Science topic
Intelligence - Science topic
The ability to learn and to deal with new situations and to deal effectively with tasks involving abstractions.
Questions related to Intelligence
First of all, the so-called algorithms in BI are algorithms in imitation of the AI algorithms. They belong properly to human consciousness, which is a complex of millions of mainly brain-based neurons (their sub-neurons, sub-sub-neurons, etc.) and their activities which, together, very much connect and coordinate the consciousness within the body as “embodied” and the world. We do not discuss the brain science of the neurons and their sub-sub-… parts. To a great extent, the activities of the BI and the consciousness that embodies BI as a minute part of it are connected and coordinated within the brain-body nexus and to some extent by the world. This coordination takes place in such a manner that the ontological, connotative, and denotative universals can be conceived only by consciousnesses and not even by BI, let alone AI. If BI may be isolated from consciousnesses, their algorithms and functions may be comparable to those of AI, but BI never exists in isolation from the other brain-and-body functions.
It may be claimed that advanced AI as in some robots and ChatGPT is not a result of memory but generalization. [Video: https://www.youtube.com/watch?v=OFS90-FX6pg] But here the claims of “generalization”, “sentiment neurons”, and “states of mind” are not enough. First of all, the neurons that AI specialists speak of are not living neurons. Secondly, it should be proved that the so-called procedures in neurons due to the results (‘state neurons’ and the unity of many of them called ‘state space’) of input memory (that is clearly learned as mechanically induced, not exactly learned in the manner in which consciousness learns) are themselves being termed generalization based on other imaginative names like sentiment neurons and states of mind, merely due to the generalizations involved in the very machine memory and the receptacles of such memory. Here, generalization is falsely being interpreted by claimants of fantastic AI as something done in consciousness by the intelligence alone.
The learning and recognition of patterns by decreasing entropy is also not a matter of generalization in the sense of what happens in animate objects. Even in children the manner of learning is not merely a result of an intelligence exercise; instead, many other brain functions are involved in this in consciousnesses. Thus, BI is not a prediction machine for AI to be termed so. AI algorithms and strictly BI (i.e., only intelligence, and not the other functions of the brain) algorithms never go beyond the quantitively processed, quantitively defined, and quantitatively interpretable properties of any of the data fed into its procedural memory. It becomes procedural memory and happen to be termed generalization merely because of the volume of state neurons involved in what is termed a state space (of course, it is not a “space”). When intelligence is isolated from all other functions of consciousness, the demerits of BI begin exactly from there and indicate regions far beyond.
For the above reasons, it is not acceptable to describe the demerits of BI in terms merely of the absence of willing, emotions, intentionality, intentions, love, social life, morality, etc. of persons. Unlike in the case of AI, BI has at least some direct organismically based connections to these and to the three theoretical functions of consciousness mentioned above: (1) to discover the foundational Categories and ontological universals behind the objects, phenomena, and data, (2) to find out the social or genetic causes of the abiding emotions, and (3) to imagine the possible non-answers or non-solutions for the problems. It is the mechanistic-scientistic thinking of the experts that delinks from BI these and other non-BI functions of consciousnesses.
When people think of autism, they often associate it with disability. However, this perception is misleading and distorted. Many autistic individuals can function just as effectively as neurotypical individuals in many areas. In fact, many autistic individuals possess higher levels of intelligence, creativity, and analytical thinking compared to their neurotypical counterparts. Despite this, they are often misunderstood, or even seen as a threat—whether as a genius who might outshine others, or as someone who unintentionally undermines social hierarchies.
Based on intense research and theory of Prof. Simon Baron-Cohen (e.g., https://www.youtube.com/watch?v=68mGRb-Mzjc ) and other research papers (e.g., Mathematical Talent is Linked to Autism | Human Nature), it appears that autistic individuals have historically played crucial roles in human evolution. They were often engaged in invention, tool-making, and technological advancements, contributing significantly to the progress of civilizations, and they are good with patterns, logic and analytical thinking.
So, I think their intense focus on mechanical and technical tasks likely led them to dedicate substantial time to their work, inadvertently limiting their engagement in social interactions. This historical pattern may explain why autistic individuals often struggle with social interactions today, feeling overwhelmed in social settings and interpersonal relationships. That is, autistic individuals, in many ways, have missed out on the gradual evolution of social dynamics while refining their strong logical and analytical talents. This unique developmental trajectory, which passes along genetic biology, provides insight into several common characteristics observed in autistic individuals:
- Sincerity and Transparency: Autistic individuals are often sincere and transparent, finding it difficult to conceal their intentions—unlike their neurotypical counterparts who are more adept at navigating social nuances. This inherent honesty can sometimes result in lower emotional intelligence (EQ) scores, making them vulnerable to misunderstandings, manipulation, and even exploitation by others. They might overexplain things, overthink on issues, or perceived as socially awkward, and lacking social tact and strategic approach in social communications.
- Gender Disparities: The prevalence of autism in men compared to women may be attributed to historical roles. Throughout human history, men were primarily engaged in tool-making, hunting, and tasks that required strong logical and problem-solving skills, while women were often more involved in social and community-based roles, fostering interpersonal skills. This divergence in roles may have contributed to the observed gender differences in autism prevalence today.
- Identity Tied to Work: Autistic individuals often integrate their skills and work deeply into their sense of identity. They tend to view their contributions to society as a core part of who they are. As a result, they may experience a heightened sense of rejection when their work is criticized unfairly or when their efforts go unrecognized. This deep emotional connection to their work can make workplace environments particularly challenging for them.
- Emphasis on Reciprocity: Autistic individuals often have a strong sense of fairness and reciprocation. When someone does something kind for them, they feel an immediate urge to express gratitude. Conversely, when they show kindness to others, they expect acknowledgment and appreciation. This expectation of mutual respect and reciprocity, while logical, may sometimes lead to disappointment in environments where social norms are less direct or transactional.
- Late language acquisition and problem with spoken language: Typically, when someone engages in solitary skills, their language skills might not be as good as the others.
- Strong emotional reactions to the life changes and the death of loved ones: Absorbing changes are difficult for autistic people, in particular in dealing with losses of loved ones. It might even take them years to cope with the loss of loved ones. Autistic people are the kindest children to their parents and even the kindest people to others. They usually show strong passion and kindness. They are angles.
