History, current development
Mind–body problem
Other impacts on philosophy
Themes of practical ethics
Relationship between robot ethics and machine ethics
Cognitive computing refers to the development of computer system modeled after the human brain.
This technology was introduced by IBM as 5 in 5.
In next five years IBM is planning to develop kind of Applications which will have capabilities of the right side of the human brain.
New technologies makes it possible for machines to mimic and augment the senses.
History, current development
Mind–body problem
Other impacts on philosophy
Themes of practical ethics
Relationship between robot ethics and machine ethics
Cognitive computing refers to the development of computer system modeled after the human brain.
This technology was introduced by IBM as 5 in 5.
In next five years IBM is planning to develop kind of Applications which will have capabilities of the right side of the human brain.
New technologies makes it possible for machines to mimic and augment the senses.
Introduction Artificial Intelligence a modern approach by Russel and Norvig 1Garry D. Lasaga
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. - Wikipedia
by Samantha Adams, Met Office.
Originally purely academic research fields, Machine Learning and AI are now definitely mainstream and frequently mentioned in the Tech media (and regular media too).
We’ve also got the explosion of Data Science which encompasses these fields and more. There’s a lot of interesting things going on and a lot of positive as well as negative hype. The terms ML and AI are often used interchangeably and techniques are also often described as being inspired by the brain.
In this talk I will explore the history and evolution of these fields, current progress and the challenges in making artificial brains
From the FreshTech 2017 conference by TechExeter
www.techexeter.uk
Introduction Artificial Intelligence a modern approach by Russel and Norvig 1Garry D. Lasaga
In computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and animals. - Wikipedia
by Samantha Adams, Met Office.
Originally purely academic research fields, Machine Learning and AI are now definitely mainstream and frequently mentioned in the Tech media (and regular media too).
We’ve also got the explosion of Data Science which encompasses these fields and more. There’s a lot of interesting things going on and a lot of positive as well as negative hype. The terms ML and AI are often used interchangeably and techniques are also often described as being inspired by the brain.
In this talk I will explore the history and evolution of these fields, current progress and the challenges in making artificial brains
From the FreshTech 2017 conference by TechExeter
www.techexeter.uk
Describe what is Artificial Intelligence. What are its goals and Approaches. Different Types of Artificial Intelligence Explain Machine learning and took one Algorithm "K-means Algorithm" and explained
Immunizing Image Classifiers Against Localized Adversary Attacksgerogepatton
This paper addresses the vulnerability of deep learning models, particularly convolutional neural networks
(CNN)s, to adversarial attacks and presents a proactive training technique designed to counter them. We
introduce a novel volumization algorithm, which transforms 2D images into 3D volumetric representations.
When combined with 3D convolution and deep curriculum learning optimization (CLO), itsignificantly improves
the immunity of models against localized universal attacks by up to 40%. We evaluate our proposed approach
using contemporary CNN architectures and the modified Canadian Institute for Advanced Research (CIFAR-10
and CIFAR-100) and ImageNet Large Scale Visual Recognition Challenge (ILSVRC12) datasets, showcasing
accuracy improvements over previous techniques. The results indicate that the combination of the volumetric
input and curriculum learning holds significant promise for mitigating adversarial attacks without necessitating
adversary training.
About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Overview of the fundamental roles in Hydropower generation and the components involved in wider Electrical Engineering.
This paper presents the design and construction of hydroelectric dams from the hydrologist’s survey of the valley before construction, all aspects and involved disciplines, fluid dynamics, structural engineering, generation and mains frequency regulation to the very transmission of power through the network in the United Kingdom.
Author: Robbie Edward Sayers
Collaborators and co editors: Charlie Sims and Connor Healey.
(C) 2024 Robbie E. Sayers
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
Ideal for homeowners, contractors, engineers, and anyone interested in modern plumbing solutions, this guide provides valuable insights into why trenchless pipe repair is becoming the preferred choice for pipe rehabilitation. Stay informed about the latest advancements and best practices in the field.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
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.
Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...Dr.Costas Sachpazis
Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.
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Water scarcity is the lack of fresh water resources to meet the standard water demand. There are two type of water scarcity. One is physical. The other is economic water scarcity.
3. Obvious question
What is AI?
Programs that behave externally like humans?
Programs that operate internally as humans
do?
Computational systems that behave
intelligently?
Rational behaviour?
