How to train smarter robots psychological collaborative systemsNUS-ISS
by Dr. Fun Wey, Principal Lecturer & Consultant, Artificial Intelligence Practice, NUS ISS for the NUS-ISS SkillsFuture Series Seminar: Harnessing the power of Intelligent Software Agents (9 April 2019)
Is Deep-Layered Machine Learning the Catalyst for an Artificial General Intel...Humanity Plus
Is Deep-Layered Machine Learning the Catalyst for an Artificial General Intelligence Revolution?
Deep-layered machine learning technologies have recently emerged as promising, biologically-inspired cognitive architectures for driving next-generation artificial intelligence applications. Deep learning architecture comprise of hierarchical structures capable of representing diverse, high-dimensional sensory data in a manner that facilitates capturing salient spatiotemporal dependencies in the observations. Advances in the field of machine learning, particularly those made over the past two decades, offer profound insight into the paradigms governing decision making under uncertainty in the mammal brain. From an implementation perspective, integrated circuits fabrication technology continues to improve to a point where billions of neuron-like computing elements can now be realized on a single chip. I argue that these conceptual and implementation building blocks serve as catalysts for the realization of artificial general intelligent systems in the near future.
Itamar Arel is an Associate Professor of Electrical Engineering and Computer Science and Director of the Machine Intelligence Laboratory at the University of Tennessee. He is a co-founder of the Artificial General Intelligence Roadmap initiative, which aims to play a vital role in defining AGI benchmarking and coherence in research focus. During 2000-2003 he was with TeraCross, Inc., a fabless semiconductor company developing Terabit/sec switch fabric integrated circuits, where he held several key positions including chief scientist. His research focus is on high-performance machine learning architectures and algorithms, with emphasis on deep learning architectures, reinforcement learning and decision making under uncertainty. Dr. Arel is a recipient of the US Department of Energy Early Career Principal Investigator (CAREER) award in 2004, and is a senior member of IEEE. He holds a B.S., M.S and Ph.D. degrees in Electrical and Computer Engineering and an M.B.A. degree, all from Ben-Gurion University in Israel.
A presentation I created for class that tries to explain the different approaches in developing Artificial Intelligence through explanation and examples.
Deep Learning: Towards General Artificial IntelligenceRukshan Batuwita
For the past several years Deep Learning methods have revolutionized the areas in Pattern Recognition, namely, Computer Vision, Speech Recognition, Natural Language Processing etc. These techniques have been mainly developed by academics, closely working with tech giants such as Google, Microsoft and Facebook where the research outcomes have been successfully integrated into commercial products such as Google image and voice search, Google Translate, Microsoft Cortana, Facebook M and many more interesting applications that are yet to come. More recently, Google DeepMind Technologies has been working on Artificial General Intelligence using Deep Reinforcement Learning methods, where their AlphaGo system beat the world champion of the complex Chinese game 'Go' in March 2016. This talk will present a thorough introduction to major Deep Learning techniques, recent breakthroughs and some exciting applications.
How to train smarter robots psychological collaborative systemsNUS-ISS
by Dr. Fun Wey, Principal Lecturer & Consultant, Artificial Intelligence Practice, NUS ISS for the NUS-ISS SkillsFuture Series Seminar: Harnessing the power of Intelligent Software Agents (9 April 2019)
Is Deep-Layered Machine Learning the Catalyst for an Artificial General Intel...Humanity Plus
Is Deep-Layered Machine Learning the Catalyst for an Artificial General Intelligence Revolution?
Deep-layered machine learning technologies have recently emerged as promising, biologically-inspired cognitive architectures for driving next-generation artificial intelligence applications. Deep learning architecture comprise of hierarchical structures capable of representing diverse, high-dimensional sensory data in a manner that facilitates capturing salient spatiotemporal dependencies in the observations. Advances in the field of machine learning, particularly those made over the past two decades, offer profound insight into the paradigms governing decision making under uncertainty in the mammal brain. From an implementation perspective, integrated circuits fabrication technology continues to improve to a point where billions of neuron-like computing elements can now be realized on a single chip. I argue that these conceptual and implementation building blocks serve as catalysts for the realization of artificial general intelligent systems in the near future.