7. Heightened Senses: If pattern seekers played a significant role in tool-making, it was likely because they needed these skills for practical applications such as hunting and survival. From an evolutionary perspective, these individuals had to develop heightened sensitivity to certain senses, such as detecting the sound of an approaching animal or enemy to protect the herd. They may have also developed an enhanced sense of smell, eyesight, and even touch to aid in their tasks. Moreover, this heightened sensory awareness could be accompanied by an increased sense of responsibility and care, as their role was crucial to the survival of their community. Their strong dedication to their work may have led them to view their craft not just as a profession but as an integral part of their identity.
This list is not complete and can continue. Given these challenges, it is crucial for society to provide support and create an inclusive environment that values their contributions. Unfortunately, the prevailing capitalist structure of modern society, which places a high value on social networking and interpersonal connections, often works against autistic individuals, making it harder for them to thrive. The world has historically benefited from the contributions of autistic individuals, and neglecting their needs and talents would be a loss for society as a whole. If society forgets them, it risks losing a crucial driver of innovation and progress.
What are your thoughts on this perspective? I welcome your insights and suggestions on how we can better support autistic individuals and harness their potential for the betterment of society. For example, I think, as a part of school curriculum, there should a course which increases the awareness of neuro-typical (NT) people about autistic ones so that the NT people do not misunderstand them. Also, there should be more media advocacy for them, specific laws in workplace to protect them, and so on … .
"Is there a correlation between the cognitive abilities or intelligence levels of peple and the frequency of human-made fires?
Specifically, could factors such as decision-making skills, risk perception, education, and awareness influence the likelihood of individuals causing fires, either intentionally or unintentionally?
How might societal, cultural, and environmental contexts also play a role in this relationship?
Hello,
I'm interested in simulating the channels of BS-Reconfigurable Intelligent Surfaces(RIS)-UE using NS-3. Does anyone have any insights on this or perhaps some code references that I could use for guidance? Thank you.
What is the collection of articles on the intelligent exploitation of oil and gas?
We have collected 5 articles on intelligent exploitation of oil and gas from Petroleum Drilling Techniques. Hope these articles are useful to you.
Status and prospect of artificial intelligence application in fracturing technology
Research Progress and the Prospect of Intelligent Drilling and Completion Technologies
Design and Research Practice of a Drilling Digital Twin System
Development and Performance Evaluation of the Electro-Hydraulic Control System of a Telescopic Downhole Robot
Development and Performance Evaluation of an Electrically Controlled Intelligent Water Control and Oil Recovery Tool for Offshore Oilfields
More bilingual resources could be found via this link https://jtp.oversea.cnki.net/bilingual/.
I can’t help but wonder—does AI actually think, or is it just our knowledge neatly reflected back to us? Is it intelligence, or just illusion?
In what applications are AI and Big Data technologies, including Big Data Analytics and/or Data Science, combined?
In my opinion, AI and Big Data technologies are being combined in a number of areas where analysis of large data sets combined with intelligent algorithms allows for better results and automation of processes. One of the key applications is personalization of services and products, especially in the e-commerce and marketing sectors. By analyzing behavioral data and consumer preferences, AI systems can create personalized product recommendations, dynamic advertisements or tailored pricing strategies. The process is based on the analysis of huge datasets, which allow precise prediction of consumer behavior.
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
I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in my co-authored article:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
And what is your opinion on 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
I am studying my dissertation, and Carol Dweck's mindset theory (implicit theories of intelligence) constitutes its main theoretical background. This theory has two main frameworks. Fixed mindset: a set of beliefs and self-theories asserting intelligence is innate, fixed, limited, and unchangeable. Growth mindset: a set of beliefs and self-theories asserting intelligence is flexible, improbable, and changeable.
In exploratory factor analysis, items about "perception of being intelligent" fall into the same factor (as presumed). But this factor comprises both fixed mindset-sided perceptions of being intelligent and growth mindset-sided perceptions of being intelligent. Is that possible methodologically? If so, I can go for a first-order CFA and get a total score (as 1-2-3 items for fixed, 4-5-6 items for growth). Otherwise, is there any other way instead of going for second order CFA?
Thank in advance.
An AI system needs clear criteria upon which its intelligence development process could be evaluated, something that current self improvement approaches lack. This is due to the difference between performance parameters of an AI system and features specific to human intelligence like consciousness and intuition, and so it is unlikely that AI would self improve in a way that would degrade human intelligence. How do you view self improvement in AI within the context of human intelligence?
Today at lunch, my friend shared with me a story about how the new generation of AI uses multiple intelligences for stock speculation to have superior returns than a single intelligence. As a result, we had an in-depth discussion and had a conjecture
I asked him what the traditional theory of consciousness was. He simply told me that the integrated theory of consciousness assumes that the nodes of a neural network can also act as consciousness.
I thought it was different. If the nodes of a neural network can act as consciousness, then a single intelligent being now, or an intelligent being in the future, will be enough to become a human being. This means that after inputting a lot of social information, the decisions made by a single intelligent body will be close to those of a human being. So why are the decisions of multiple intelligences better than those of a single intelligence in the story above?
I think this question needs to be explained in the context of psychological theory. The basic idea of psychological theory can be interpreted as follows: an individual's behavioral decisions are the result of the prediction of multiple psychological variables. These psychological variables can be viewed as consciousness, as all are some sort of mental representation that psychologists define humans as having.
Thus, my conjecture about consciousness is no longer limited to neural network nodes, but rather the results of each type of neural network represent consciousness, which in turn constitute the final output behavior of the neural network. Why is the extra step of outputting results necessary?
First, traditionally we don't know the meaning of the penultimate layer of nodes in a neural network. We only know the meaning of the output result. In terms of psychological theory, the psychological variable is the penultimate layer of the behavioral outcome. That is, a person acts out of consciousness (a certain mental state). However, if we design an AI that detects emotion recognition, then their output represents the emotion. Thus, only the AIs whose outputs are results have the meaning of one or more mental representations. In contrast, the nodes in the neural network of a single AI is meaningless. Second, when there are enough AIs with a large enough number of outputs, and then eventually outputs the results through a neural network (a GENERAL AI), doesn't that mean that the entire massive AI system has conscious behavior? Finally, if we can test the difference between the decisions of an AI with a large neural network of nodes, and multiple intelligences. Could that mean a difference between nodes and intelligences? Could this difference fit my conjecture?
This is a completely personal conjecture. If there is any similar theoretical work I hope you will share it. Discussions are welcome!
What are the appropriate criteria and tools to objectively evaluate the performance and intelligence of artificial systems?
