About
What is Artificial Intelligence(AI)? , Evolution , Applications of AI? , Features of AI , What is Intelligence and its types?,
What are Agents and Environment? , Fear of AI , Machine Learning , Difference between AI, ML and Deep Learning ,
Applications of ML , Algorithms of AL and ML , Future of AI
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
Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include: Speech recognition, Learning, Planning and Problem solving - [Source: https://www.techopedia.com/definition/190/artificial-intelligence-ai]
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
Artificial intelligence (AI) is an area of computer science that emphasizes the creation of intelligent machines that work and react like humans. Some of the activities computers with artificial intelligence are designed for include: Speech recognition, Learning, Planning and Problem solving - [Source: https://www.techopedia.com/definition/190/artificial-intelligence-ai]
The English translation of the content presented at the joint meeting of
Research Meeting for Embodied Approach
http://www.geocities.jp/body_of_knowledge/
and
Meta-theoretical Studies of Mind Science
http://www.isc.meiji.ac.jp/~ishikawa/kokoro.html
on July 11th, 2015.
Ref. Phenomenology of Artefacts
http://rondelionai.blogspot.jp/2014/02/phenomenology-of-artefacts.html
The Japanese (original) version: https://www.slideshare.net/naoyaarakawa39/201507-50448060
Understanding artificial intelligence and it's future scopeChaitanya Shimpi
In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.
AILABS - Lecture Series - Is AI the New Electricity? - Advances In Machine Le...AILABS Academy
Prof. Garain discusses in brief on the backgrounds of learning algorithms & major breakthroughs that have been made in the field of machine perception in the last 50 yrs. He also discusses the role of statistical algorithms like artificial neural network, support vector machines, and other concepts related to Deep Learning algorithms.
Along with the above, Prof. Garain touched upon the basics of CNN & RNN, Long Short-Term Memory Networks (LSTM) & attention network & illustrate all of these using real-life problems. Several state-of-the-art problems like image captioning, visual question answering, medical image analysis etc. were discussed to make the potential of deep learning algorithms understandable.
Prof. Utpal Garain is one of the leading minds in Kolkata in the field of Neural Networks & Artificial Intelligence. His research interest is now focused on AI research, especially exploring deep learning methods for language, image and video analysis including NLP tools, OCRs, handwriting analysis, computational forensics and the like.
The English translation of the content presented at the joint meeting of
Research Meeting for Embodied Approach
http://www.geocities.jp/body_of_knowledge/
and
Meta-theoretical Studies of Mind Science
http://www.isc.meiji.ac.jp/~ishikawa/kokoro.html
on July 11th, 2015.
Ref. Phenomenology of Artefacts
http://rondelionai.blogspot.jp/2014/02/phenomenology-of-artefacts.html
The Japanese (original) version: https://www.slideshare.net/naoyaarakawa39/201507-50448060
Understanding artificial intelligence and it's future scopeChaitanya Shimpi
In the field of computer science, artificial intelligence, sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans and other animals.
AILABS - Lecture Series - Is AI the New Electricity? - Advances In Machine Le...AILABS Academy
Prof. Garain discusses in brief on the backgrounds of learning algorithms & major breakthroughs that have been made in the field of machine perception in the last 50 yrs. He also discusses the role of statistical algorithms like artificial neural network, support vector machines, and other concepts related to Deep Learning algorithms.
Along with the above, Prof. Garain touched upon the basics of CNN & RNN, Long Short-Term Memory Networks (LSTM) & attention network & illustrate all of these using real-life problems. Several state-of-the-art problems like image captioning, visual question answering, medical image analysis etc. were discussed to make the potential of deep learning algorithms understandable.
Prof. Utpal Garain is one of the leading minds in Kolkata in the field of Neural Networks & Artificial Intelligence. His research interest is now focused on AI research, especially exploring deep learning methods for language, image and video analysis including NLP tools, OCRs, handwriting analysis, computational forensics and the like.
Artificial Intelligence power point presentationDavid Raj Kanthi
A presentation about the basic idea about the present and future technologies which are dependent on the "ARTIFICIAL INTELLIGENCE".
AI is a branch of science which deals with the thinking, predicting, analyzing which are done by the computer itself.
The present presentation slides consists of the AI with machine learning and deep learning, goals of AI, Applications of AI and history of the Artificial intelligence etc.
Artificial intelligence is the simulation of human intelligence processes by machines, especially computer systems. Specific applications of AI include expert systems, natural language processing, speech recognition and machine vision.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
1. ARTIFICIAL INTELLIGENCE AND MACHINE LEARNING
Dr.M.Inbavalli
Vice Principal
Marudhar Kesari Jain College for Women
Vaniyambadi-635751
1
2. Overview
• What is Artificial Intelligence(AI)?