Itamar Arel is an Associate Professor of Electrical Engineering and Computer Science and Director of the Machine Intelligence Laboratory at the University of Tennessee. He is a co-founder of the Artificial General Intelligence Roadmap initiative, which aims to play a vital role in defining AGI benchmarking and coherence in research focus. During 2000-2003 he was with TeraCross, Inc., a fabless semiconductor company developing Terabit/sec switch fabric integrated circuits, where he held several key positions including chief scientist. His research focus is on high-performance machine learning architectures and algorithms, with emphasis on deep learning architectures, reinforcement learning and decision making under uncertainty. Dr. Arel is a recipient of the US Department of Energy Early Career Principal Investigator (CAREER) award in 2004, and is a senior member of IEEE. He holds a B.S., M.S and Ph.D. degrees in Electrical and Computer Engineering and an M.B.A. degree, all from Ben-Gurion University in Israel.
A presentation I created for class that tries to explain the different approaches in developing Artificial Intelligence through explanation and examples.
Deep Learning: Towards General Artificial IntelligenceRukshan Batuwita
For the past several years Deep Learning methods have revolutionized the areas in Pattern Recognition, namely, Computer Vision, Speech Recognition, Natural Language Processing etc. These techniques have been mainly developed by academics, closely working with tech giants such as Google, Microsoft and Facebook where the research outcomes have been successfully integrated into commercial products such as Google image and voice search, Google Translate, Microsoft Cortana, Facebook M and many more interesting applications that are yet to come. More recently, Google DeepMind Technologies has been working on Artificial General Intelligence using Deep Reinforcement Learning methods, where their AlphaGo system beat the world champion of the complex Chinese game 'Go' in March 2016. This talk will present a thorough introduction to major Deep Learning techniques, recent breakthroughs and some exciting applications.
Advantages and disadvantages of social mediaAlan Raj
an interesting show about social media that you can find all the information and it also contains an interesting video with voice so u can understand what is the advantages and disadvantages of social media very clearly....................................................................................................................................................u just need to watch this u will be interested ,iam sure about that
This Social Media Survival Guide will give you the tools you need to make smart content marketing decisions as your brand explores the diverse social media landscape. This collection of expert insights, advice, and brand examples outlines the unique characteristics of each channel, helps you identify which platforms and practices are likely to work best for your particular business goals, and offers creative inspiration to ignite more successful and sustainable conversations with your target audience. Read on for an in-depth discussion on 12 of the top social media platforms content marketers are using right now.
Applications of Artificial Intelligence-Past, Present & FutureJamie Gannon
This presentation in Ignite format gives a brief look into the applications of Artificial Intelligence. Starting from the humble beginnings and working its way through present day and finally the future possibilities of Artificial intelligence.
How to Create the Perfect Social-Media PostGuy Kawasaki
These are the slides that Guy Kawasaki and Peg Fitzpatrick used for a webinar hosted by Mari Smith. The purpose of the webinar was to help people create "the perfect posts" for social media. The presentation uses a classic top-ten format.
A computer network is defined as the interconnection of two or more computers. It is done to enable the computers to communicate and share available resources.
Components of computer network
Network benefits
Disadvantages of computer network
Classification by their geographical area
Network classification by their component role
Types of servers
Artificial Intelligence is referred to as machine intelligence, and it is rooted in binary codes and mathematical algorithms. It is a testament to human creativity and is capable of massive data processing, pattern recognition, and even self-learning. However, the realm of AI realm is confined.
The 117th Green Drinks Monthly Sustainability forum
An exploration of AI technology (Giga-byte world), through the lens of philosophy (Gita), and the abstract world of physical environment we live in (Green).
Artificial consciousness (AC) refers to the ability of an artificial system to possess subjective experiences and self-awareness similar to that of a human being. The presentation of AC is a complex and ongoing topic of research in the field of artificial intelligence and cognitive science.
One of the primary challenges in presenting AC is the lack of a clear definition of what consciousness entails. However, most researchers agree that consciousness involves a subjective awareness of one's own existence and surroundings, as well as the ability to experience emotions, make decisions, and engage in intentional actions.