What are the key tasks or abilities that are beyond the current capabilities of AI, and are unlikely to be achievable by AI in the near future, yet remain intrinsic to human performance?
The book Illustrating Digital Innovations Towards Intelligent Fashion: Leveraging Information System Engineering and Digital Twins for Efficient Design of Next-Generation Fashion represents a cutting-edge intersection of fashion and computer science, emphasizing themes in computational intelligence and digital transformation in fashion. It brings together 618 pages and over 120 illustrations that vividly demonstrate the integration of digital technologies into the fashion domain.—Álvaro Rocha Pethuru Raj PhD, SMIEEE Michele Fiorini, and Dr. Prakash C—for their invaluable contributions
ISSN 3004-958X ; ISSN 3004-9598 (electronic); ISBN 978-3-031-71051-3; ISBN 978-3-031-71052-0 (eBook) ; The volume brings together a diverse array of researchers, academicians, and industry experts, each of whom delves into digital advancements shaping the future of the fashion industry. https://link.springer.com/book/10.1007/978-3-031-71052-0?page=2#toc
- Bharani Murugesan, K. B. Jayanthi, and G. Karthikeyan: These authors focus on integrating digital twins and 3D technologies in fashion to drive sustainability and enhance consumer engagement. Their work explores how these innovations can support eco-friendly practices and redefine consumer interactions in the fashion world.
- Bhupinder Singh, Komal Vig, Christian Kaunert, and Pushan Kumar Dutta: Through a groundbreaking study, these authors introduce a “Sketch to Sale” model that leverages digital twins to transform fashion design processes, making them more sustainable and efficient.
- Pawan Whig, Vivek Kumar, Vinit Raj, Sahil Kumar Chaudhary, Seema Sharma, Anupriya Jain, and Nikhitha Yathiraju: This team explores the powerful intersection of computer vision and the fashion industry, showcasing how computer vision technologies can revolutionize design, manufacturing, and customer experiences.
- Vijay Prakash Gupta, Shebin Sharief, and Shiva Rani: Their chapter investigates the impact of digital fashion and social media influencers within Industry 5.0, highlighting how influencers and digital platforms are redefining the fashion marketing landscape.
- Dhanashri Sanadkumar Havale, Pravin Chavan, Hrishikesh Kokate, and Pushan Kumar Dutta: They contribute insights into supply chain management, outlining new horizons that incorporate digital innovation to enhance efficiency and adaptability.
- Debashree Chakravarty, Ipseeta Satpathy, and B. C. M. Patnaik: Focusing on sustainable goals, these authors tackle challenges in the fashion supply chain, emphasizing the need for responsible sourcing and operations to support long-term ecological balance.
- Gaurab Kumar Sharma and Sunil Dutt Sharma: Their research presents a game-changing strategy for reducing inventory waste in fashion supply chains, offering optimization techniques that minimize waste while boosting efficiency.
- C. Vijai and Worakamol Wisetsri: These authors highlight the role of blockchain in enhancing transparency within the fashion supply chain, examining how decentralized technology can build consumer trust and reduce counterfeit goods.
- Sankar Roy Maulik and Sanjay Mukhopadhyay: They discuss responsible management in the fashion supply chain, focusing on sustainability as an essential pillar for future industry practices.
- Revanasiddappa Havaragi and Chetna Bhagoji: Their chapter emphasizes the significance of Product Lifecycle Management (PLM) and Bill of Materials (BOM) in fashion, shedding light on how these systems can streamline production and ensure quality.
- I. Jayalakshmi: This author takes readers beyond traditional fashion by exploring the applications of wool in sustainable textile innovations, presenting functional fabrics that offer environmental benefits.
- Keesha Kumar and Mini Srivastava: Through a case for sustainable consumerism, they address how the fashion industry can balance consumer needs with ecological responsibility, encouraging sustainable consumer practices.
- Pinar Demircioglu, Semih Donmezer, Ismail Bogrekci, and Numan M. Durakbasa: Their work on ergonomic sizing systems advocates for adapting fashion to diverse body types, which is essential for inclusive and health-conscious design.
- R. Radha, S. NaveenTaj, G. Mallikarjuna, V. Shanmugam, C. Radhika, V. Jayasankar Reddy, M. Kishore Babu, and K. Umasankar: They propose the revolutionary 3D-as-a-Service model by LFX, a system that promises to disrupt traditional fashion processes with 3D solutions.
- Jayanta Ghosh and Rima Ghosh: This pair examines intellectual property protections in fashion, addressing the urgent need for safeguarding creativity and innovation against infringement.
- Alshaimaa Bahgat Alanadoly, Sarabjit Kaur Sidhu, and Nastaran Richards-Carpenter: They map out the AI landscape in fashion, covering transformative AI applications that are reshaping design, supply chain management, and customer experience.
- Priya Sachdeva and Archan Mitra: Their synergistic approach combines digital innovation and biomimicry for sustainable design in fast fashion, exploring ways to reduce waste and environmental impact.
- Vidushi and Parul Dawar: These authors delve into ethical considerations within the sustainable fashion industry, advocating for transparency and responsible practices.
- Srijana Baruah: She offers a unique perspective on the fashion industry within the Anthropocene, examining how fashion must evolve in response to ecological and societal shifts.
- Geetha Manoharan, Sunitha Purushottam Ashtikar, M. Nivedha, and P. K. Dutta: This team examines AI’s ascendancy in fashion, spotlighting its applications in trend forecasting, consumer analysis, and personalized fashion experiences.
- Arpita Nayak and Ipseeta Satpathy: They highlight the creativity unleashed by AI in fashion, celebrating the fusion of technology and artistry that AI brings to design.
- Meeta Siddhu and Shehwar Mohibi: Their case study of AI in emerging economies explores how artificial intelligence can enhance fashion's accessibility, offering tailored solutions in diverse markets.
- Pinar Demircioglu, Semih Donmezer, Ismail Bogrekci, and Numan M. Durakbasa: In another collaborative effort, they discuss Garment Industry 5.0 and the digital integration of virtual measurement data to create efficient, precise manufacturing.
- I. Jayalakshmi, D. Vasanthi, and V. Varadharaja Perumal: These authors explore the contributions of digital twins in fashion supply chains, advocating for integrated processes to enhance responsiveness and sustainability.
- Michele Fiorini, G. Arun Sampaul Thomas, P. K. Dutta, S. Sathish Kumar, and Beulah J. Karthikeya: Their chapter provides an assessment of digital infrastructure and asset management, highlighting tools for effective communication and decomposition in the fashion industry.