• Evolution
• Applications of AI?
• Features of AI
• What is Intelligence and its types?
• What are Agents and Environment?
• Fear of AI
• Machine Learning
• Difference between AI, ML and Deep Learning
• Applications of ML
• Algorithms of AL and ML
• Future of AI
2
3. • Artificial Intelligence
• Ability for a machine to perform tasks that would normally human do.
• artificial intelligence is making machines "intelligent“ - acting as we
would expect people to act.
• Capability of machine to imitate intelligent human behavior-Merriam
Webster.
• The inability to distinguish computer responses from human responses
is called the Turing test.
• Intelligence requires knowledge .
3
3
5. • Artificial Intelligence
• From a business perspective AI is a set of very powerful tools, and
methodologies for using those tools to solve business problems.
• From a programming perspective, AI includes the study of symbolic
programming, problem solving, and search.
• Typically AI programs focus on symbols rather than numeric processing.
or Problem solving - achieve goals.
• Search - seldom access a solution directly. Search may include a variety of
techniques.
• include:
• – LISP, developed in the 1950s
• LISP is a functional programming language with procedural extensions
5
5
9. S.
No
Programming
Languages
Features
1
LISP
developed in 1950s
A functional programming language with procedural extensions
specifically designed for processing heterogeneous lists -- typically a list of symbols.
Features of LISP
are run- time type checking,
recursion, dynamic typing, Automatic storage management, High-order functions, self-hosting
compiler, and tree data structure.
2 PROLOG developed in 1970s
Prolog is a rule-based and declarative language containing facts and rules
based on first order logic,Features- pre-designed search mechanism, recursive nature,
abstraction, non determinism, backtracking mechanism, and pattern matching.
3 Object-
oriented
languages -
Smalltalk,
Objective C,
C++
Object oriented extensions to LISP (CLOS - Common LISP Object System) and PROLOG (L&O -
Logic & Objects) are also used.
9
AI programming languages
9
13. • Applications of AI
• Game Playing- video games
• Speech Recognition
• Understanding Natural Languages
• Image Recognition
• Automated customer support-Sending reminders, notifications, timing
alerts, messages, currencies to Rs. Conversion
• Health care-accuracy in diagnosing
• Finance- accuracy in decision-stock market
• Smart cars and drones
• Travel and navigation-book Trips/google maps
13
14. • Applications of AI
• Social Media
• Smart home
• Creative arts/Animations
• Security and Survillenace
• Uber
• Loan and Credit card processing
• Online banking
• Spam filters
• Identification Technologies-Biometric
• Intrusion Detection
• Agriculture
14
15. • Applications of AI
• Customer Preferences - based on previous searches Eg.Netflix
• Chat boxes-NLP, virtual assistant google duplex
• Space Exploration-Kepler telescope in order to identify a distant eight-
planet solar system.
15
18. • Artificial Intelligence Subfields - AI is EVERYWHERE –
• Machine Translation
• - Google Translate
• - Spam Filters
• Digital Personal Assistants
• - Siri
- Google Assistant
• - Cortana
• - Alexa
18
19. • Artificial Intelligence Subfields - AI is EVERYWHERE
• - Game players
• - DeepBlue
• - AlphaGo
• - “The Computer” in video games
• - Speech Recognition Systems
• - IBM
• - Dragon
• - Image Recognitions Systems
• - AlgorithmicTrading Systems
• - Black-Scholes Model (Caused crash in 1987)
• - AutomatedTrading Services
• - Recommender Systems
• - Amazon’s Suggestions
• - Google Ads
19
23. • What is Intelligence?
• ability of a system to calculate, reason, perceive relationships and
analogies, learn from experience, store and retrieve information from
memory, solve problems, comprehend complex ideas, use natural
language fluently, classify, generalize, and adapt new situations
• Types of Intelligence
23
24. Intelligence Description Example
Linguistic intelligence
The ability to speak, recognize, and
use mechanisms of phonology
(speech sounds), syntax
(grammar), and semantics
(meaning).
Narrators, Orators
Musical intelligence
The ability to create, communicate
with, and understand meanings
made of sound, understanding of
pitch, rhythm.
Musicians, Singers, Composers
Logical-mathematical intelligence
The ability of use and understand
relationships in the absence of
action or objects. Understanding
complex and abstract ideas.
Mathematicians, Scientists
Spatial intelligence
The ability to perceive visual or
spatial information, change it, and
re-create visual images without
reference to the objects, construct
3D images, and to move and rotate
them.
Map readers, Astronauts, Physicists
24
25. Intelligence Description Example
Bodily-Kinesthetic intelligence
The ability to use complete or part
of the body to solve problems or
fashion products, control over fine
and coarse motor skills, and
manipulate the objects.