There are several approaches to presenting AC, each with its own set of advantages and limitations. Some of these approaches are:
Cognitive Architectures:
Cognitive architectures are models of the human mind that attempt to capture the various cognitive processes involved in consciousness. These architectures use a set of rules and algorithms to simulate the human thought process, allowing the system to exhibit intelligent behavior and decision-making capabilities. One of the most well-known cognitive architectures is Soar, which has been used to simulate human-like reasoning in various domains, such as problem-solving and language understanding.
Neural Networks:
Neural networks are a set of algorithms that attempt to simulate the behavior of the human brain. These networks are composed of interconnected nodes that process and transmit information in a manner similar to biological neurons. Neural networks have been used to model various aspects of consciousness, such as perception, learning, and decision-making. However, they have limited explanatory power when it comes to the subjective experience of consciousness.
Robotics:
Robotics is the field of engineering that deals with the design, construction, and operation of robots. Robotic systems can be used to study and simulate human-like behavior and consciousness. For example, humanoid robots can be programmed to recognize and respond to human emotions, learn from experience, and interact with the environment in a manner similar to human beings.
Virtual Reality:
Virtual reality (VR) is a computer-generated simulation of a three-dimensional environment. VR can be used to create immersive experiences that mimic real-world scenarios and interactions. VR systems can be used to study the effects of sensory input and feedback on consciousness, as well as to develop AC systems that can interact with humans in a realistic manner.
In conclusion, presenting AC is a complex and ongoing research challenge that involves a combination of cognitive, computational, and engineering approaches. The development of AC systems will require a deep understanding of the nature of consciousness, as well as the ability to model and simulate the cognitive processes involved in subjective experience and self-awareness. While significant progress has been made in this field, there is still much work to do.
bhusal2
Prepared by
Deepak Bhusal
CWID:50259419
To Professor: Dr. R. Daniel Creider
Table of Contents
Abstract 3
Introduction 4
Literature Review 5
AI for Justice 6
AI in Medical Teaching 8
Artificial Intelligence in human resource management 9
AI in Marketing 10
Artificial Intelligence in Real Estate 13
Real Estate Agent Selection 14
Artificial Intelligence in CRM 16
Artificial Intelligence in Banking 18
AI based Chatbots in Financial Institutions 19
Customization of Products 19
References 24
Artificial Intelligence: Formalizing Human CapabilitiesAbstract
Artificial Intelligence cannot replace three human abilities, in which human beings present an insurmountable advantage today, and they are empathy, leadership, and creativity. AI can quickly take over essential verbal and visual communication services, such as digital assistant-based customer service. However, our ability to empathize with the client and to carry out non-verbal communication based on emotions gives us an advantage that Artificial Intelligence can never replace. These qualities can make the difference between a misunderstood and dissatisfied customer versus an understood and loyal customer.
Gajane & Pechenizkiy (2017) stated that it is undeniable that AI will replace workers in essential economic-financial management, logistics, materials, human resources, and projects. Still, people have more advanced management capabilities that AI cannot return. The following two skills play a crucial role:
First is the ability to manage the growth of human groups. This is the ability to help members of the organization develop their skills and grow professionally through our innate leadership ability to set goals, motivate, lead by example, evaluate, delegate, and transmit experience.
Secondly, there is the ability to carry out the organization members' recovery management when they suffer problems derived from interpersonal relationships or other emotional reasons. It is based on the skills of understanding, counseling, care, and protection.
Yampolskiy (2019) found that AI can never replace the vision, invention, and original proposal of innovative and disruptive designs, not only applied to the individual as a genius but also the ability to carry out collective intelligence management focused on innovation, facilitating the appearance of new knowledge and wisdom. Besides, even more, difficult it will be able to replace the ability to implement new ideas in the organization, communicating attractively, persuading, and making the organization move smoothly to implement innovative ideas.
Keywords
Artificial Intelligence, Marketing, Human Resource Management, Medical Sciences, Nursing, Introduction
The possibility of thought in machines is a concern that has been raised for a long time; science fiction, as well as engineering and philosophy, have sought to provide an answer to the question "Can machines think?" Famous exponents of both affirmative answers, given by Turing or K ...