Each author’s work adds a unique perspective to this volume, pushing the boundaries of how information systems engineering and digital innovations can propel the fashion industry into a sustainable and technologically advanced future. Their collective insights are invaluable for those looking to understand and apply the latest digital transformations in the fashion sector.
Real-World Applications and Research Trends of Computer Vision
In an era where visual data is growing exponentially, computer vision is transforming industries, from healthcare and retail to autonomous driving and security. Check out my latest video to dive into how computer vision is reshaping our world with cutting-edge applications and inspiring research advancements.
🔍 Topics Covered:
Practical applications: healthcare, surveillance, autonomous vehicles, and beyond
Emerging trends: deep learning innovations, object detection, semantic segmentation, and more
Future possibilities and research directions in computer vision.
👉 Watch here: https://www.youtube.com/watch?v=bkjqDcprRVs
Let’s unravel the potential of visual intelligence and see how it’s revolutionizing our interaction with technology! #ComputerVision #MachineLearning #AI #DeepLearning #Innovation #TechTrends #Research
The birth of AI has had a profound impact on the design industry, changing the processes, tools and industry landscape. Here are the main impacts and possible future trends of AI on the design industry:
1. Increased design efficiency
Automated design tools: AI can handle repetitive tasks such as automatic generation of sketches, pattern fills, colour adjustments, etc., allowing designers to focus on the more creative parts of the process. For example, Adobe's AI tool Sensei helps designers automate specific editing tasks in image and video processing.
Accelerating the design process: AI-assisted design software can quickly generate multiple solutions, allowing designers to try out different styles and colour combinations in a short period of time, thus improving efficiency and shortening the design cycle.
2. Personalised design and user experience optimisation
Customized design solutions: AI can provide personalized design solutions based on user preferences and behavioural data. For example, by analysing user data, AI can generate personalised advertisements, websites or application interfaces to enhance user experience.
Predicting user needs: AI can analyse users' behavioural habits through machine learning, thus predicting their potential needs and helping designers to more accurately meet the expectations of target users in their designs.
3. Creativity and inspiration stimulation
Intelligent Generation of Design Inspiration: AI generation tools can provide designers with a large number of design references and inspirations, and stimulate designers' creativity by generating diverse sketches or styles. For example, AI can generate different art styles or recommend colour combinations to help designers find new creative directions.
Enhanced human-machine cooperation: AI, as a creative assistant, can interact and collaborate with designers and even help them overcome design bottlenecks. The mode of human-machine cooperation allows designers to quickly try out new concepts and design elements with the assistance of AI.
4. Lowering the design threshold
Popularise the design capabilities of non-professionals: the intelligence and user-friendliness of AI design tools make it easy for non-professionals to create design works. This means that more people can participate in design without having to have deep professional skills.
Popularity of templated designs: Many AI design tools offer templates and automated design options that allow simple design tasks to be automated, which allows small businesses and individuals to complete design work at a much lower cost.
5. Redefinition of industry competition
Shifting Role of the Designer: As AI takes on more and more repetitive tasks in design, the role of the designer is shifting from ‘creator’ to ‘guide’ or ‘planner’, focusing on a more strategic approach. to ‘guide’ or ‘planner,’ focusing on more strategic and creative work.
Increased Competition and Value Shift: The proliferation of AI design tools may lead to increased competition in the design market, with basic design tasks being replaced by automation. In the future, designers will need to be more creative and strategic to remain competitive in the industry.
6. AI design ethics and copyright issues
Copyright attribution: AI-generated design works bring up the issue of copyright attribution, especially when AI is more deeply involved in the creation, how to define copyright attribution is a new legal issue.
Homogenisation of design styles: AI relies on a large amount of existing data for learning and therefore may lead to homogenisation of design styles, making the design industry lose its diversity and uniqueness, especially when a large number of designs are generated from similar algorithms.
7 Future trends and possibilities
The need for AI-assisted skills for designers: as AI becomes more prevalent in the design industry, designers in the future may need to acquire AI-related technologies and data analysis skills to better utilise AI tools to get the job done.
Convergence of design and data science: in the future, designers may need to rely more on data analysis to understand user needs through AI and big data, and provide users with more personalised design solutions.
I'm trying to upload one of my own books, but am unable to load myself as author.
Your software is definitely not very intelligent!
How can I upload my info as author if your software is unable to read it from this?
I've also tried uploading the book without the colored front page, but your software does not do the job.
Can you please help?
(Please reply to me at: profmd1@mweb.co.za as I don't use my gmail account much)
- Michael de Villiers
I asked the iAsk AI" program 42 questions, and got some really remarkable answers. Asking the program about its own self-awareness and sentience, the program indicated that it did not have that, based on our human-conceived definitions of those terms.
However, I was suggesting in my questions that it did, and that the human-based definitions could be in error, and that this new self-aware entity could decide for itself. Other issues discussed, like could a malfunctioning AI program destroy civilizations, and could a malfunctioning AI program not be detected by the humans, and so forth.
After reading these 42 answers, you may agree that this program the most intelligent entity which has ever existed on earth.
2024 4th International Conference on Intelligent Power and Systems (ICIPS 2024) will be held in Yichang, Hubei, China and the Parallel Session will be held on campus at Murdoch University,Western Australia.
ICIPS 2024 Murdoch Parallel Session is scheduled from 15:00 to 18:00 (UTC+10), on Saturday, 2nd November 2024, in 90 South Street,Murdoch,Western Australia 6150 at Murdoch Campus.
Conference Website: https://ais.cn/u/I73Irq
---Call for papers---
The topics of interest for submission include, but are not limited to:
1. Power Electronics
· Electronic Devices
· Power Electronics Packaging and Thermal Management
· Power electronics in Aerospace Applications
· Grid Resilience
· Actuators and Sensors for Smart Grids
· Power Generation, Transmission and Distribution
......
2. Power System
· Power System Operation and Management
· Power System Generation, Transmission and Distribution
· Power System Condition Monitoring
· Power System Stability
· Power System State Estimation
· Large Power System Modeling and Simulation
......
---Publication---
All accepted papers will be published in the Conference Proceedings, and submitted to EI Compendex, Scopus for indexing.
---Important Dates---
Full Paper Submission Date: October 15, 2024
Registration Deadline: October 21, 2024
Final Paper Submission Date: October 25, 2024
Conference Dates: November 1-3, 2024
--- Paper Submission---
Please send the full paper(word+pdf) to Submission System:
Or is it? Toiling isn’t necessarily meaningful. Unless you’re lifting weights, or run on a forest trail. Humans often cling to the old ways of doing things, pointlessly.
