakhstan
- Prof. Bakhytzhan Omarov, International University of Tourism and Hospitality, Kazakhstan
Summary
In this special issue, we delve into the cutting-edge advancements and transformative applications of deep learning techniques within the realms of biomedical engineering and healthcare. Deep learning, a subset of artificial intelligence, has emerged as a groundbreaking tool, offering unparalleled capabilities in interpreting complex biomedical signals and images. This issue brings together a collection of research articles, reviews, and case studies that highlight the innovative integration of deep learning methodologies for analyzing physiological signals (such as EEG, ECG, and EMG) and medical images (including MRI, CT scans, X-rays, and etc.).
The content spans a broad spectrum, from theoretical frameworks and algorithm development to practical applications and case studies, providing insights into the current state-of-the-art and future directions in this rapidly evolving field. Key themes include, but are not limited to, the development of novel deep learning models for disease diagnosis and prognosis, enhancement of image quality and interpretation, real-time monitoring and analysis of biomedical signals, and personalized healthcare solutions.
Contributors to this issue showcase the significant impact of deep learning on improving diagnostic accuracy, enabling early detection of abnormalities, and facilitating personalized treatment plans. Furthermore, discussions extend to ethical considerations, data privacy, and the challenges of implementing AI technologies in clinical settings, offering a comprehensive overview of the landscape of deep learning applications in biomedical signal and image processing.
Through a blend of technical depth and accessibility, this special issue aims to inform and inspire researchers, clinicians, and industry professionals about the potential of deep learning to revolutionize healthcare, paving the way for more innovative, efficient, and personalized medical care.
For submission guidelines and details, visit: https://www.techscience.com/.../special.../biomedical-signal
How to build a sustainable data center based on Big Data Analytics, AI, BI and other Industry 4.0/5.0 technologies and powered by renewable and carbon-free energy sources?
If a Big Data Analytics data center is equipped with advanced generative artificial intelligence technology and is powered by renewable and carbon-free energy sources, can it be referred to as sustainable, pro-climate, pro-environment, green, etc.?
Advanced analytical systems, including complex forecasting models that enable multi-criteria, highly sophisticated, big data and information processing-based forecasts of the development of multi-faceted climatic, natural, social, economic and other processes are increasingly based on new Industry 4.0/5.0 technologies, including Big Data Analytics and machine learning, deep learning and generative artificial intelligence. The use of generative artificial intelligence technologies enables the application of complex data processing algorithms according to precisely defined assumptions and human-defined factors. The use of computerized, integrated business intelligence information systems allows real-time analysis on the basis of continuously updated data provided and the generation of reports, reports, expert opinions in accordance with the defined formulas for such studies. The use of digital twin technology allows computers to build simulations of complex, multi-faceted, prognosticated processes in accordance with defined scenarios of the potential possibility of these processes occurring in the future. In this regard, it is also important to determine the probability of occurrence in the future of several different defined and characterized scenarios of developments, specific processes, phenomena, etc. In this regard, Business Intelligence analytics should also make it possible to precisely determine the level of probability of the occurrence of a certain phenomenon, the operation of a process, the appearance of described effects, including those classified as opportunities and threats to the future development of the situation. Besides, Business Intelligence analytics should enable precise quantitative estimation of the scale of influence of positive and negative effects of the operation of certain processes, as well as factors acting on these processes and determinants conditioning the realization of certain scenarios of situation development. Cloud computing makes it possible, on the one hand, to update the database with new data and information from various institutions, think tanks, research institutes, companies and enterprises operating within a selected sector or industry of the economy, and, on the other hand, to enable simultaneous use of a database updated in this way by many beneficiaries, many business entities and/or, for example, also by many Internet users in a situation where the said database would be made available on the Internet. In a situation where Internet of Things technology is applied, it would be possible to access the said database from the level of various types of devices equipped with Internet access. The application of Blockchain technology makes it possible to increase the scale of cybersecurity of the transfer of data sent to the database and Big Data information as part of the updating of the collected data and as part of the use of the analytical system thus built by external entities. The use of machine learning and/or deep learning technologies in conjunction with artificial neural networks makes it possible to train an AI-based system to perform multi-criteria analysis, build multi-criteria simulation models, etc. in the way a human would. In order for such complex analytical systems that process large amounts of data and information to work efficiently it is a good solution to use state-of-the-art super quantum computers characterized by high computing power to process huge amounts of data in a short time. A center for multi-criteria analysis of large data sets built in this way can occupy quite a large floor space equipped with many servers. Due to the necessary cooling and ventilation system and security considerations, this kind of server room can be built underground. while due to the large amounts of electricity absorbed by this kind of big data analytics center, it is a good solution to build a power plant nearby to supply power to the said data center. If this kind of data analytics center is to be described as sustainable, in line with the trends of sustainable development and green transformation of the economy, so the power plant powering the data analytics center should generate electricity from renewable energy sources, e.g. from photovoltaic panels, windmills and/or other renewable and emission-free energy sources of such a situation, i.e., when a data analytics center that processes multi-criteria Big Data and Big Data Analytics information is powered by renewable and emission-free energy sources then it can be described as sustainable, pro-climate, pro-environment, green, etc. Besides, when the Big Data Analytics analytics center is equipped with advanced generative artificial intelligence technology and is powered by renewable and emission-free energy sources then the AI technology used can also be described as sustainable, pro-climate, pro-environment, green, etc. On the other hand, the Big Data Analytics center can be used to conduct multi-criteria analysis and build multi-faceted simulations of complex climatic, natural, economic, social processes, etc. with the aim of, for example. to develop scenarios of future development of processes observed up to now, to create simulations of continuation in the future of diagnosed historical trends, to develop different variants of scenarios of situation development according to the occurrence of certain determinants, to determine the probability of occurrence of said determinants, to estimate the scale of influence of external factors, the scale of potential materialization of certain categories of risk, the possibility of the occurrence of certain opportunities and threats, estimation of the level of probability of materialization of the various variants of scenarios, in which the potential continuation of the diagnosed trends was characterized for the processes under study, including the processes of sustainable development, green transformation of the economy, implementation of sustainable development goals, etc. Accordingly, the data analytical center built in this way can, on the one hand, be described as sustainable, since it is powered by renewable and emission-free energy sources. In addition to this, the data analytical center can also be helpful in building simulations of complex multi-criteria processes, including the continuation of certain trends of determinants influencing the said processes and the factors co-creating them, which concern the potential development of sustainable processes, e.g. economic, i.e. concerning sustainable economic development. Therefore, the data analytical center built in this way can be helpful, for example, in developing a complex, multifactor simulation of the progressive global warming process in subsequent years, the occurrence in the future of the negative effects of the deepening scale of climate change, the negative impact of these processes on the economy, but also to forecast and develop simulations of the future process of carrying out a pro-environmental and pro-climate transformation of the classic growth, brown, linear economy of excess to a sustainable, green, zero-carbon zero-growth and closed-loop economy. So, the sustainable data analytical center built in this way will be able to be defined as sustainable due to the supply of renewable and zero-carbon energy sources, but will also be helpful in developing simulations of future processes of green transformation of the economy carried out according to certain assumptions, defined determinants, estimated probability of occurrence of certain impact factors and conditions, etc. orz estimating costs, gains and losses, opportunities and threats, identifying risk factors, particular categories of risks and estimating the feasibility of the defined scenarios of the green transformation of the economy planned to be implemented. In this way, a sustainable data analytical center can also be of great help in the smooth and rapid implementation of the green transformation of the economy.
Kluczowe kwestie dotyczące problematyki zielonej transformacji gospodarki opisałem w poniższym artykule:
IMPLEMENTATION OF THE PRINCIPLES OF SUSTAINABLE ECONOMY DEVELOPMENT AS A KEY ELEMENT OF THE PRO-ECOLOGICAL TRANSFORMATION OF THE ECONOMY TOWARDS GREEN ECONOMY AND CIRCULAR ECONOMY
Zastosowania technologii Big Data w analizie sentymentu, analityce biznesowej i zarządzaniu ryzykiem opisałem w artykule mego współautorstwa:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
If a Big Data Analytics data center is equipped with advanced generative artificial intelligence technology and is powered by renewable and carbon-free energy sources, can it be described as sustainable, pro-climate, pro-environment, green, etc.?