Artificial Intelligence and Consciousness (Empiricist League Presentation)John C. Havens
Consciousness and AI
John C. Havens is a contributing writer for Mashable, The Guardian, and Slate. He is the author of Hacking H(app)iness – Why Your Personal Data Counts and How Tracking it Can Change the World and has recently published his second title for Tarcher/Penguin, Heartificial Intelligence: Embracing Our Humanity to Maximize Machines. He will be speaking to the Empiricist League about what AI can teach us about consciousness, as well as the ramifications for conscious machines on our world.
Talk given at the Neurons London Meetup in April 2018. I discuss where AI is now, what we know from biology and whether it is possible that abstract algorithms could lead to intelligence.
Advantages and disadvantages of social mediaAlan Raj
an interesting show about social media that you can find all the information and it also contains an interesting video with voice so u can understand what is the advantages and disadvantages of social media very clearly....................................................................................................................................................u just need to watch this u will be interested ,iam sure about that
This Social Media Survival Guide will give you the tools you need to make smart content marketing decisions as your brand explores the diverse social media landscape. This collection of expert insights, advice, and brand examples outlines the unique characteristics of each channel, helps you identify which platforms and practices are likely to work best for your particular business goals, and offers creative inspiration to ignite more successful and sustainable conversations with your target audience. Read on for an in-depth discussion on 12 of the top social media platforms content marketers are using right now.
Applications of Artificial Intelligence-Past, Present & FutureJamie Gannon
This presentation in Ignite format gives a brief look into the applications of Artificial Intelligence. Starting from the humble beginnings and working its way through present day and finally the future possibilities of Artificial intelligence.
How to Create the Perfect Social-Media PostGuy Kawasaki
These are the slides that Guy Kawasaki and Peg Fitzpatrick used for a webinar hosted by Mari Smith. The purpose of the webinar was to help people create "the perfect posts" for social media. The presentation uses a classic top-ten format.
A computer network is defined as the interconnection of two or more computers. It is done to enable the computers to communicate and share available resources.
Components of computer network
Network benefits
Disadvantages of computer network
Classification by their geographical area
Network classification by their component role
Types of servers
Artificial Intelligence is referred to as machine intelligence, and it is rooted in binary codes and mathematical algorithms. It is a testament to human creativity and is capable of massive data processing, pattern recognition, and even self-learning. However, the realm of AI realm is confined.
The 117th Green Drinks Monthly Sustainability forum
An exploration of AI technology (Giga-byte world), through the lens of philosophy (Gita), and the abstract world of physical environment we live in (Green).
Artificial consciousness (AC) refers to the ability of an artificial system to possess subjective experiences and self-awareness similar to that of a human being. The presentation of AC is a complex and ongoing topic of research in the field of artificial intelligence and cognitive science.
One of the primary challenges in presenting AC is the lack of a clear definition of what consciousness entails. However, most researchers agree that consciousness involves a subjective awareness of one's own existence and surroundings, as well as the ability to experience emotions, make decisions, and engage in intentional actions.
There are several approaches to presenting AC, each with its own set of advantages and limitations. Some of these approaches are:
Cognitive Architectures:
Cognitive architectures are models of the human mind that attempt to capture the various cognitive processes involved in consciousness. These architectures use a set of rules and algorithms to simulate the human thought process, allowing the system to exhibit intelligent behavior and decision-making capabilities. One of the most well-known cognitive architectures is Soar, which has been used to simulate human-like reasoning in various domains, such as problem-solving and language understanding.
Neural Networks:
Neural networks are a set of algorithms that attempt to simulate the behavior of the human brain. These networks are composed of interconnected nodes that process and transmit information in a manner similar to biological neurons. Neural networks have been used to model various aspects of consciousness, such as perception, learning, and decision-making. However, they have limited explanatory power when it comes to the subjective experience of consciousness.
Robotics:
Robotics is the field of engineering that deals with the design, construction, and operation of robots. Robotic systems can be used to study and simulate human-like behavior and consciousness. For example, humanoid robots can be programmed to recognize and respond to human emotions, learn from experience, and interact with the environment in a manner similar to human beings.