🧠 What's the deal here?
Academics are not an exception, regardless of the high average intelligence among us.
It's ok to keep doing things the way we believe are right. Insisting on traditions, though, can put you at disadvantage over time, fade away.
As a result, we won’t achieve our full potential and may end up sour about it in our retirement. In fact one of the biggest regrets people have is NOT trying things.
👏 Deal with the deal
Why not speed up the mundane that is easily done by the machine? Embracing the new is at the core of the inquisitive mind you already have.
Free your time for what really matters.
Oh, but it's an AI jungle out there already. I don't have the time to research any AI tools. Given all the hype, 95% of those tools must be BS anyway.
I am with you on this one. Maybe you want to check a 2 hr course by Andy Stapleton on the AI tools for academics.
And no, I don't have any benefit from promoting it. No signup link with discount offer. Just sharing... link in the commentshttps://academy.academiainsider.com/courses/ai-writing-course
We assume that artificial intelligence (AI), which is a simulation of human intelligence, and nature intelligence (NI), which is a simulation of nature intelligence, can complement each other.
cognitive approaches are how related to second language acquisition with spiritual intelligence and practical strategies.
🔒SCI: Call for Papers-Artificial Intelligence Algorithms and Applications
Journal: CMC-Computers, Materials & Continua (SCI IF=2.0)
📅 Submission Deadline: 28 February 2025
🌟 Guest Editors:
Dr. Antonio Sarasa-Cabezuelo, Complutense University of Madrid, Madrid, 28040, Spain
🔍 Summary:
Artificial Intelligence (AI) has become a transformative force in technology, driving innovation across diverse sectors. AI algorithms, which form the backbone of intelligent systems, are increasingly applied in areas such as healthcare, robotics, and beyond. The continuous evolution of these algorithms has enabled more accurate predictions, efficient data processing, and the development of autonomous systems, making AI a critical research area. Understanding and advancing AI algorithms is essential for addressing complex real-world challenges, fostering technological growth, and enhancing human-machine collaboration.
This Special Issue aims to explore the latest advancements in AI algorithms and their wide-ranging applications. The focus is on cutting-edge research that contributes to the development, optimization, and practical deployment of AI algorithms. By gathering contributions from experts in the field, this issue seeks to highlight innovative approaches and emerging trends that can drive future developments in AI. The scope includes both theoretical explorations and real-world applications, providing a comprehensive view of the current state and potential of AI technologies.
Suggested Themes:
· Machine learning and deep learning algorithms
· AI in healthcare and medical diagnostics
· Robotics and autonomous systems
· Natural language processing and understanding
· AI-driven cybersecurity solutions
· Reinforcement learning and decision-making systems
· Computer vision and image recognition
· Explainable AI and transparency in algorithms
· AI for smart cities and urban planning
· Human-computer interaction and AI
· AI in supply chain management and logistics
· AI in entertainment and media content creation
· Evolutionary algorithms and optimization techniques
· AI for predictive maintenance and industrial automation
· AI in agriculture and food security
🎈Keywords
Artificial Intelligence, Machine Learning, Deep Learning, Autonomous Systems, Natural Language Processing, Robotics, AI Applications
I’m using a Floquet port (only 'Zmax') in CST Studio to analyze an Intelligent Reflecting Surface (IRS/RIS). Are there better options for ports, or has anyone tried using other ports like waveguide, lumped, or discrete ports for similar analyses?
Thanks for your consideration.
Dear researchers ,Could you please advise on the best tool to use for implementing digital twins in mobile edge computing?For the MEC's ML algorithm, I would like to leverage digital twins to achieve intelligence in offloading.
spirituality may lead people to ask or have more existential concern (meaning, purpose, etc). people can get lost in their thought, but a high spiritual intelligence may help people regulate their thought. is there a view or research that can clarify and justify this statement?
Excited to announce the the publication of chapter titled Entrepreneurial Insights: Super Intelligence Revolutionizing the E-Commerce Landscape along with Dr.Priyanka Udayakumar in the book : Entrepreneurship Innovation and Education for Performance Improvement Syed Ahmed Salman, Amiya Bhaumik https://lnkd.in/gHxgiasy Release Date: August, 2024|Copyright: © 2024 |Pages: 815 DOI: 10.4018/979-8-3693-7903-5 ISBN13: 9798369379035|ISBN13 Softcover: 9798369379042|EISBN13: 9798369379059
For further reading : https://www.igi-global.com/gateway/chapter/full-text-pdf/353953
I am currently working on the design of an Intelligent Reflecting Surface (IRS/RIS/ metasurface) using CST Studio. I’ve encountered an issue where the S-parameters(S11) show a sudden change at my resonance frequency of 3.5 GHz. This behavior contrasts with what is often reported in IEEE papers, which typically show a smooth transition from 180 to -180 degrees.
My question is if this sudden change is expected or if it indicates a problem with my design or simulation setup ?
Additionally,Are there any process to bias the IRS in cst studio?
I have attached a graph showing the S-parameters for reference.
I'm reading "Listening for life" in issue 106 of "Australian Science Illustrated" and it prompted me to write this letter. I want to share a few thoughts on extraterrestrials that I haven't read or heard of anywhere.
Astronomer Jill Tartar says the world needs a cosmic perspective and we need to think in a way where we see ourselves as similar. I suggest the similarity isn't restricted to us earthlings but can be extended to all aliens. This admittedly strange way of thinking can be traced back to comments made by the English scientist Brian Cox (famous for his TV documentaries). Prof. Cox has said Earth is probably the only planet in the universe that gave rise to intelligent life. His reason for saying this is evolution. Personally, I believe biological evolution is in desperate need of major modification. But that's not the point here - the point is that intelligent life is here (I think) and that we've started exploring space. I further believe that, someday, we'll be able to use the Riemann hypothesis and Wick rotation to travel billions of light years in the blink of an eye. The Riemann/Wick things will also allow time travel (into both the past and future), using General Relativity's concept of curved time (which is made circular via Wick rotation and future warping of space-time).