How to build a sustainable data center based on Big Data Analytics, AI, BI and other Industry 4.0/5.0 technologies and powered by renewable and carbon-free energy sources?
How to build a sustainable data center based on Big Data Analytics, AI, BI and other Industry 4.0/5.0 and RES technologies?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
Topic is ''The most effective AI tool for university students among Chatgpt VS Gemini ai'' and our aim is to find out what is the most effective AI tool for university students.
Is the design of new pharmaceutical formulations through the involvement of AI technology, including the creation of new drugs to treat various diseases by artificial intelligence, safe for humans?
There are many indications that artificial intelligence technology can be of great help in terms of discovering and creating new drugs. Artificial intelligence can help reduce the cost of developing new drugs, can significantly reduce the time it takes to design and create new drug formulations, the time it takes to conduct research and testing, and can thus provide patients with new therapies for treating various diseases and saving lives faster. Thanks to the use of new technologies and analytical methods, the way healthcare professionals treat patients has been changing rapidly in recent times. As scientists manage to overcome the complex problems associated with lengthy research processes, and the pharmaceutical industry seeks to reduce the time it takes to develop life-saving drugs, so-called precision medicine is coming to the rescue. It takes a lot of time to develop, analyze, test and bring a new drug to market. Artificial intelligence technology is particularly helpful in this regard, including reducing the aforementioned time to create a new drug. When creating most drugs, the first step is to synthesize a compound that can bind to a target molecule associated with the disease. The molecule in question is usually a protein, which is then tested for various influencing factors. In order to find the right compound, researchers analyze thousands of potential candidates of different molecules. When a compound that meets certain characteristics is successfully identified, then researchers search through huge libraries of similar compounds to find the optimal interaction with the protein responsible for the specific disease. In contrast, many years of time and many millions of dollars of funding are required to complete this labor-intensive process today. In a situation where artificial intelligence, machine learning and deep learning are involved in this process, then the entire process can be significantly reduced in time, costs can be significantly reduced and the new drug can be brought to the pharmaceutical market faster by pharmaceutical companies. However, can an artificial intelligence equipped with artificial neural networks that has been taught through deep learning to carry out the above-mentioned processes get it wrong when creating a new drug? What if the drug that was supposed to cure a person of a particular disease produces a number of new side effects that prove even more problematic for the patient than the original disease from which it was supposed to be cured? What if the patient dies due to previously unforeseen side effects? Will insurance companies recognize the artificial intelligence's mistake and compensate the family of the deceased patient? Who will bear the legal, financial, ethical, etc. responsibility for such a situation?
I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Is the design of new pharmaceutical formulations through the involvement of AI technologies, including the creation of new drugs to treat various diseases by artificial intelligence, safe for humans?
Is the creation of new drugs by artificial intelligence safe for humans?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
What is the impact of the development of applications and information systems based on artificial intelligence technology on labor markets in specific industries and sectors of the economy?
Since the release of an intelligent chatbot built on the ChatGPT language model on the Internet in November 2021, the scale of ongoing discussions on the topic of the impact of the development of artificial intelligence technology on labor markets has increased again. Each successive technological revolution has largely generated changes in labor markets. The increase in the scale of automation of manufacturing processes carried out as part of business operations was motivated by the reduction of operational personnel costs resulting from hired personnel. Automation of manufacturing processes, including processes of production and offering services, may also have reduced the level of personnel operational risk. As a result, companies, firms and, in recent years, financial institutions and public entities, through the implementation of ICT, Internet and Industry 4.0/5.0 technologies in various business processes, are improving the efficiency of business processes and increasing the economic profitability of these processes. In each of the previous four technological revolutions, in spite of changing technical solutions and emerging new technologies, analogous processes of using these new technological advances to increase the scale of automation of economic processes worked. In the era of the current fourth or fifth technological revolution, in which a special role is played by the development of generative artificial intelligence technology, applications of this technology in the development of robotics, building autonomous robots, increasing the scale of cooperation between humans and highly intelligent androids is also making a new appearance and another stage of increasing the scale of automation of manufacturing processes. However, what from the point of view of entrepreneurs thanks to the applied new technologies, the achieved automation of production processes is an increase in the efficiency of manufacturing processes, increasing the scale of economic profitability, etc., is, on the other hand, generating serious effects on labor markets, including, among other things, a reduction in employment in certain jobs. The largest scale of applied automation of economic processes and, at the same time, the largest scale of employment reduction was and is generated for those jobs that are characterized by a high level of repetition of certain activities. The activities carried out by employees that are characterized by a high level of repetitiveness were usually the first ones that could be and have been replaced by technology in a relatively simple way. this is also the case today in the era of the fifth technological revolution, in which highly advanced intelligent information systems and autonomous androids equipped with generative artificial intelligence technologies contribute to the reduction of employment in companies and enterprises where humans are replaced by such technology. A particular manifestation of these trends are the group layoffs announced starting in 2022 of employees, including IT specialists in technology companies that the aforementioned advanced technologies of Industry 4.0/5.0 are also creating, developing and implementing into their economic processes carried out in the aforementioned technology companies. Recently, there have been a lot of different kinds of predictive analysis results in the media suggesting which occupations and professions previously performed by people are most at risk of increasing unemployment in the future due to the development of business applications of generative artificial intelligence technologies. In the first months of ChatGPT's release, the Internet was dominated by a number of publications suggesting that a significant portion of jobs in many industries will be replaced by AI technology over the next few decades. Then, after another few months of the development of applications of intelligent chatbots, but also the revelation of many controversies and risks associated with it such as the development of cybercrime and disinformation on the Internet, this dominant opinion began to change in the direction of slightly less pessimistic. these less pessimistic opinions suggest that the technology of generative artificial intelligence does not necessarily deprive the majority of employees in companies and enterprises of their jobs only the majority of employees will be forced to use these new tools, applications, information systems equipped with AI technology as part of their work. Besides, the scale of the impact of new technologies on labor markets will probably not be the same across industries and sectors of the economy.
I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
What is the impact of the development of applications and information systems based on artificial intelligence technology on labor markets in specific industries and sectors of the economy?
What is the impact of the development of applications of artificial intelligence technology on labor markets in specific industries and sectors of the economy?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
I ask this question from the perspective that AI algorithms can automate tasks, analyze vast amounts of data, and suggest new research avenues. It can also improve research efficiency and speed up scientific progress, in addition to analysing massive datasets, it could identify patterns, and accelerate scientific discovery. These no doubt are advantageous benefits, but AI algorithms can also inherit biases from the data they're trained on, leading to discriminatory or misleading results, which directly affect research in terms of the quality of output. Additionally, the "black box" nature of some AI systems makes it difficult to understand how they reach conclusions, raising concerns about transparency and accountability.
Do artificial intelligence applications have a role in developing all types of sports media, audio-visual media, journalism, and digital multimedia?
I am writing articles on Electrical and Protection Automation, IoT and Artificial Intelligence, I am looking like minded people who can be a co-author with me.
Thanks and Regards,
Madhu
What does LLM and generative AI tell us about language acquisition and language use?
What does LLM and generative AI mean for linguistic theories? For generative grammar or for cognitive construction grammar? For diachronic linguistics and philology?
Call for Papers
CMC-Computers, Materials & Continua new special issue“Practical Application and Services in Fog/Edge Computing System”is open for submission now.
📆 Submission Deadline: 31 December 2024
👨🎓 Guest Editors
Prof. Hwa-Young Jeong, Kyung Hee University, South Korea
Prof. Neil Y. Yen, University of Aizu, Japan
Prof. Jason C. Hung, Taichung University of Science and Technology, Taiwan
📝 The main topics of this special issue are state-of-the-art technologies and research for practical use or application in the field of fog/edge computing with IoT. Real cases and technical studies in various fields are recruited with fog/edge computing technology, and research cases applied to fog/edge computing with artificial intelligence/deep learning are recruited.
