This is the lecture delivered at Jadavpur University for the engineering students. The lecture was organised by the JU Entrepreneurship Cell and Alumni Association, Singapore Chapter.
Artificial Intelligence for Business - Version 2Nicola Mattina
This presentation is part of a workshop that will help you understand artificial intelligence tools and how they can be employed across your organization.
Lectures and activities are customized considering the background of the participants to highlight the use of artificial intelligence in a specific industry and in three different areas: product development, customer care, business operations.
Workshop structure
120’ lectures
2 activities to apply the concepts
1 practical toolkit
Keynote from Intellifest 2012 addressing the differences between narrow (classical) Artificial Intelligence and Artificial General Intelligence. Implications of cloud computing for AGI are also discussed.
Ajit Jaokar, Data Science for IoT professor at Oxford University “Enterprise ...Dataconomy Media
“Enterprise AI - Artificial Intelligence for the Enterprise."
AI is impacting many areas today. This talk discusses how AI will impact the Enterprise and what it means in the near future. The talk is based on my course I teach at the University of Oxford.
Artificial Intelligence for Business - Version 2Nicola Mattina
This presentation is part of a workshop that will help you understand artificial intelligence tools and how they can be employed across your organization.
Lectures and activities are customized considering the background of the participants to highlight the use of artificial intelligence in a specific industry and in three different areas: product development, customer care, business operations.
Workshop structure
120’ lectures
2 activities to apply the concepts
1 practical toolkit
Keynote from Intellifest 2012 addressing the differences between narrow (classical) Artificial Intelligence and Artificial General Intelligence. Implications of cloud computing for AGI are also discussed.
Ajit Jaokar, Data Science for IoT professor at Oxford University “Enterprise ...Dataconomy Media
“Enterprise AI - Artificial Intelligence for the Enterprise."
AI is impacting many areas today. This talk discusses how AI will impact the Enterprise and what it means in the near future. The talk is based on my course I teach at the University of Oxford.
Had a 90 minutes introductory lecture at the Technozion 2018 organised by NIT Warangal. Touched upon many aspects of AI, from definition to constituting properties to scientific elements behind the scene. Ended the lecture with a brief intro to IBM tools available to build AI solution.
Shawn Riley, Chief Data Officer & Chief Information Security Officer, DarkLight Inc. on Artificial Intelligence in Cybersecurity. Shawn provides a formal definition of artificial intelligence, describes the two primary fields of artificial intelligence being applied in the cyber defense ecosystem, Data Science derived AI such as machine learning and deep learning & Knowledge Engineering derived AI such as expert systems. Shawn then looks at topics such as explainability, reproducibility, and use of AI in zero-trust.
Slides from the 12 minute YouTube video https://youtu.be/Ubq8lTUey7Q
Talking SoS with Shawn Riley - Slides from - A 25 Minute Primer On Cybersecur...Shawn Riley
A video series on the Science of Security (SoS) with Cybersecurity Scientist Shawn Riley
Recorded - Tuesday, December 12, 2018
Topics in this video....
What is Science?
What is Cybersecurity Science?
Operational Cyber Defense Knowledge
Three Sources of Knowledge
Symbolic AI & Non-symbolic AI
4 Types of Knowledge Models
Cognitive Playbooks – Experience
Claim Evidence Reasoning – Argumentation
Comparing Symbolic AI & Non-symbolic AI
1.0 Introduction
1.1 Objectives
1.2 Some Simple Definition of A.I.
1.3 Definition by Eliane Rich
1.4 Definition by Buchanin and Shortliffe
1.5 Another Definition by Elaine Rich
1.6 Definition by Barr and Feigenbaum
1.7 Definition by Shalkoff
1.8 Summary
1.9 Further Readings/References
Artificial Intelligence and Soft Computing.Brief view of AI it's components and the importance of soft computing in AI.Several applications of AI and various fields of application.
The Foundations of Artificial Intelligence, The History of
Artificial Intelligence, and the State of the Art. Intelligent Agents: Introduction, How Agents
should Act, Structure of Intelligent Agents, Environments. Solving Problems by Searching:
problem-solving Agents, Formulating problems, Example problems, and searching for Solutions,
Search Strategies, Avoiding Repeated States, and Constraint Satisfaction Search. Informed
Search Methods: Best-First Search, Heuristic Functions, Memory Bounded Search, and Iterative
Improvement Algorithms.