4. Turing Test
Human beings are
intelligent
To be called
intelligent, a machine
must produce
responses that are
indistinguishable from
those of a human
Alan Turing
5. Does AI have applications?
Autonomous planning and scheduling of
tasks aboard a spacecraft
Beating Gary Kasparov in a chess match
Steering a driver-less car
Understanding language
Robotic assistants in surgery
Monitoring trade in the stock market to
see if insider trading is going on
6. A rich history
Philosophy
Mathematics
Economics
Neuroscience
Psychology
Control Theory
John McCarthy- coined the term- 1950’s
7. Philosophy
Dealt with questions like:
Can formal rules be used to draw valid conclusions?
Where does knowledge come from? How does it lead to
action?
David Hume proposed the principle of induction
(later)
Aristotle-
Given the end to achieve
Consider by what means to achieve it
Consider how the above will be achieved …till you reach
the first cause
Last in the order of analysis = First in the order of action
If you reach an impossibility, abandon search
8. Mathematics
Boolean Logic(mid 1800’s)
Intractability (1960’s)
Polynomial Vs Exponential growth
Intelligent behaviour = tractable
subproblems, not large intractable
problems.
Probability
Gerolamo Cardano(1500’s) -
probability in terms of outcomes
of gambling events
George Boole
Cardano
9. Economics
How do we make decisions so as to
maximize payoff?
How do we do this when the payoff may
be far in the future?
Concept of utility (early 1900’s)
Game Theory (mid 1900’s)
Leon Walras
10. Neuroscience
Study of the nervous system, esp. brain
A collection of simple cells can lead to
thought and action
Cycle time: Human brain- microseconds
Computers- nanoseconds
The brain is still 100,000 times faster
11. Psychology
Behaviourism- stimulus leads to response
Cognitive science
Computer models can be used to understand
the psychology of memory, language and
thinking
The brain is now thought of in terms of
computer science constructs like I/O units, and
processing center
12. Control Theory
Ctesibius of Alexandria- water clock
with a regulator
Purposeful behaviour as arising
from a regulatory mechanism to
minimize the difference between
goal state and current state
(“error”)
13. Does AI meet EE?
Robotics- the science
and technology of
robots, their design,
manufacture, and
application.
Liar! (1941)
Isaac Asimov
14. Mechatronics- mechanics, electronics and
computing which, combined, make
possible the generation of simpler, more
economical, reliable and versatile systems.
Cybernetics- the study of communication
and control, typically involving regulatory
feedback, in living organisms, in machines,
and in combinations of the two.
Norbert Wiener
15. An Agent
‘Anything’ that can gather information
about its environment and take action
based on that information.
16. The Environment
What all do we need
to specify?
The action space
The percept space
The environment as
a string of mappings
from the action space
to the percept space
17. The World Model
Perception function
World dynamics / State transition function
Utility function- how does the agent know
what constitutes “good” or “bad”
behaviour
18. What is Rationality?
Goal
Information / Knowledge
The purpose of action is to reach the goal,
given the information/knowledge
possessed by the agent
Is not omniscience
The notion of rationality does not
necessarily include success of the actions
chosen
21. Planning
Planning a policy = considering the future
consequences of actions to choose the
best one
22. Seems okay so far?
Computational constraints
Can we possibly specify EXACTLY the
domain the agent will work in?
A look-up table of reactions to percepts is
far to big
Most things that could happen, don’t
23. Learning
Incomplete information about the
environment
A changing environment
Use the sequence of percepts to estimate
the missing details
Hard for us to articulate the knowledge
needed to build AI systems – e.g. try
writing a program to recognize visual
input like various types of flowers
24. What is Learning?
Herb Simon-
“Learning denotes changes in the system that are
adaptive in the sense that they enable the system to do the
tasks drawn from the same population more efficiently and
more effectively the next time.”
But why do we believe we have the license
to predict the future?
25. Induction
David Hume- Scottish
philosopher, economist
All we can say, think, or
predict about nature must
come from prior experience
Bertrand Russell-
“If asked why we believe the sun will
rise tomorrow, we shall naturally
answer, ‘Because it has always risen
everyday.’ ”
David Hume
26. Classifying Learning Problems
Supervised learning- Given a set of
input/output pairs, learn to predict the
output if faced with a new input.
Unsupervised Learning- Learning patterns
in the input when no specific output values
are supplied.
Reinforcement Learning- Learn to interact
with the world from the reinforcement you
get.
27. Functions
Given a sample set of inputs and
corresponding outputs, find a function to
express this relationship
Pronunciation= Function from letters to sound
Bowling= Function from target location (or
trajectory?) to joint torques
Diagnosis= Function from lab results to
disease categories