📚 For submission guidelines and details, visit: https://www.techscience.com/cmc/special_detail/fog_edge-computing
Keywords
- Advanced Edge computing and analytics using big data
- Application and service of edge computing and security
- Practical service of Edge-as-a-Service (EaaS), Fog as a Service (FaaS)
- Distributed computation with 6G networks and edge computing
- Fog and edge computing technique and service for smart city
- High performance Storage as a service in Fog computing
- Practical Infrastructure as a Service (IaaS) in Fog/Edge computing
- Advanced Fog architecture using IoT sensing technique and service
- Practical IoT application and service with fog/edge computing
- Improved IoT-Fog-Cloud Architecture using Big-Data analytics
- Optimization of IoT-Fog Network Path
- The use of IoT based education application with fog/edge computing
- Advanced life change using IoT with fog/edge computing
- The development of deep learning models for cloud, edge, fog, and IoT computing
- The design and development of Cloud, fog and edge computing platforms
- The development and use of AI-based fog and edge computing
- The use of smart healthcare with fog/edge computing
- 6G network application and service with devices in IoT with fog/edge computing
- Processing and analysis of IoT based drone computation offloading with fog/edge computing
As AI technology, such as ChatGPT, continues to advance, I'm curious about its impact on academic research. How do researchers view the integration of AI tools in their work? Are these tools seen as beneficial for enhancing research productivity and quality, or are there concerns about their influence on the integrity and originality of research? I would appreciate any insights or experiences you could share.
Why all the buzz about AI-assisted writing? Think about it—haven’t we already embraced tools like Grammarly and Quillbot and other AI-assisted and Computer Assisted Writing to help us write better(Wang, 2022)? And remember when we switched from digging through library cards to hopping onto research databases? Evidently, each has advantages and disadvantages (Falagas, 2008). Sure, there was a time when many educators were wary about students using computers for writing, worried it might spoil their writing skills (Billings, 1986) or second language acquisition (Lai, 2006; Gündüz, 2005). But look how that turned out: we adapted and learned to see the value in the technology. So, what's the big deal now? AI writing tools are just the next step. Instead of pushing back, why not dive in, learn how it works, and show others how to use it? Let's make the most of what tech can offer and keep up with the times!
Billings, D. M. (1986). Advantages and disadvantages of computer-assisted instruction. Dimensions of Critical Care Nursing, 5(6), 356-362.
Falagas, M. E., Pitsouni, E. I., Malietzis, G. A., & Pappas, G. (2008). Comparison of PubMed, Scopus, web of science, and Google scholar: strengths and weaknesses. The FASEB journal, 22(2), 338-342.
Gündüz, N. (2005). Computer-assisted language learning. Journal of language and linguistic studies, 1(2), 193-214.
Lai, C. C., & Kritsonis, W. A. (2006). The advantages and disadvantages of computer technology in second language acquisition. Online Submission, 3(1).
Wang, Z. (2022). Computer-assisted EFL writing and evaluations based on artificial intelligence: a case from a college reading and writing course. Library Hi Tech, 40(1), 80-97.
Dear all,
I would like to publish my papers in a journal. Since it is strongly required to publish the paper in an international journal indexed by Scopus, I face some difficulties due to some fees that must be paid (which is very high) by the author.
My research areas are computer science, artificial intelligence, machine learning, Pattern recognition, natural language processing and Social Media Analytics.
Are there any Scopus-indexed journals without without any article processing charge or other hidden charges for publication and suitable for my research areas?
I would like to thanks for your kind help.
With best regards,
Amit
good greetings
I need references such as books and papers about artificial intelligence in international law.
How far back can we go in history to understanding productivity using AI? Is use of embedded MS Excel functions/formulae or even use of spelling checker in Word.doc a good example of describing the time-frame in terms of early AI? I think AI has just advanced in progression but has been in use for 50 years or more, agree?
- How many of us use THREE or more or all of the following apps in our workspaces?:
#Eximioussoftlogodesin_2023; #Xaradesignerproplus_19.5; #AutoCADPlant3D_2024; #AutoCADRasterdesign_2024; #AutoCADMap3D_2025; #AnsysSpaceClaim_2024 or #AnsysEMA3D_2024; #4CSQL or CWSQL6.97.0 with #4CMobileCMMS; #Windows.netPro_2023; #Windowsserver_2022; #OracleVirtualBox7.0; #FileZilla;
Is our productivity really simplified and made economically affordable or we tend to desire learning more and more and getting entangled in even more complications but in a simplified manner? I mean to argue that instead of reducing complications, science prompts us to simplify complications?
To what extent has the scale of disinformation generated with the use of applications available on the Internet based on generative artificial intelligence technology increased?
To what extent has the scale of disinformation generated in online social media increased using applications based on generative artificial intelligence technology available on the Internet?
Many research institutions have included among the main types of threats and risks developing globally in 2023 the question of the increase in the scale of organized disinformation operating in online social media. The diagnosed increase in the scale of disinformation generated in online social media is related to the use of applications available on the Internet based on generative artificial intelligence technology. With the help of applications available on the Internet, it is possible without being a computer graphic designer and even without artistic skills to simply and easily create graphics, drawings, photos, images, videos, animations, etc., which can represent graphically professionally created “works” that can depict fictional events. Then, with the help of other applications equipped with generative artificial intelligence technology and advanced language models, i.e. with the help of intelligent chatbots, text can be created to describe specific “fictional events” depicted in the generated images. Accordingly, since the end of 2022, i.e. since the first such intelligent chatbot, i.e. the first versions of ChatGPT, were made available on the Internet, the number of memes, photos, comments, videos, posts, banners, etc. generated with the help of applications equipped with tools based on artificial intelligence technology has been growing rapidly, including the rapid increase in the scale of disinformation generated in this way. In order to limit the scale of the aforementioned disinformation developing in online media, on the one hand, technology companies running social media portals and other online information services are perfecting tools for identifying posts, entries, comments, banners, photos, videos, animations, etc. that contain specific, usually thematic types of disinformation. However, these solutions are not perfect, and the scales of disinformation operating in internecine social media are still high. On the other hand, specific institutions for combating disinformation are being established, NGOs and schools are conducting educational campaigns to make citizens aware of the high scale of disinformation developing on the Internet. In addition, proposed regulations such as the AIAct, which as a set of regulations on the proper use of tools equipped with artificial intelligence technology is expected to come into force in the next 2 years in the European Union may play an important role in reducing the scale of disinformation developing on the Internet.
I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
To what extent has the scale of disinformation generated in online social media using applications based on generative artificial intelligence technology available on the Internet increased?
To what extent has the scale of disinformation generated using applications based on generative artificial intelligence technology available on the Internet increased?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
I was recently asked by LinkedIn to respond to and elaborate on this question, given a post of mine on this subject there. Before I provide my response here on researchgate.net, I wish to ask this question within this forum's context.
There are numerous angles one can take in approaching this critical question which is likely to affect not only Colleges and Universities' built infrastructure, but also their basic functions: teaching and research.
Obviously, there are currently expected future effects in both the short as well as the longer term of Artificial Intelligence upon Higher Education. Hence, the informed and educated views from the academic community are solicited here with this generic type of question. Thank you for your attention.
I would like to start a research from this question
As part of a capstone project, we are a group of graduate students researching innovations (technological or otherwise) that have the potential to transform the business model in American journalism. Our challenge is to propose ideas that make it more financially sustainable without sacrificing public trust. Much of our focus has been on advertising as the adjacent business and we also have been exploring different applications of AI, blockchain, etc., but are hoping to gain more insights generated by "out-of-the-box" thinking.
What innovations have you encountered that you think could help support a unique business like news? We will credit you for any new paths you might set us on!
Thank you.
To what extent do artificial intelligence technology, Big Data Analytics, Business intelligence and other ICT information technology solutions typical of the current Fourth Technological Revolution support marketing communication processes realized within the framework of Internet marketing, within the framework of social media advertising campaigns?