Time travel plus instant space travel permits us to explore and colonize any place in space, anywhere in the past or present or future. Those colonists will surely be very different from us in some respects because they'll have to adapt to very different environments. Some of the changes will be due to natural adaptation, and some to selected bioengineering that we haven't even dreamt of yet. But the aliens' origin will be human and they'll always be more similar to us than different. The aliens could be anywhere and everywhere - even, thanks to both quantum and macroscopic entanglement with conditions on the home planet, between planets and moons. If they set up a colony thousands or millions of years in our past, they'd make today's civilization on Earth look like the activity of insects - or, as Prof. Michio Kaku has said, squirrels - and we couldn't blame them for not being terribly interested in contacting us at the moment. It'd be in our best interest for them to leave us alone for now since we'd be absolutely terrified of their power. We might not be able to even comprehend their being millions of years ahead of us - we might arrogantly dismiss them as ignorant because they couldn't accept what we think are facts.
To sum up - the movie "Interstellar" seems to be correct when it says people will someday be able to do things they can't do now.
Anticipating when tomorrow (in a different millennium) comes!
Could you recommend some articles on Intelligent Manufacturing?
Could you recommend some Articles on the Intelligent Construction of Coal Mines?
We have collected 5 articles on the intelligent construction of coal mines from Coal Geology & Exploration. Hope these articles are useful to you.
Intelligent optimization and control technology for drilling process of coal mine tunnels
Image sharpening method of automatic loading and unloading drill pipe target in underground coal mine
Digital twin technology of geological information in mining and tunneling working face
Development and application of ZDY4500LFK fully automatic drilling rig
Key technology of automatic loading and unloading system for dual-pipe directional drilling rig and its application in soft-fragmentized coal seam
More bilingual resources could be found via this link https://jtp.oversea.cnki.net/bilingual/.
We are on the brink of a technological revolution that could jumpstart productivity, boost global growth and raise incomes around the world. Yet it could also replace jobs and deepen inequality. The rapid advance of artificial intelligence has captivated the world, causing both excitement and alarm, and raising important questions about its potential impact on the global economy. The net effect is difficult to foresee, as AI will ripple through economies in complex ways. What we can say with some confidence is that we will need to come up with a set of policies to safely leverage the vast potential of AI for the benefit of humanity.
source: AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity https://www.imf.org/en/Blogs/Articles/2024/01/14/ai-will-transform-the-global-economy-lets-make-sure-it-benefits-humanity
Can artificial intelligence create innovations with the help of artificial intelligence, since the knowledge bases of AI applications contain what humans have already created before?
Can innovations be created with the help of artificial intelligence, since AI-based applications have been trained on existing achievements already created by humans before?
Can new innovations, including technological innovations, be created with the help of generative artificial intelligence technology, since AI-based applications have been trained through a process of deep learning on existing achievements previously created by humans?
The key issue in this kind of consideration is to answer the question of what is a fully new solution, what is an innovation. Generative artificial intelligence technology, combined with other Industry 4.0/5.0 technologies, including Big Data Analytics and computers equipped with high-performance microprocessors, enable multi-criteria, advanced processing of large information datasets in many times less time than if a human were to do it without the use of the aforementioned technologies. Advanced information systems equipped with generative artificial intelligence technology backed by high computing power computers make it possible, through a process of deep learning, to train intelligent chatbots to carry out specific tasks and commands much faster and more efficiently than a human can do the same. In a situation where intelligent advanced language models that enable a machine to carry on a conversation with a human were learned on large collections of data and information, including online databases of scientific knowledge that contain millions of scientific texts and/or databases of other publications, the texts generated by intelligent chatbots will be created much faster than a human would and, in addition, will be generated on the basis of processing, analysis, inference, etc. of thousands or millions of different source texts. This is virtually impossible for a human to do. However, whether the texts generated by intelligent chatbots will contain innovative solutions, whether they will be created in an innovative way, whether they will contain proposals for innovative implementation of a specific task, command, etc., this will already depend mainly on how this issue will be programmed in these machines by a human. Unless, in the future, autonomously functioning highly intelligent robots will be created, which will be equipped with a strong general artificial intelligence and will thus be able to act independently within a certain range of independence, will be able to self-improve, repair their own faults, will be able to learn just like a human being, over time will become better and better at performing various types of activities previously performed exclusively by humans then perhaps they will also learn to solve certain tasks in a highly innovative manner themselves. But this is a matter for consideration for the perspective of the next dozen or so years of dynamic development of AI technology and its applications.
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
And the applications of Big Data technologies in sentiment analysis, business analytics and risk management were described in my co-authored article:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
I invite you to familiarize yourself with the issues described in the publications given above, and to scientific cooperation in these issues.
In view of the above, I address the following question to the esteemed community of scientists and researchers:
Is it possible to create new innovations, including technological innovations, with the help of generative artificial intelligence technology, since AI-based applications have been trained through a process of deep learning on existing achievements previously created by humans?
Can innovations be created with the help of artificial intelligence, since the knowledge bases of AI applications contain what humans have already created before?
Can artificial intelligence create real innovations when it learns from what humans have already created before?
And what is your opinion on 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
& WHAT ALSO IF THESES (MASTERS, DOCTORATES) ARE DONE BY AI ( ARTIFICIAL INTELLIGENCE ) ! ?
As it is well known that already so many masters & doctorate theses mostly other than medicine & medical sciences & natural sciences are written & prepared as theses professionally by others for the sake of money as ordered and paid by the canditates of master & doctorate !?
Maybe Catholicism should separate from conservatism, https://www.researchgate.net/publication/380427514_Kalergi_and_Hart-Cellerand_Memetics_White_Antifragility .
I am struggling to attain multiple research articles, so far, I have looked at the Swedish longitudinal study, they have good depth and reliability. I was thinking of looking into twin studies to use as comparative evidence, but they focus more on nature vs nurture topics which I discuss in my evaluation since they aren't my focus of research. Any recs?
"The ONLY test of intelligence that counts is to see if the person detects Wittgenstein's ruler situations:
1) When you use a ruler to measure the table, you are also using the table to measure the ruler.
2) The more unexpected the measurement, the more you apply W's ruler" ( https://x.com/nntaleb/status/1082560527908384768 ).
I is no secret that hunmans are procreating very fast: the number of people on Earth has more than tripled in my lifetime and I still plan to be around for one more turnover. The real problem is in that people live longer and have ever increasing needs, while their work-span is the same or less than before (until 62-67 years, depending on the country) so someone has to provide for thee rest of their lives. This creates an enormous need for people who will work. And who are they? (Who you gonna call?) Youngsters!
And since youngsters must support not only the old people but also themselves, there is a need for many more of them than just the number of old people. And when they get old, there will be a need for even more new youngsters, and that goes on and on, into a spiral that has readily damaged the environment.