Virtual Reality:
Virtual reality (VR) is a computer-generated simulation of a three-dimensional environment. VR can be used to create immersive experiences that mimic real-world scenarios and interactions. VR systems can be used to study the effects of sensory input and feedback on consciousness, as well as to develop AC systems that can interact with humans in a realistic manner.
In conclusion, presenting AC is a complex and ongoing research challenge that involves a combination of cognitive, computational, and engineering approaches. The development of AC systems will require a deep understanding of the nature of consciousness, as well as the ability to model and simulate the cognitive processes involved in subjective experience and self-awareness. While significant progress has been made in this field, there is still much work to do.
bhusal2
Prepared by
Deepak Bhusal
CWID:50259419
To Professor: Dr. R. Daniel Creider
Table of Contents
Abstract 3
Introduction 4
Literature Review 5
AI for Justice 6
AI in Medical Teaching 8
Artificial Intelligence in human resource management 9
AI in Marketing 10
Artificial Intelligence in Real Estate 13
Real Estate Agent Selection 14
Artificial Intelligence in CRM 16
Artificial Intelligence in Banking 18
AI based Chatbots in Financial Institutions 19
Customization of Products 19
References 24
Artificial Intelligence: Formalizing Human CapabilitiesAbstract
Artificial Intelligence cannot replace three human abilities, in which human beings present an insurmountable advantage today, and they are empathy, leadership, and creativity. AI can quickly take over essential verbal and visual communication services, such as digital assistant-based customer service. However, our ability to empathize with the client and to carry out non-verbal communication based on emotions gives us an advantage that Artificial Intelligence can never replace. These qualities can make the difference between a misunderstood and dissatisfied customer versus an understood and loyal customer.
Gajane & Pechenizkiy (2017) stated that it is undeniable that AI will replace workers in essential economic-financial management, logistics, materials, human resources, and projects. Still, people have more advanced management capabilities that AI cannot return. The following two skills play a crucial role:
First is the ability to manage the growth of human groups. This is the ability to help members of the organization develop their skills and grow professionally through our innate leadership ability to set goals, motivate, lead by example, evaluate, delegate, and transmit experience.
Secondly, there is the ability to carry out the organization members' recovery management when they suffer problems derived from interpersonal relationships or other emotional reasons. It is based on the skills of understanding, counseling, care, and protection.
Yampolskiy (2019) found that AI can never replace the vision, invention, and original proposal of innovative and disruptive designs, not only applied to the individual as a genius but also the ability to carry out collective intelligence management focused on innovation, facilitating the appearance of new knowledge and wisdom. Besides, even more, difficult it will be able to replace the ability to implement new ideas in the organization, communicating attractively, persuading, and making the organization move smoothly to implement innovative ideas.
Keywords
Artificial Intelligence, Marketing, Human Resource Management, Medical Sciences, Nursing, Introduction
The possibility of thought in machines is a concern that has been raised for a long time; science fiction, as well as engineering and philosophy, have sought to provide an answer to the question "Can machines think?" Famous exponents of both affirmative answers, given by Turing or K ...
Artificial Intelligence and Consciousness (Empiricist League Presentation)John C. Havens
Consciousness and AI
John C. Havens is a contributing writer for Mashable, The Guardian, and Slate. He is the author of Hacking H(app)iness – Why Your Personal Data Counts and How Tracking it Can Change the World and has recently published his second title for Tarcher/Penguin, Heartificial Intelligence: Embracing Our Humanity to Maximize Machines. He will be speaking to the Empiricist League about what AI can teach us about consciousness, as well as the ramifications for conscious machines on our world.
Talk given at the Neurons London Meetup in April 2018. I discuss where AI is now, what we know from biology and whether it is possible that abstract algorithms could lead to intelligence.
These are my slides at ISIA Firenze where we discussed how current technology (and emerging ones) could help designers. Starting from AI and moving to Generative Design and Zero UI interfaces
Artificial Consciousness is the final destination of computer science. We have heard a lot about Artificial Intelligence but Artificial Consciousness is the next level of AI. The idea is centuries old and is a philosophical phenomena. There has been no consensus on what consciousness is since all the definitions of consciousness are subjective and based on the human perception of consciousness.