Among the areas in which applications based on generative artificial intelligence are now rapidly finding application are marketing communication processes realized within the framework of Internet marketing, within the framework of social media advertising campaigns. More and more advertising agencies are using generative artificial intelligence technology to create images, graphics, animations and videos that are used in advertising campaigns. Thanks to the use of generative artificial intelligence technology, the creation of such key elements of marketing communication materials has become much simpler and cheaper and their creation time has been significantly reduced. On the other hand, thanks to the applications already available on the Internet based on generative artificial intelligence technology that enable the creation of photos, graphics, animations and videos, it is no longer only advertising agencies employing professional cartoonists, graphic designers, screenwriters and filmmakers that can create professional marketing materials and advertising campaigns. Thanks to the aforementioned applications available on the Internet, graphic design platforms, including free smartphone apps offered by technology companies, advertising spots and entire advertising campaigns can be designed, created and executed by Internet users, including online social media users, who have not previously been involved in the creation of graphics, banners, posters, animations and advertising videos. Thus, opportunities are already emerging for Internet users who maintain their social media profiles to professionally create promotional materials and advertising campaigns. On the other hand, generative artificial intelligence technology can be used unethically within the framework of generating disinformation, informational factoids and deepfakes. The significance of this problem, including the growing disinformation on the Internet, has grown rapidly in recent years. The deepfake image processing technique involves combining images of human faces using artificial intelligence techniques.
In order to reduce the scale of disinformation spreading on the Internet media, it is necessary to create a universal system for labeling photos, graphics, animations and videos created using generative artificial intelligence technology. On the other hand, a key factor facilitating the development of such a problem of generating disinformation is that many legal issues related to the technology have not yet been settled. Therefore, it is also necessary to refine legal norms on copyright issues, intellectual property protection that take into account the creation of works that have been created using generative artificial intelligence technology. In addition to this, social media companies should constantly improve tools for detecting and removing graphic and/or video materials created using deepfake technology.
I have described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
To what extent does artificial intelligence technology, Big Data Analytics, Business intelligence and other ICT information technology solutions typical of the current Fourth Technological Revolution support marketing communication processes realized within the framework of Internet marketing, within the framework of social media advertising campaigns?
How do artificial intelligence technology and other Industry 4.0/5.0 technologies support Internet marketing processes?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
I have come across some ideas which I hope will be pursued by academics in the associated disciplines:
1) Topics Broadly outlined in the following articles
Fathabadi OS (2022) Voluntary Selection; Bringing Evolution at the Service of Humanity. Scientific J Genet Gene Ther 8(1): 009-015.DOI: http://dx.doi.org/10.17352/sjggt.000021
Fathabadi OS (2023) The way of future through voluntary selection. Glob J Ecol 8(1): 034-041. DOI: 10.17352/gje.000079
2) Explanation of how violence is the link between evolution and society. What is not clear in the articles above is that just as a disease shows symptoms such as fever in its early stages, violence that is caused by the lack of evolutionary order in society also shows itself in the form of problems like bullying, harassment, discrimination, passive aggression, coercive control, etc and then It may appear in the form of an increase in the rate of crimes and social riots and finally in the form of naked violence, civil wars, genocides and foreign wars. The purpose of the topics raised in both articles is to realize the evolutionary order through the methods proposed in control engineering and by achieving the desired statistical goals, not only to prevent violence, but also to spread satisfaction in the society and to provide internal and external security.
3) Interpretation of historical events including genocides and world wars through the lens of insights provided above for example how passive aggression became widespread prior to such events.
4) The articles above argue that Control Theory, in conjunction with data science, can help establish and maintain democracies with an unprecedented level of stability and provide optimal levels of living standards by regulating evolutionary health of societies and the relationships between them. This goal however, requires interpretation of the theory widely used in engineering, for application in Humanities. Control Engineering remains a rather challenging field to learn and its theoreticians and practitioners are mostly active in areas other than humanities - most critically politics - and even despite the large number of engineering graduates receiving education in Systems and Control Theory as part of their curriculum, the specific practical pathway for application of the theory for solving problems in Humanities remains rather unclear; let alone the inaccessibility of the field to the practitioners of humanities even to the extent necessary to allow them to express the problems in terms approachable by control engineering experts. Projects should therefore be defined to develop highly targeted educational materials and tools which provide a shortcut to applying the theory in solving practical problems in humanities. It is particularly important to understand that the type of Control Theory applicable to Humanities would be "Non-Linear Time-Varying Control" which is an extension of control Theory as relevant to most engineering problems and as such, the specific theory will need to be developed specifically beyond what a classically educated expert in Control Engineering would be comfortably equipped with even if educated with a PhD. For example the types of time constants and uncertainties relevant in Humanities and the types of irregularities which can be created by collective mis-intentions of social groups as well as moral aspects of implications of such techniques on human population will extend to matters associated in politics, biology, culture, education, and media. Actually it is important to understand that the knowledge and tools, will not act as a pill to fix problems but through insights, they provide directions and "Decision Support Systems" with local applicability and temporal relevance which despite their limitations, will provide unprecedented powers for providing better living standards for all populations and individuals. Such tools need to be maintained in order to remain relevant to the changes in the system under control and time. The developed materials will help students, researchers and practitioners get started and up to speed with the expertise through minimal training or self-study and the impact I believe would be revolutionary. In addition to Systems and Control Theory, the mentioned books/educational materials/tools may also cover topics such as Programming, Differential Equations, Numerical Optimisation, System Identification, Artificial Intelligence and to some extent Statistics. The set of these topic may one day help establish an independent field of study namely "Humanities Engineering".
5) Applications of the theory, educational materials, and tools mentioned above, to solve practical problems associated in sociology, psychology, politics and other fields of humanities is the ultimate goal and such projects make great topics for research in universities, Think tanks, and governments. It is important to mention that using the mean-values and standard deviations defining phenotypic profiles of populations is a way of taking into account the differences of different populations in achieving desirable results within them and in regulating the relationship between them.
6) It is also possible to characterise discourses, and broadcasted contents by defining relevant indices that quantify various aspects of them and then model and predict their relationship with the outcomes in society. These models can then act as decision support systems to identify and implement adjustments for achieving the desired social outcomes. If sufficiently predictive, they can also be used in combination with other models or in isolation as part of the control loops associated in Control Theory in order to achieve the desired outcomes in terms of sustainability, social stability, freedoms, economic welfare, health, national security, psychological security, gender equality, and optimal levels of happiness in all individuals and social groups, etc.
7) It is possible to compile a set of contents including matters mentioned in the articles above, to act as a mental anchorage for people. Something that is scientifically proven, convincing and understandable by those who put in the effort and allows them to remain motivated, morally directed, socially responsible and supported and mentally healthy. I believe adding a content starting from Genetics explaining how "Life is a complex Product of Nature" and how "Survival and Reproduction are Complex Interpretations of Laws of Nature" is necessary. Topics such as cosmology and Quantum Physics can also be included.
8) It is possible to define a project on optimal forms of democracy for different populations with emphasis on the fact that peoples' choices represent their interests as they understand them as individuals while much of what comprises our existing living standards or is necessary for achieving higher standards of living are a result of societies and mechanisms maintaining them. Societies were formed by cultures/religions as an aftermath of painful evolutionary events which occurred when people pursued their personal interests and emerged as optimal ways of achieving a better average standard of living for larger numbers of individuals over a larger proportion of their lives. In other words, many aspects of our existing living standards are by-products of societies and could not be achieved or maintained only pursuing our individual choices which is what a democracy guarantees. Democracies should be pursued for optimum living standards and preventing abuse however, it is necessary to have democracies in place to guarantee the maintenance of society itself (what you can call an evolutionary order) and realise/maintain its desired levels of standards of living and this should not be compromised by the choice of individuals.
9) Ethics of Voluntary Selection and application of methods concerned in Control Theory and AI in solving problems in Humanities specially to prevent abuse of individuals, and minorities under the flag of interests of society and to prevent creating senseless scientific approvals for imposing disadvantage on individuals and social groups. It is also necessary to minimise pain imposed on individuals and social groups in transitions as a result of adjustments.
10) While the first article introduces the concept of "Voluntary Selection" and a methodology to use it in a calculated way, it only acts as a beginning and if it is going to be implemented, a huge methodological and experimental effort is needed for identifying relevant phenotypes, developing phenotypic maps for distinct populations, identifying the results when choosing donor and receiver populations, and developing tools to predict and monitor the progress of such programs besides studying the implications for society, economy and beyond. Research can also dig deeper and take into account genotype-phenotype relationships in achieving the desired results.