Players, Dancers
Intra-personal intelligence
The ability to distinguish among
one’s own feelings, intentions, and
motivations. Gautam Buddhha
Interpersonal intelligence
The ability to recognize and make
distinctions among other people’s
feelings, beliefs, and intentions. Mass Communicators, Interviewers
25
27. • Intelligence
• Reasoning − It is the set of processes that enables us to provide basis for
judgement, making decisions, and prediction.
• Inductive Reasoning-specific observations to makes broad general statements
• Example − "Nita is a teacher. Nita is studious. Therefore, All teachers are studious."
• Deductive Reasoning-It starts with a general statement and examines the
possibilities to reach a specific, logical conclusion.
• Example − "All women of age above 60 years are grandmothers. Shalini is 65 years. Therefore,
Shalini is a grandmother.“
Learning-gaining knowledge or skill by studying, practising, being
taught, or experiencing something.
Types-Auditory,stimulus,perceptutional, observational etc
Problem Solving -Decision making
Perception-sensor
Linguistic – Ability to speak,listen,write
27
29. • Types of Learning Based on Ability
• Artificial Narrow Intelligence-does not posses any thinking ability.
Eg.-Siri, Alexa, Self-driving cars, Alpha-Go, Sophia the humanoid and so on
• Artificial General Intelligence-ability to think and make decisions
• Eg-Biological , agricultural, drowns , scientific etc
• Artificial Super Intelligence-super pass humans
• Eg.film, fictions
• Types of Learning Based on Functionality
• Reactive Intelligence- operate solely based on the present data, taking into
account only the current situation
• cannot form inferences from the data to evaluate their future actions.
• perform a narrowed range of pre-defined tasks.Eg. IBM Chess program
29
30. • Limited Memory AI
• used to store past experiences and hence evaluate future actions.
Eg.Self Driving car-use sensor for decision
• Theory of Mind AI
• major role in psychology
• emotional intelligence so that human believes and thoughts can be
better comprehended.
• Self Aware
• own consciousness and become self-aware.
• Superintelligence
• Futuristics
30
31. • Branches of AI
• Logical AI-mathematical logical language, do by inferring
• Search —large numbers of possibilities Eg.chess
• Pattern Recognition-try to match a pattern of eyes and a nose in a scene in
order to find a face. Eg.Fraud detection
• Representation-Visuals using logics
• Inference-Mathematical logical deduction Eg. when we hear of a bird, we infer
that it can fly, monotonic
• Common sense knowledge and Reasoning- futuristic
• Learning from experience-types of learning
• Planning – scheduling , drawings
• Ontology-Deals with objects and its properties
• Heuristic-search or to measure how far a node in a search tree
• Genetic-Hierarchial and high level problem solving
31
32. • Difference between Humans and Machines
S.No Humans Machines
1 Perceive by patterns perceive by set of rules and data.
2 store and recall information by
patterns
Eg:40404040
searching algorithms
3 figure out the complete object even if
some part of it is missing
machines cannot do
32
33. Task Domains of Artificial Intelligence
Mundane (Ordinary) Tasks Formal Tasks Expert Tasks
•Perception
• Computer Vision
• Speech, Voice
•Mathematics
•Geometry
•Logic
•Integration and Differentiation
•Engineering
•Fault Finding
•Manufacturing
•Monitoring
•Natural Language Processing
• Understanding
• Language Generation
• Language Translation
•GamesGo
•Chess (Deep Blue)
•Ckeckers
Scientific Analysis
Common Sense Verification Financial Analysis
Reasoning Theorem Proving Medical Diagnosis
Planing Creativity
•Robotics
• Locomotive
33
35. • What are Agent and Environment?
• Artificial intelligence is defined as a study of rational agents A rational agent
could be anything which makes decisions, as a person, firm, machine, or software.
It carries out an action with the best outcome after considering past and current
percepts
• Human Agent, Robotic agent, Software Agent
35
36. • An AI system is composed of an agent and its environment. The agents act in
their environment. The environment may contain other agents. An agent is
anything that can be viewed as :
• perceiving its environment through sensors and
• acting upon that environment through actuators
• Agent Terminology
• Performance Measure of Agent
• Behavior of Agent
• Percept –perceptual instance at a given instance
• Percept Sequence-perceived till date
• Agent Function-map from percept sequence to an action
36
37. • Exampes:AI assistants, like Alexa and Siri,
• they use sensors to perceive a request made by the user and the
automatically collect data from the internet without the user's help. They
can be used to gather information about its perceived environment such
as weather and time.
37
38. • Examples of Agent:-
A software agent has Keystrokes, file contents, received network packages which act
as sensors and displays on the screen, files, sent network packets acting as actuators.
A Human agent has eyes, ears, and other organs which act as sensors and hands,
legs, mouth, and other body parts acting as actuators.