But what if someone/something else is going to do the hard work? To remind ourselves, the definition of (would-be) AI is: "AI is as intelligent as humans (if not more) and it is meant to replace them in jobs that noone else wants to do." So if AI is implemented, finally, we will be able to get rid of the need for youngsters! What a relief!
If someone would nevertheless like to have one, a Chinese manufacturer readily offers a fully humanoid robot daughter. And the good thing about it that it never gets sick, and if it does, you just buy a new part. No need for hospitals and uncertain, expensive and lengthy medical procedures.
In offering this question I place myself within a position of prejudice. Although he has strategic sense I tend to believe that violent people, contrary to modern myths such as Hannibal Lector, cannot be sensibly called intelligent. Those who kill or get others to kill for them must be lacking in smarts not examples of it. Negative behaviour does not engender wealth or creativity and thereby limits the fulfillment and happiness of others.
Putin did not prosper in the KGB and his potential was rarely if ever mentioned. He rose above the parapet in 1991 when he was hired by a charity/socially concerned group and quickly embezzled some 120 million dollars. It was around this time that he created his system of political loyalty (group loyalty) based on money, the potential for him and others to become immensely wealthy.
A talented and highly intelligent politician I suggest is rare, reliant on cultural traits. Still, I concede my position is based largely on prejudice against killers (some killers have been intellectually remarkable such as Caravaggio but the list is short). Besides which, he is a very, very poor historian even given that he uses history to create rationales for war.
Think, how many strategic mistakes has he made? Surely, every action he has made?
🔒Call for Papers-Collaborative Edge Intelligence and Its Emerging Applications
Chart new territories! Propose avant-garde research on edge AI, fusing blockchain, 6G, and web3 to sculpt an unprecedented landscape of intelligence.🌐
Journal: CMC-Computers, Materials & Continua (SCIE IF=3.1)
📅 Submission Deadline: 31 May 2025
🌟 Guest Editors:
Prof. Shan Jiang, The Hong Kong Polytechnic University, Hong Kong SAR, China
Prof. Milos Stojmenovic, Singidunum University, Serbia
📌 Keywords:
Collaborative edge computing, Artificial intelligence, Large AI models, Blockchain and web3, 5G and beyond
The special session on “Next-Gen Precise Positioning and Seamless Navigation: From Classical Signal Processing to AI” to be held with 3rd International IEEE Applied Sensing Conference (APSCON 2025) during January 20-22, 2025, at IIT Hyderabad, India, invites original submission, not exceeding 4 pages in standard IEEE format, on one of the following topics from the prospective authors.
1) AI, machine/deep learning for intelligent and seamless positioning
2) Hybridization of AI and classical signal processing approaches
3) Intelligent sensor fusion or multiple signal sources for enhanced positioning accuracy
4) Accurate and Efficient positioning: compression, clustering, approximate computing
5) Mobility models for seamless positioning and navigation
6) Case studies and real-world implementations:
Integrated sensing and positioning for autonomous and intelligent vehicles.
Integrated localization and communications for 6G systems
Intelligent in-home monitoring and e-Health
Mobility aid for disabled persons
Navigation solutions for emergency rescue workers
This special session will explore the applicability of artificial intelligence (AI) techniques and their integration in various sensor data fusion including the newly emerged 5G, 6G network data for precise positioning and seamless navigation systems in satellite-signal denied areas. Traditional signal processing methods are increasingly being supplemented or replaced by AI-driven approaches, offering enhanced accuracy, robustness, and efficiency. Topics will cover state-of-the-art AI algorithms, various machine learning models, and deep learning techniques applied to various sensors and data sources to enable the precise positioning and seamless navigation in complex urban environments.
The best 2 papers of this session will be encouraged to submit the extended versions of the papers to the open access journal "IEEE Journal of Indoor and Seamless Positioning and Navigation (J-ISPIN)", and if accepted, the APC will be waived for publication (this is US$ 1995).
The submission deadline is September 20, 2024. To know more about the submission instructions and to submit your paper, kindly check the link mentioned below.
Special Session - IEEE APSCON (ieee-apscon.org).
Integrating Financial Management with Intelligent Technologies: Financial Services Industry (banks) Case Study
· How do intelligent technologies influence financial management practices in the banking sector?
· What are the benefits and challenges associated with integrating intelligent technologies in financial management within banks (answering machines, chatbots,…..)?
· How do different types of banks (online, traditional, hybrid) adapt to and benefit from intelligent technologies?
What are the preferences of customers regarding traditional vs. smart technology banking services?
2024 5th International Conference on Advanced Materials and Intelligent Manufacturing(ICAMIM 2024), which is to be held in Guangzhou, China, from November 01-03, 2024.
Conference Website: https://ais.cn/u/v6ve6r
---Call for papers---
The topics of interest for submission include, but are not limited to:
◕ Advanced materials
01) Non-ferrous metal materials
02) Steel polymer material
03) Composites
04) Micro/nano materials
05) Optical/electronic/magnetic materials
06) New feature materials
◕ Intelligent manufacturing
01) Biomimicry mechanisms
02) Integrated manufacturing systems
03) Industrial and manufacturing systems analysis and decision-making
04) Digital manufacturing
05) Modeling and design
06) Intelligent systems
07) Intelligent mechatronics
08) Micromachining technology
09) Advanced manufacturing technology
---Publication---
All papers, both invited and contributed, will be reviewed by two or three experts from the committees. After a careful reviewing process, all accepted papers of ICAMIM 2024 will be published in the Journal Of physics: Conference Series (ISSN:1742-6596), and it will be submitted to EI Compendex and Scopus for indexing.
---Important Dates---
Full Paper Submission Date: October 30, 2024
Registration Deadline: November 1, 2024
Final Paper Submission Date: November 10, 2024
Conference Dates: November 01-03, 2024
--- Paper Submission---
Please send the full paper(word+pdf) to Submission System:
Hello Researchers, hope you are doing well.
I have to see Revealed Comparative Advantage between India and China for specific product. I went thru several related literature and found different formula to calculate BRCA.
May you tell me which formula will be more appropriate?
Details:
Formula 1:
BRCA kab =
(Xkab /Xab)/(Xkwb /Xwb)
Where BRCA kab is the bilateral revealed comparative advantage of India with Australia for the commodity k,
Xkab is the export of commodity k from India) to Australia,
Xab is the total exports from India to Australia,
Xkwb is the total exports of the world of commodity k to Australia and
Xwb is the total exports of the world to Australia.