One of the new technologies that has been thoroughly discussed is AI in general and ChatGPT in specific. How do you see its role in teaching and learning in terms of benefits and disadvantages? What are the models to integrate such innovations in your instruction? How do you see the future trends and beliefs of faculty members in this domain?
Regarding Turing's proposal to follow the example of the development of intelligence in humans and apply it to machines. Specifically, the example of a child who, in addition to learning discipline, needs to learn the spirit of initiative and decision-making. Could this kind of intelligence be compared to the case of a simple machine, or what Turing called the “child machine,” which is provided with basic instructions that enable it to learn and make its decisions later?
The Legal Impact of AI development on business and rural society in the Asia-Pacific and ASEAN region is at a crossroads. How will AI impact the local community (urban and rural) now?
As a student in Bachelor degree program in computer science field we have a project in course of "Language Theory", our project related with Natural Language Processing:
- First phase talks about giving a dictionary of "Physical Objects Name's" and give it a "Text" (all this in input) after that it gives us a list of "Physical Objects Name's" in our "Text" (this is the output as a file).
- Second phase is to use the last list to as input and implement a code that can classify words by topics and the result will be the general topic or idea of our text.
In this project I did the first phase but in the second one I don't understand how can I implement my code.
P.S: I try to add a python file but I can't, so for all those who wanna help me I can send them my work.
I have 293 (at the moment) videos of artificial intelligence system:
How do I make automatic annotation of videos in Russian?
Even though Saeedi, Logothetis et al. (2024) have concluded that visual illusions are a product of extrastriate rather than striate mechanisms (based on neural response latencies of illusions versus real-images as well as the optogenetic silencing of the object-encoding area of extrastriate cortex), we suspect that ultimately the creation of the mismatch is due to a discrepancy between the efference-copy representation stored in the cerebellum (perhaps going back to the time of development) and the real-world representations contained in the cortical sensory systems (Tehovnik, Hasanbegović, Chen 2024). The reason for this is that the cerebellum, with its disproportionate number of neurons (Herculano-Housel 2009), is the structure whose job it is to put all the senses in register with the motor system. For example, Hebb (1969) observed that a subject donning a prism that bent an otherwise straight line eventually adapts such that if asked to draw a straight line by hand, for example, the line to an outside observer would be deemed straight even though initially (before adaptation) this line appeared curved to the subject wearing the prism. That the cerebellum is necessary for prism adaptation as well as other types of sensory-motor realignments is well accepted (Bell, Sawtell et al. 2008; Braizer and Glickstein 1973,1999; Gallistel et al. 2022; Gilbert and Thach 1977; Giovannicci et al. 2017; Guell et al. 2018; Heun et al. 1999; Ito 2008; Kitazawa et al.1998; Miles and Lisberger 1981; Robinson 1981; Soetedjo and Fuchs 2006; Soetedjo et al. 2008; Smaers et al. 2018; Swain et al. 2011; Thach et al. 1992). It is this re-alignment that permits for highly automated acts to be executed precisely and at the shortest latencies by all vertebrates. Indeed, in the 14th Century, Pope Benedict XI set out to have the wall of St. Peter’s cathedral remodeled. To accomplish this, applicants were required to submit their art, but Giotto di Bondone (1267-1337) did not have any art to submit, so he took out a sheet of paper upon which he drew a perfect circle. Today in Tuscany this circle is known as ‘The round O of Giotto’ (Schiller and Tehovnik 2015). Without the cerebellum, Giotto’s circle would not have been precisely round, a perspective to have by anyone remodeling a building.
I heard on television a famous professor of ethics speaking about the rights of intelligent machines. There are no intelligent machines and there is no artificial intelligence. Machines function in the way people designed and programmed them to function. A discourse bout intelligent machines leads into a totalitarian society, in which people will succumb to what machines say. And machines will say what power-holders ordered to programmers to program them to say and do.
I graduated computer science; I am now retired and I regret the fact that I spent my career teaching something what now leads people into a mental and physical slavery.
How does generative artificial intelligence technology combined with Big Data Analytics and other Industry 4.0 technologies help in planning and improving production logistics management processes in business entities, companies and enterprises?
Production logistics management in a manufacturing company is currently one of the key areas of business management that significantly affects the level of technical and organizational efficiency of business operations. The change in the level of technical and organizational efficiency of business operations also usually has a significant impact and correlates with the issue of business efficiency and affects the financial results generated in the business entity. Among the key segments of logistics in the enterprise are also internal production logistics, on the way of organization of which the efficiency of the operation of production processes and the efficiency of the enterprise also largely depends. In recent years, more and more companies and enterprises have been optimizing production logistics through the implementation of information systems and automation of individual operations in the process. Production logistics is mainly concerned with ensuring the optimal flow of materials and information in the process of producing all types of goods. Production logistics does not deal with the technology of production processes, but only with the organization of the production system together with the storage and transport environment. Production logistics is mainly concerned with the optimization of all operations related to the production process, such as: supplying the plant with raw materials, semi-finished products and components necessary for production; transporting items between successive stages of production; and transferring the finished product to disposal warehouses. Precisely defining optimal production logistics is a lengthy process, requiring analysis and modification of almost every process taking place in a company. One of the key factors in the optimization of production logistics is the reduction of inventory levels and their adjustment to the ongoing production process. This translates directly into a decrease in storage costs. Effective management of production logistics should ensure timely delivery, while maintaining high product quality. Effective production logistics management can be supported by the implementation of new Industry 4.0/5.0 technologies, including Big Data and generative artificial intelligence.
The key issues of opportunities and threats to the development of artificial intelligence technology are described in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
How does the technology of generative artificial intelligence, combined with Big Data Analytics and other Industry 4.0 technologies, help to plan and improve production logistics management processes in business entities, companies and enterprises?
How does generative artificial intelligence technology help in planning and improving production logistics processes in an enterprise?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best wishes,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
I have 293 (at the moment) videos of artificial intelligence system:
How do I make automatic annotation of videos in Russian?
Is it ethical for someone on social media to offer for sale access to selected AI applications, i.e. applications based on artificial intelligence technology offered in the form of links, plug-ins on created websites, applications that can be found on the Internet for free?
I have participated in trainings whose organizers advertised on social media and during which they first presented their achievements in social media, pointed out the large income they generate within the framework of large reach in these online media, then talked about social media, marketing and online advertising used in these media, the possibility of using various applications based on artificial intelligence technology within the framework of marketing activities, creating and running advertising campaigns in social media and then presented their paid offers to gain access to these applications through created additional overlays, intermediary platforms, websites. Such training courses, webinars are usually free of charge. After the training, participants can receive free certificates confirming their participation in the training. This is a free additional form of incentive to participate in the training. On the other hand, among the forms of encouraging the purchase of access to specific AI applications is a promotional offer that lasts until the end of the training time and/or until the end of the day. however, it happens that the people conducting this type of training are not computer scientists who create AI applications, they are influencers, youtubers who have contrived to sell access to selected applications based on artificial intelligence technology, which for a certain fee will be available on created overlays, websites that act as intermediary applications to access specific source applications that are available for free on the Internet. In addition, it happens that those who conduct this kind of training do not even have a registered business and cannot even issue a VAT invoice for the services sold in this way in mediating access to selected AI applications. Surprisingly, the tax authorities in the various countries where such youtubers operate have not yet addressed this issue, given that some unethical individuals operating in this way boast about the high income they earn during such training sessions. It can be a problem of sorts for public tax authorities operating in individual countries if this kind of training and business activity is conducted via the Internet from other countries, which can be a kind of tax haven for this kind of activity. However, the problem can be serious if this kind of activity is conducted from a country referred to as a tax haven and is aimed at citizens of other countries. Apparently, there is still a lack of legal regulations that would effectively limit the use of unethical, unreliable business practices in the use of certain solutions based on artificial intelligence.