A Robotic agent has Cameras and infrared range finders which act as sensors and
various motors acting as actuators.
• Types of Agents
• Simple Reflex Agents
• Model-Based Reflex Agents
• Goal-Based Agents
• Utility-Based Agents
• Learning
38
39. • Fear Over AI
• - a good example rajini enthiran movie
• AI will produce biased outcomes
• Algorithms are only as good as the data that they are trained on. So if a dataset
includes the historical biases of an organization, then the predictions it makes will
reflect that historical behavior.– ignore expert who belong to other behaviour
• We (will) have no idea why AI does what it does-black box
• Fear of unforseen - automatic vehicle driving
• AI is a Job killer
• Bad people do bad things
• Privacy Considerations-Automatic recording
• Lacking out of box thinking
39
41. • Machine Learning
• Machine learning is concerned with algorithms which train a machine
learning model to learn how to perform tasks using data rather than
hand-coded rules.
• Machine learning data most frequently takes the form of input-label pairs
(x, y) where x is the input to a machine learning model and y is the label
or expected output
• Data is often split into three partitions: training data,
validation/development data, and testing data
41
41
42. Artificial Intelligence Machine learning
Artificial intelligence is a technology which enables a
machine to simulate human behavior.
Machine learning is a subset of AI which allows a
machine to automatically learn from past data without
programming explicitly.
The goal of AI is to make a smart computer system like
humans to solve complex problems.
The goal of ML is to allow machines to learn from data so
that they can give accurate output.
In AI, we make intelligent systems to perform any task
like a human.
In ML, we teach machines with data to perform a
particular task and give an accurate result.
Machine learning and deep learning are the two main
subsets of AI.
Deep learning is a main subset of machine learning.
AI has a very wide range of scope. Machine learning has a limited scope.
AI is working to create an intelligent system which can
perform various complex tasks.
Machine learning is working to create machines that can
perform only those specific tasks for which they are
trained.
AI system is concerned about maximizing the chances of
success.
Machine learning is mainly concerned about accuracy
and patterns.
42
42
43. Artificial Intelligence Machine learning
The main applications of AI are Siri, customer support
using catboats, Expert System, Online game playing,
intelligent humanoid robot, etc.
The main applications of machine learning are Online
recommender system, Google search
algorithms, Facebook auto friend tagging
suggestions, etc.
On the basis of capabilities, AI can be divided into three
types, which are, Weak AI, General AI, and Strong AI.
Machine learning can also be divided into mainly three
types that are Supervised learning, Unsupervised
learning, and Reinforcement learning.
It includes learning, reasoning, and self-correction. It includes learning and self-correction when introduced
with new data.
AI completely deals with Structured, semi-structured,
and unstructured data.
Machine learning deals with Structured and semi-
structured data.
43
43
45. Learning Proceeding Cont.
7/22/2020 45
Machine Learning is a type of Artificial
Intelligence that provides computers with the
ability to learn without being explicitly
programmed
AI
M
L
DL Part of the machine learning field of learning representations of data.
Exceptional effective at learning
Utilizes learning algorithms that derive meaning out of data by using a hierarchy of
multiple layers that mimic the neural networks of our brain
If the system is provided with tons of information, it begins to understand it and
respond in useful ways
45
49. • Searching is the universal technique of problem solving
• Popular AI Search Algorithms
• Single Agent Pathfinding Problems
• Travelling Salesman Problem, Rubik’s Cube, and Theorem Proving.
49
49
50. • Search Terminology
• Problem Space − It is the environment in which the search takes place. (A set
of states and set of operators to change those states)
• Problem Instance − It is Initial state + Goal state.
• Problem Space Graph − It represents problem state. States are shown by
nodes and operators are shown by edges.
• Depth of a problem − Length of a shortest path or shortest sequence of
operators from Initial State to goal state.
• Space Complexity − The maximum number of nodes that are stored in
memory.
• Time Complexity − The maximum number of nodes that are created.
• Admissibility − A property of an algorithm to always find an optimal
solution.
• Branching Factor − The average number of child nodes in the problem space
graph.
• Depth − Length of the shortest path from initial state to goal state.
50
50
54. • THE FUTURE OF ARTIFICIAL INTELLIGENCE
• Artificial intelligence is impacting the future of virtually every industry
and every human being. Artificial intelligence has acted as the main
driver of emerging technologies like big data, robotics and IoT, and it
will continue to act as a technological innovator for the foreseeable
future.
54
54
But what is Artificial Intelligence. In general, it is the ability for a machine to perform tasks that would normally require a person to do. And just like people, it’s the ability to take information, make decisions based on it and cause an action to be taken. Such as moving an arm, creating and image or text, or providing a suggestion.