NUMERICAL SIMULATIONS OF HEAT AND MASS TRANSFER IN CONDENSING HEAT EXCHANGERS...ssuser7dcef0
Power plants release a large amount of water vapor into the
atmosphere through the stack. The flue gas can be a potential
source for obtaining much needed cooling water for a power
plant. If a power plant could recover and reuse a portion of this
moisture, it could reduce its total cooling water intake
requirement. One of the most practical way to recover water
from flue gas is to use a condensing heat exchanger. The power
plant could also recover latent heat due to condensation as well
as sensible heat due to lowering the flue gas exit temperature.
Additionally, harmful acids released from the stack can be
reduced in a condensing heat exchanger by acid condensation. reduced in a condensing heat exchanger by acid condensation.
Condensation of vapors in flue gas is a complicated
phenomenon since heat and mass transfer of water vapor and
various acids simultaneously occur in the presence of noncondensable
gases such as nitrogen and oxygen. Design of a
condenser depends on the knowledge and understanding of the
heat and mass transfer processes. A computer program for
numerical simulations of water (H2O) and sulfuric acid (H2SO4)
condensation in a flue gas condensing heat exchanger was
developed using MATLAB. Governing equations based on
mass and energy balances for the system were derived to
predict variables such as flue gas exit temperature, cooling
water outlet temperature, mole fraction and condensation rates
of water and sulfuric acid vapors. The equations were solved
using an iterative solution technique with calculations of heat
and mass transfer coefficients and physical properties.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Welcome to WIPAC Monthly the magazine brought to you by the LinkedIn Group Water Industry Process Automation & Control.
In this month's edition, along with this month's industry news to celebrate the 13 years since the group was created we have articles including
A case study of the used of Advanced Process Control at the Wastewater Treatment works at Lleida in Spain
A look back on an article on smart wastewater networks in order to see how the industry has measured up in the interim around the adoption of Digital Transformation in the Water Industry.
Forklift Classes Overview by Intella PartsIntella Parts
Discover the different forklift classes and their specific applications. Learn how to choose the right forklift for your needs to ensure safety, efficiency, and compliance in your operations.
For more technical information, visit our website https://intellaparts.com
2. Contents
AI and Consciousness
Comparison of computer and human skills
Practical systems based on AI
Components of AI
7 August 2015
3. Consciousness
Mystic science of human evolution
Byproduct of human neuron
It comes from within
It is in the universe
Consciousness defined as individual awareness of his thoughts
, memories, feelings, sensations and environment. It varies
from person to person
Definition
It is direct ,immediate experience
It is private to me
It occupies present moment
7 August 2015
4. What makes human conscious?
Sentience
Personality
Learning
Anticipation
Evolution
What else?
7 August 2015
5. Artificial Consciousness
It is something which is more than logic
Its not about creating it but mimicking it
it is further divided to strong AI and weak AI
7 August 2015
6. AI and Consciousness
AC is a philosophical concept
“Artificial” or machine “consciousness” is the attempt to
model and implement aspects of human cognition that are
identified with the elusive and controversial phenomenon of
consciousness
Artificial Consciousness also known as machine
consciousness or synthetic consciousness is a field related to
artificial intelligence and cognitive robotics whose aim is to
define that which would have to be synthesized were
consciousness to be found in an engineered
artifact(Alexsander 1995) 7 August 2015
7. Comparison of computer and human
skills
Perception
Reasoning
Learning
Understanding /communicating
in natural language
Solving Problem
7 August 2015
8. Human Brain Computer
speed Neurotransmitters
travel at about 1000
ft/second
Electrons at
speed of light
memory Roughly 100 billion
neurons - about 50
trillion bits
Top super
computers might
approach this
much memory
other Each neuron
connected to 1000
others (roughly)
Perhaps 100
parallel
processors7 August 2015
9. Major Components of AI:
Knowledge
Reasoning
Language Understanding
Learning,
Perception
Robotics
7 August 2015