I described the key issues of opportunities and threats to the development of artificial intelligence technology in my article below:
OPPORTUNITIES AND THREATS TO THE DEVELOPMENT OF ARTIFICIAL INTELLIGENCE APPLICATIONS AND THE NEED FOR NORMATIVE REGULATION OF THIS DEVELOPMENT
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Is it ethical that in social media someone offers for sale access to selected AI applications, i.e. applications based on artificial intelligence technology offered in the form of links, plug-ins on created websites, applications that can be found on the Internet for free?
Is it ethical for someone to offer for sale on social media access to AI applications that can be found on the Internet for free?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
We see that the world is in disarray and there is no meaningful global cooperation. Nation states keep warring at an increasing rate with more intensity. None of our problems are solved and things just keep getting worse and they add new existential threats like artificial intelligence to the mix. How could anyone think that AI can be kept under control at such an environment bogs my mind. There is competition instead of collaboration, there is war, and there are no principles. UN is a total sham as can be seen once again in the example of Palestine/Israel. What good is a regulation then?
As AI detection improves, so will AI generation of text? Should we be defeatist?
AI in research offers tremendous potential, but ethical considerations are crucial. Biases in data or algorithms can lead to discriminatory or unfair results. The "black box" nature of some AI models makes it difficult to understand their reasoning, raising concerns about accountability. Ensuring data privacy, transparency in research methods, and maintaining human oversight are all essential for ethical AI-powered research.
Hi Dears,
I would like to know if it is possible to access the site's content via an API. This would make the job of implementing AI much easier. I'm new in this group, so I'm asking for your guidance and support on this matter.
Sincerely, Antonio
The aim of this study is to publish in a top-quality journal.
The frequent question that will AI excessive use reduce novelty? Is an interesting perspective.
Depending on AI too heavily can indeed lead to concerns about reduced innovation or novelty, as machines tend to optimize for efficiency and predictability rather than creativity. AI often works by analyzing existing data and patterns, which means it can sometimes perpetuate the status quo rather than generate new ideas.
Using AI as a tool to augment human creativity and decision-making, rather than replace it, could be a more balanced approach. This way, humans can leverage AI’s processing power and data analysis capabilities while still driving innovation with human creativity and intuition.
What do you think could be done to maintain a good balance between using AI and preserving human-driven innovation?
Can paintings painted or sculptures created, unique architectural designs by robots equipped with artificial intelligence be recognised as fully artistic works of art?
In recent years, more and more perfect robots equipped with artificial intelligence have been developed. New generations of artificial intelligence and/or machine learning technologies, when equipped with software that enables the creation of unique works, new creations, creative solutions, etc., can create a kind of artwork in the chosen field of creativity and artistry. If we connect a 3D printer to a robot equipped with an artificial intelligence system that is capable of designing and producing beautiful sculptures, can we thus obtain a kind of work of art?
When a robot equipped with an artificial intelligence system paints beautiful pictures, can the resulting works be considered fully artistic works of art?
If NO, why not?
And if YES, then who is the artist of the works of art created in this way, is it a robot equipped with artificial intelligence that creates them or a human being who created this artificial intelligence and programmed it accordingly?
What is your opinion on this topic?
What do you think about this topic?
Please reply,
I invite you all to discuss,
Thank you very much,
Best regards,
Dariusz Prokopowicz
Are the intelligent and learning humanoid robot "Artificial Friends" , AFs, envisaged by Kazuo Ishiguro in his recent novel "Klara and the Sun" feasible and likely to be mass produced in reality?
If so, wnat are the implications for human society?
IMPORTANT: the entife novel is the life story of KLARA, an artificial friend ie an AF, as told FROM HER INNER PERSPECTIVE, that is it tells her inner thoughts whether outwardly expressed or not.
"Klara and the Sun", Published Faber and Faber 2021
I have been through the web pages of RSC, ACS, and Elsevier, looking for information about the use of AI for translation, but I didn't find an answer. Is it allowed to use AI for translation? Once the data discussion and conclusions has been written in a mother language, how ethic (and permitted) is to use the AI to translate to English?
Dr. Cyrus F Nourani <[email protected]> wrote:
Greetings for starts to the new New Yearpersonal invitation to author a chapter based on your impressive accomplishments. Here is the track for the Innovations Management series that I have edited for the past few years. https://www.appleacademicpress.com/Innovation-Management-and-Computing The new volume you are being invited to is Innovations on Cooperative Computing and Enterprise https://www.appleacademicpress.com/innovations-on-cooperative-computing-and-enterprise-blockchains-/715 An abstract is what is required to begin. Kind regards, Cyrus https://www.appleacademicpress.com/Innovation-Management-and-Computing The new volume you are being invited to is Innovations on Cooperative Computing and Enterprise image.png Apple Academic Press https://www.appleacademicpress.com › ... Kind regards, Cyrus..
The current dynamic innovation, research, and development in the fields of Artificial Intelligence (AI), Ultra-Smart Computation, Applied Mathematics, Modeling and Simulation, and Fast Internet, promote the creation of Automated Ultra Smart Cyberspace, which opens a new horizon of opportunities for government, business, academia, and industry worldwide.
As a research area, simulation is an interdisciplinary endeavor with a vast literature. Cybersecurity research is also interdisciplinary. There is a strong connection between these areas of research.
source: JOURNAL ARTICLE - Simulation for cybersecurity: state of the art and future directions
According to artificial intelligence, 83% of Internet posts are against Israel. Why is this?
Dear/ All Egyptians
Kindly fill in the questionnaire about Artificial Intelligence (AI) through the link below.
I am asking Egyptians only because the part from Egypt need to be covered.
Thank you in advance
We are sponsoring a special issue of Research in HRM on AI and Human Resource Management. I would like to send the call for papers to researchers conducting research on the topic.
Thanks,
Dianna Stone
Bonjour,
Je réalise mon mémoire de fin d'étude qui vise à étudier l'impact de l'intelligence artificielle sur la productivité au sein des entreprises.
Cette étude s'adresse principalement à ceux parmi vous qui développent des IA ou qui utilisent ces technologies dans leur environnement professionnel.
Ce questionnaire ne vous prendra pas plus de 5 minutes et votre participation est confidentielle !
Je vous remercie par avance pour votre temps et votre contribution !
Pour participer, veuillez cliquer sur le lien ci-dessous : https://forms.gle/8tc21iJyiBP8AGYP6
What is the impact of an organization’s reliance on artificial intelligence tools in its competition for market share with other competing organizations in the same activity?
Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and accelerate progress towards SDG 4. However, rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. UNESCO is committed to supporting Member States to harness the potential of AI technologies for achieving the Education 2030 Agenda, while ensuring that its application in educational contexts is guided by the core principles of inclusion and equity.
UNESCO’s mandate calls inherently for a human-centred approach to AI. It aims to shift the conversation to include AI’s role in addressing current inequalities regarding access to knowledge, research and the diversity of cultural expressions and to ensure AI does not widen the technological divides within and between countries. The promise of “AI for all” must be that everyone can take advantage of the technological revolution under way and access its fruits, notably in terms of innovation and knowledge.
source: Artificial intelligence in education | UNESCO
"How can artificial intelligence (AI) and machine learning techniques be effectively utilized to predict, monitor, and mitigate antimony contamination in soil, optimizing remediation strategies for sustainable soil quality management?"
Is the survival instinct found in single cells as exists in humans, and can single cells communicate for the benefit of the group? The answer seems to be yes (see: Reber, Slijepcević et al. 2024 on ResearchGate). Thus (for those who want to extent volition/consciousness to machines), the ability to kill to survive will have to be programmed into machines such that the compulsion to kill (which has been perfected by humans) cannot be undone by the machine.
AI is killing the Palestinian people in the Gaza Strip in retaliation for Oct 7th. If The Hague convicts the perpetrators of the killings (on all sides), then it will not be the machines that will be imprisoned/executed—for the lust to kill is not in the genes of the AI machine, even though some have suggested that this might be commonplace in the future (e.g., Geoffrey Hinton 2023).
Introducing Artificial Intelligence in the first year of engineering studies offers students a foundational understanding of its principles and applications. This early exposure fosters relevance, interdisciplinary skills, and prepares them for future technological demands. It cultivates critical thinking and creativity, equipping them with essential tools to tackle complex problems in diverse fields. But, what about their personal skill and learning process?