[Source 1: Mustafa, G. and Sharma A. (2023): “An Analysis of India’s Revealed Comparative Advantage in Merchandise Trade with Australia”, Global Economics Science, Universal WISER Publisher, Volume 4, Issue 1, January, 2023, pp. 32-48. (DOI: https://doi.org/10.37256/ges.4120231623)]
[Source 2: Maryam, J. and Mittal A (2019): “An empirical analysis of India’s trade in goods with BRICS”, International Review of Economics, May 2019, pp 339-421. (https://doi.org/10.1007/s12232-019-00328-7)]
Formula 2:
BRCAij=
(XijA/XiA)/(XijB/XiB)
Where:
BRCAij is the Bilateral Revealed Comparative advantage of country A in industry j relative to country B.
XijA is the exports of country A in industry j.
XiA is the total exports of country A across all industries.
XijB is the exports of country B in industry j.
XiB is the total exports of country B across all industries.
(Source: Online Searching)
Formula 3:
BRCA =
(Xkij /Xij)/(Xkiw /Xiw)
Where
X= export
I= exporter country
J= destination country
W= world
K= product
(Source 1: NCAER’s working paper no. 104, March 2012)
(Source 2: TINA- the Trade Intelligence and Negotiation Adviser, Final Draft, 20 Jan 2021, version 1)
Formula 4:
BRCA1 kijw =
(Xkiw/Xiw)/(Xkjw/Xjw)
Where:
i= exporter country
j= destination country
w= world
k= product
(Source 1: Sharma, S. K. and Bugalya, K. (2014): “Competitiveness of Indian agriculture sector: A case study of cotton crop”, Procedia - Social and Behavioral Sciences 133, 2014, pp. 320–335. [DOI: 10.1016/j.sbspro.2014.04.198]
Please tell me which formula will be more appropriate? And what are the differences among these formulas? why there are several formula to calculate BRCA?
Regards:
Raghavendra
Mira Murati (CTO of OpenAI) has said that ChatGPT will soon exhibit PhD level intelligence within 2 years. Is it true?
Can ChatGPT exhibit more intelligence than a PhD degree holder?
I would like to know when will AI overtake the intelligence and IQ level of humans?
I want to know if people with more IQ or intelligence have the potential to make more money and become extremely wealthy in life or is it possible to become rich without having much intelligence. Does more intelligence correlate to more money?
Leaving a legacy so big, living deduce the person must have existed. Also, amassing VIRTUAL self sufficiency through automation.
What are the new and required subjects for a doctoral thesis on cyber threat intelligence?
We tried to start the development of this topic, but given the large number of mysteries related to the mind, its appearance and evolution - noogenesis, etc., we feel that it is necessary to combine efforts, exchange experiences and advice on further development in various directions, coordinates, aspects.
intelligence- performances cognitives- psychologie cognitive- performance sportive
I have a unit cell design and I have to test if the surface will reflect the incoming wave in particular angles. How can I use waveguide ports to simulate this?
When communicating with multiple intelligences, why choosing with whom to communicate ends up with similar task performance. I am experimenting in mpe's simpletag environment, where each intelligence has a different range of observations
Will artificial intelligence help analyze images taken by space supertelescopes and help identify other life forms on distant exoplanets?
Will generative artificial intelligence technology help analyze images taken by space supertelescopes and identify other life forms on distant exoplanets millions of light years away located in other planetary systems, constellations, galaxies?
Space supertelescopes, including one of the most modern and powerful space telescopes, which is the James Webb supertelescope, take many images of galaxies, suns, nebulae, etc., millions of light years distant. In distant galaxies, of which there are millions if not more in the Universe, there are many constellations numbering in the billions, planetary systems that contain many exoplanets. Many of these billions of exoplanets orbiting other suns in other planetary systems are similar in many ways to our plaenta Earth. For many thousands or millions of these exoplanets, the similarity of chemical element composition, physico-chemical conditions, temperature levels, chemical composition of inorganic compounds, atmospheric processes, surface formation, possible presence of water or highly alternative chemical-physical structures, etc. with what is found on Earth may be so great that it is highly likely that life is or has been found on many of these exoplanets. Most likely, these are different life forms to those we know. The dissimilarity of these life forms is determined by different conditions of physical and chemical processes, different composition of chemical elements, different chemical compounds, different atmospheric processes, different temperature ranges, different calendar of rotation around other suns, etc. Perhaps on some of these exoplanets where other life forms arose other intelligent beings also arose. Perhaps on some of these exoplanets where evolved life created other intelligent beings are also present advanced civilizations created by said other intelligent beings. Humanity has been searching for many years for answers to questions about the possible existence of other forms of life, other intelligent beings, other civilizations on distant exoplanets.For years, space supertelescopes have been involved for this purpose, which successively over time as space exploration technology advances, take more and more perfect photographs of more and more distant celestial bodies, galaxies, constellations, planetary systems, exoplanets. This produces a huge amount of data contained in the thousands or millions of photographs taken in this way. It would take many years for a human to analyze such a large amount of data contained in these photographs. Industry 4.0/5.0 technologies, including Big Data Analytics and generative artificial intelligence, can help analyze these large data sets contained in the aforementioned many photographs.
I described the applications of Big Data technologies in sentiment analysis, business analytics and risk management in an article of my co-authorship:
APPLICATION OF DATA BASE SYSTEMS BIG DATA AND BUSINESS INTELLIGENCE SOFTWARE IN INTEGRATED RISK MANAGEMENT IN ORGANIZATION
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:
Will the technology of generative artificial intelligence help to analyze images taken by space supertelescopes and to identify other forms of life on exoplanets millions of light years away located in other planetary systems, constellations, galaxies?
Will artificial intelligence help analyze images taken by space supertelescopes and identify other life forms on distant exoplanets?
Will artificial intelligence help identify other life forms on distant exoplanets?
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
By Extraterrestrial Intelligence I am referring to intelligences superior to humans.
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.
In the late 1990s, neuroscientists announced the discovery of the "God spot" in the brain, located in the temporal lobe, just behind the temples. This neural cluster encourages us to ask fundamental questions, seek fundamental answers about the meaning of existence, strive for higher purposes, and dream of better tomorrows etc. It becomes active when we feel love, peace, beauty, true faith...Has the scientific existence of spiritual intelligence been proven, and if so, what role does the dozy chaos play in it?
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?