1. Have you come across students using ChatGTP to submit a paper?
2. What are the advantages and disadvantages of ChatGTP and AI in education and academia?
3 How will it enhance learning?
4. How will it compromise academic integrity?
5. How about researchers who use ChatGTP to write?
Dear RG group,
We are going to examine different AI models on large datasets of ultrasound focal lesions with definitive (patological examination after surgery in malignant leasions and biopsy and follow up in benign ones) final diagnosis. I am looking for images obtained with different us scanners with application of different image optimisation techniques as eg harmonic imaging, compound ultrasound etc. with or without segmentation.
Thank you in advance for your suggestions,
RZS
Is The Introduction Or AI Good For Our Academic System?
I am curious if we, the epidemiologists and public health physicians, could think of modified methods using AI in future research some of those may be challenging the traditional epidemiological study designs.
I will be happy to welcome suggestions and ideas in this context, and to perhaps write an article together in this context.
Dear colleagues, our team is working on development of a cloud-based AI powered research assistant to be trained on the literature in your specific field and to become a companion and SME aiding your literature review, gap identification, formulation of research problems, questions and hypotheses, and terminology and term definition management. Using a MS Word plugin, it will also be capable to assist with the academic writing process (form & style). The application will learn from interactions with the user and will proactively search the online sources for relevant new literature to boost your research by doing more, discovering more, achieving more by augmenting research capabilities and by removing tedious manual tasks. We also work on integrating it with Zotero, GoogleScholar, and online library repositories.
We will start a crowdsourcing campaign to help finance development of this application designed exclusively for academic researchers and students after completing a feasibility study and development of a working prototype.
Would this be of interest to you personally and what recommendations would you have for the development team?
Thank you for your help!
Explaining the role of artificial intelligence in achieving well-being for the workforce in business organizations
Does the application of Big Data Analytics and artificial intelligence technologies in the credit scoring processes of potential borrowers increase the profitability of commercial banks' lending activities?
Does the application of Big Data Analytics and artificial intelligence technologies in the processes of screening the creditworthiness of potential borrowers in order to improve, among other things, credit scoring analytics and credit risk management increase the profitability of commercial banks' lending activities?
In recent years, the scale of application of ICT and Industry 4.0/5.0, including Big Data Analytics and Artificial Intelligence technologies in financial institutions, including commercial banks, has been increasing. The banking sector is among those sectors of the economy where the implementation of new information technologies used to build banking information systems is progressing rapidly. This process in highly developed countries has been taking place since the 1960s. Subsequently, the development of computer science, personal computer technology in the 1970s and 1980s, the development of the Internet and business applications of Internet technology since the 1990s and then the development of technologies typical of Industry 4.0/5.0 set the trends of technological progress, the effects of which in the form of new technological solutions quickly found applications in financial institutions. Commercial banks operating in the model of classic deposit-credit banking usually generate the largest part of their revenues from the sale of bank loans and credits. Large universal banks also develop selected elements of investment banking, in which they finance the construction of housing estates through their own development companies, make financial transactions with securities, financial transactions in foreign exchange markets and other capital markets. In all these areas of activity, the key categories of banking risk that banks manage include credit and interest rate risk and other financial risks, i.e. liquidity risk, debt risk. In addition, the key categories of risk that the bank manages in its banking operations include asset-liability mismatch risk in the balance sheet and various categories of operational risks related to the performance of certain activities at the bank, including personnel operational risk related to the staff employed, technical operational risk related to the technical equipment used, system operational risk related to the IT systems used, etc. On the other hand, risks operating in the bank's environment and affecting the bank's operations and indirectly also the bank's financial performance include market risk of changes in the prices of specific assortments relating to specific markets in which banks operate; foreign exchange risk associated with transactions made using different currencies; investment risk within investment banking; systemic risk associated with the functioning of the financial system; political risk associated with the government's economic policy; risks of high volatility of macroeconomic development of the economy associated with changes in the economy's economic situation in the context of business cycles realized on a multi-year scale, etc. However, in a situation where lending activities are the main types of sources of income for a commercial bank then a particularly important category of banking risk that the bank manages is credit risk. On the other hand, due to the rapid development of electronic, Internet and mobile banking, cyber risk management is also growing in importance. New ICT information technologies and Industry 4.0/5.0, including Big Data Analytics and Artificial Intelligence technologies, can be increasingly helpful in managing each of the aforementioned risk categories. The aforementioned new technologies prove to be particularly helpful in the situation of their effective implementation into banking activities in order to improve the processes of managing, among other things, credit risk. An important element of individual credit risk management, i.e. with regard to individual credit transactions, are the methodologies, procedures, processes, etc. concerning the analysis of a potential borrower's creditworthiness and credit risk arising from a bank loan carried out in commercial banks. In view of the above, the implementation of new technologies to support the implementation of the processes of examining the creditworthiness of potential borrowers and improving, among other things, credit scoring analytics, are particularly important aspects of credit risk management, which may translate into increased profitability of commercial banks' bank lending activities.
I described selected issues of improving credit risk management processes, including the issue of screening the creditworthiness of potential borrowers and credit scoring analytics, in an article of my co-authorship:
Determinants of credit risk management in the context of the development of the derivatives market and the cyclical conjuncture economic processes
IMPROVING MANAGING THE CREDIT RISK IN CONDITIONS SLOWING ECONOMIC GROWTH
THE IMPLEMENTATION OF AN INTEGRATED CREDIT RISK MANAGEMENT IN OPERATING IN POLAND COMMERCIAL BANKS
Importance and implementation of improvement process of prudential instruments in commercial banks on the background of anti-crisis socio-economic policy in Poland
GLOBALIZATIONAL AND NORMATIVE DETERMINANTS OF THE IMPROVEMENT OF THE BANKING CREDIT RISK MANAGEMENT IN POLAND
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Does the application of Big Data Analytics and artificial intelligence technologies in the processes of screening the creditworthiness of potential borrowers in order to improve, among other things, credit scoring analytics and credit risk management, result in an increase in the profitability of commercial banks' bank lending activities?
Does the application of Big Data Analytics and artificial intelligence technologies in the credit scoring processes of potential borrowers result in increased profitability of commercial banks' lending business?
Can Big Data Analytics and artificial intelligence help improve credit scoring and increase the profitability of commercial banks' lending activities?
What do you think about this topic?
What is your opinion on this issue?
Please answer,
I invite everyone to join the discussion,
Thank you very much,
Best regards,
Dariusz Prokopowicz
The above text is entirely my own work written by me on the basis of my research.
In writing this text, I did not use other sources or automatic text generation systems.
Copyright by Dariusz Prokopowicz
Calling on international research scholars to meet here to collaborate on research into AI issues and applications in finance, economics, accounting, business and management.
This call remains open from 2024 to 2025
The collaborating authors will take responsibility for developing a meaningful research agenda, completing the research and deciding where to publish it.
As the convener, I will regularly post available call for papers/chapters that authors can send their completed work to.
In Uganda, the financial services sector is increasingly adopting artificial intelligence (AI) to streamline operations and enhance customer experiences. This research question seeks to explore the effects of AI integration on customer satisfaction and trust within this context. Specifically, it aims to understand how AI-driven services, such as personalized financial advice, fraud detection, and customer service chatbots, are perceived by users in terms of their reliability, efficiency, and overall impact on the customer experience.
The inquiry is grounded in the broader context of digital transformation in emerging economies, where the adoption of technology in financial services presents both opportunities and challenges. Given the rapid pace of AI development and its potential to revolutionize financial interactions, this research could provide valuable insights into consumer attitudes and inform strategies for implementing AI in a way that fosters trust and satisfaction.
For the research how can i established this idea?
It is evident that Artificial intelligence (AI) is rapidly transforming our world, but with great power comes great responsibility. That's why Responsible AI is no longer a niche concern - it's critical for everyone.
What is responsible AI?
Why should we care?
How can you get involved?
The future of AI is in our hands. Let's work together to ensure it's a force for good.
Feel free to share your thoughts on Responsible AI in the comments!
#ResponsibleAI #FutureofAI #AIethics #AIfairness #ExplainableAI #Diversegroupofpeople
I think by merging AI's personalized learning capabilities with the interactive, community-oriented features of social media, language learning can become a more dynamic, engaging, and effective process, deeply impacting both the cognitive development and social integration of learners.
AI systems can be used to collect and analyze large amounts of data on human emotions, which can help us to better understand the underlying patterns and causes of emotions. They can also be used to develop new therapies and interventions for emotional disorders.
The future of wearable technologies is likely to see several innovative advancements that can enhance their functionality, usability, and impact on various aspects of our lives.
For Example:
Humane officially launches the AI Pin, its OpenAI-powered wearable
The Ai Pin, as the device is called, is designed to be worn on clothing and can be tapped to talk to a virtual assistant powered by technologies from ChatGPT-creator OpenAI and cloud computing power from Microsoft (MSFT.O). It uses a laser projection system to display text and monochromatic images on a user's hand.
Learn more about Ai Pin: https://lnkd.in/dhvR4h4p
A new disease is beginning to appear in humans, which is now being remembered as AI.
There are many questions about this disease, but the important point is to control our mind and body with our own hands.
Dear Colleagues and Researchers,
Greetings!
I'm currently editing a book titled “Building Business Knowledge for Complex Modern Business Environments” with IGI Global and would like to invite you to contribute to the book by submitting your Chapters. Here is the link, and below you will find the deadlines.
About The Book
This book serves as a comprehensive guide to essential components necessary for navigating the complexities of contemporary business landscapes. It delves into crucial aspects such as strategic planning, financial management, technological integration, marketing strategies, and sustainable practices. Through detailed analysis and practical examples, the book offers insights into the dynamic interplay of these elements and their significance in achieving business success in today's rapidly evolving global marketplace. It caters to entrepreneurs, business professionals, educators, and students seeking a thorough understanding of fundamental principles essential for thriving in the modern business environment. The aim of this book is to empower individuals and organizations with the knowledge and tools necessary to navigate the complexities of modern business environments effectively.
The book also contributes significantly to the research community by synthesizing current knowledge and best practices in various fields related to business essentials. It offers a comprehensive overview of essential topics, providing researchers with a foundational understanding to explore deeper complexities and emerging trends within specific areas of interest. Additionally, the book may inspire further research inquiries into the intersectionality of business essentials with emerging technologies, socio-economic factors, and environmental sustainability, fostering interdisciplinary collaboration and innovation within the academic community.
Recommended Topics
1. Vision and Strategy.
2. Effective Organizational Leadership.
3. Financial Management.
4. Business Analysis and Excellence.
5. Business Ethics.
6. Sales and Marketing.
7. Business Sustainability and Diversity.
8. Human Resources, Culture, Team Building, and Talent Management.
9. Customer Experience Management and Engagement.
10. Marketing Management.
11. Engineering Management.
12. Project and Portfolio Management.
13. Risk Management and Governance.
14. Quality Management.
15. Entrepreneurship and Innovation.
16. Technological Integration and Artificial Intelligence (AI) Applications.
17. Operational Efficiency.
18. Supply Chain and Procurement Management.
Important Dates
May 19, 2024: Proposal Submission Deadline
June 2, 2024: Notification of Acceptance
August 11, 2024: Full Chapter Submission
September 22, 2024: Review Results Returned
October 20, 2024: Final Acceptance Notification
October 27, 2024: Final Chapter Submission
Best Regards,
Dr. Ahmed Sedky
New learning can range from an astronaut returning from space to adjust his vestibular system to 1G, an individual associating a group of stimuli to generate a conditioned response, or someone memorizing a speech before facing an audience. In all cases, the neocortex must be engaged and signals transmitted to the cerebellar cortex to alter the synaptic weights so that the new behavior—of the vestibulo-ocular reflex, of classical conditioning, or of language acquisition—yields an automated response which is the goal of all learning. In short, how is the declarative conscious code of the neocortex converted into executable code? Sultan and Heck (2003) suggest that the mossy fibre-granular cell-parallel fibre synapses onto Purkinje neurons is such that inputs from the senses (from neocortex, brain stem, and spinal cord) can be order sequentially along a collection of parallel fibres, so that the synaptic input to a single Purkinje neuron [of which there are 15 million in human cerebellum and which contains a vast dendritic arbor (Andersen et al. 1992; Braitenberg and Atwood 1958; Nairn et al. 1989)] is synchronized to generate an optimal response whether excitatory—or inhibitory (see: Miles and Lisberger 1981). It is noteworthy that input from a single granular cell is typically insufficient to drive a Purkinje neuron, suggesting that it is the collective input from many granular elements that shapes the firing of Purkinje cells (Sultan and Heck 2003). It is the sequential timing along the parallel fibres as triggered by the mossy input that elicits new learning, which has millisecond temporal resolution (Sultan and Heck 2003). For example, when a motor command is issued by the motor cortex a signal is sent to the cerebellar mossy fibres which is then compared at a Purkinje circuit to the feedback signals from the spinal proprioceptors to assess whether the command and the feedback signal are aligned as generated via the parallel fibres (Heck and Sultan 2002). If aligned, this signals optimal performance and the end of the learning process. Sultan and Heck (2003) suggest that at least 50,000 (relatively independent) Purkinje networks throughout the cerebellar cortex of humans can be engaged simultaneously via mossy fibre input to facilitate learning (Heck and Sultan 2002; Sultan and Heck 2003). This global representation allows for all aspects of a body’s musculature to be integrated with sensory information (as conveyed from neocortex, brain stem, and spinal cord) during learning (Thach et al. 1992). That the mossy fibre input to the cerebellar cortex has global reach well beyond the circuits critical for the performance of a specific task is well established (Hasanbegović 2024), making the cerebellum an optimal learning machine to fine tune all aspects of a performance in preparation for playing a musical instrument at the highest level or for competing at the Olympic games, for instance.
Hello everyone and thank you for reading my question.
I have a data set that have around 2000 data point. It have 5 inputs (4 wells rate and the 5th is the time) and 2 ouputs ( oil cumulative and water cumulative). See the attached image.
I want to build a Proxy model to simualte the cumulative oil & water.
I have made 5 models ( ANN, Extrem Gradient Boost, Gradient Boost, Randam forest, SVM) and i have used GridSearch to tune the hyper parameters and the results for training the models are good. Of course I have spilited the training data set to training, test and validation sets.
So I have another data that I haven't include in either of the train,test and validation sets and when I use the models to predict the output for this data set the models results are bad ( failed to predict).
I think the problem lies in the data itself because the only input parameter that changes are the (days) parameter while the other remains constant.
But the problem is I can't remove the well rate or join them into a single variable because after the Proxy model has been made I want to optimize the well rates to maximize oil and minimize water cumulative respectively.
Is there a solution to suchlike issue?
When a model is trained using a specific dataset with limited diversity in labels, it may accurately predict labels for objects within that dataset. However, when applied to real-time recognition tasks using a webcam, the model might incorrectly predict labels for objects not present in the training data. This poses a challenge as the model's predictions may not align with the variety of objects encountered in real-world scenarios.
- Example: I trained a real-time recognition model for a webcam, where I have classes lc = {a, b, c, ..., m}. The model consistently predicts class lc perfectly. However, when I input a class that doesn't belong to lc, it still predicts something from class lc.
Are there any solutions or opinions that experts can share to guide me further in improving the model?
Thank you for considering your opinion on my problems.
In the above paper, the author states many of the O & T implied in the current AI development and market but I think two important key questions are missing:
- Economical impacts: to date, no study I know of has published the _cost_ of training and using Ai in real applications, in fact, even the stated "pro" access cost seem too low in regards to the amount of energy consumption that has been reported.
- Societal impacts: predatory business Ai practices reported in the press seem to indicate a strong desire from business leaders to _reduce_ their workforce, which will not be compensated by the hiring of "Ai experts".
Generative AI in its very childhood and with its currently very limited potential can create (or at least perfectly mimic or steal) art or code as excellent as human's art or code etc., if not better. I for one see no bright future for (human) creativity once "creative" AI becomes too powerful, too available, and too economic --which is probably just a few years later.
Almost no creative humans will be eager to do creative work anymore, because their hard work will be bested by AI in milliseconds. AI will do it all. AI will even have its own ideas.