This presentation is an introduction to artificial intelligence: expert systems components. Topics covered are the following: defining artificial intelligence; expert systems key terms; expert systems requirements; expert systems components; and selecting appropriate problems for expert systems.
Building an AI App: A Comprehensive Guide for BeginnersChristopherTHyatt
"Discover the steps to create your own AI app: Choose a framework, define your app's purpose, collect and prepare data, train the model, integrate a user-friendly interface, and deploy successfully."
The power and potential of artificial intelligence cannot be overstated. It has transformed how we interact with technology, from introducing us to robots that can perform tasks with precision to bringing us to the brink of an era of self-driving vehicles and rockets. And this is just the beginning. With a staggering 270% growth in business adoption in the past four years, it has been clear that AI is not just a tool for solving mathematical problems but a transformative force that will shape the future of our society and economy.
Artificial Intelligence (AI) has become an increasingly common presence in our lives, from robots that can perform tasks with precision to autonomous cars that are changing how we travel. It has become an essential part of everything, from large-scale manufacturing units to the small screens of our smartwatches. Today, companies of all sizes and industries are turning to AI to improve customer satisfaction and boost sales. AI is the next big thing, making its way into the inner workings of Fortune 500 companies to help them automate their business processes. Investing in AI can be beneficial for businesses looking to stay competitive in a fast-paced business world.
Had a 90 minutes introductory lecture at the Technozion 2018 organised by NIT Warangal. Touched upon many aspects of AI, from definition to constituting properties to scientific elements behind the scene. Ended the lecture with a brief intro to IBM tools available to build AI solution.
Shawn Riley, Chief Data Officer & Chief Information Security Officer, DarkLight Inc. on Artificial Intelligence in Cybersecurity. Shawn provides a formal definition of artificial intelligence, describes the two primary fields of artificial intelligence being applied in the cyber defense ecosystem, Data Science derived AI such as machine learning and deep learning & Knowledge Engineering derived AI such as expert systems. Shawn then looks at topics such as explainability, reproducibility, and use of AI in zero-trust.
Slides from the 12 minute YouTube video https://youtu.be/Ubq8lTUey7Q
Talking SoS with Shawn Riley - Slides from - A 25 Minute Primer On Cybersecur...Shawn Riley
A video series on the Science of Security (SoS) with Cybersecurity Scientist Shawn Riley
Recorded - Tuesday, December 12, 2018
Topics in this video....
What is Science?
What is Cybersecurity Science?
Operational Cyber Defense Knowledge
Three Sources of Knowledge
Symbolic AI & Non-symbolic AI
4 Types of Knowledge Models
Cognitive Playbooks – Experience
Claim Evidence Reasoning – Argumentation
Comparing Symbolic AI & Non-symbolic AI
1.0 Introduction
1.1 Objectives
1.2 Some Simple Definition of A.I.
1.3 Definition by Eliane Rich
1.4 Definition by Buchanin and Shortliffe
1.5 Another Definition by Elaine Rich
1.6 Definition by Barr and Feigenbaum
1.7 Definition by Shalkoff
1.8 Summary
1.9 Further Readings/References
Artificial Intelligence and Soft Computing.Brief view of AI it's components and the importance of soft computing in AI.Several applications of AI and various fields of application.
The Foundations of Artificial Intelligence, The History of
Artificial Intelligence, and the State of the Art. Intelligent Agents: Introduction, How Agents
should Act, Structure of Intelligent Agents, Environments. Solving Problems by Searching:
problem-solving Agents, Formulating problems, Example problems, and searching for Solutions,
Search Strategies, Avoiding Repeated States, and Constraint Satisfaction Search. Informed
Search Methods: Best-First Search, Heuristic Functions, Memory Bounded Search, and Iterative
Improvement Algorithms.
This presentation is an introduction to artificial intelligence: expert systems components. Topics covered are the following: defining artificial intelligence; expert systems key terms; expert systems requirements; expert systems components; and selecting appropriate problems for expert systems.
Building an AI App: A Comprehensive Guide for BeginnersChristopherTHyatt
"Discover the steps to create your own AI app: Choose a framework, define your app's purpose, collect and prepare data, train the model, integrate a user-friendly interface, and deploy successfully."
The power and potential of artificial intelligence cannot be overstated. It has transformed how we interact with technology, from introducing us to robots that can perform tasks with precision to bringing us to the brink of an era of self-driving vehicles and rockets. And this is just the beginning. With a staggering 270% growth in business adoption in the past four years, it has been clear that AI is not just a tool for solving mathematical problems but a transformative force that will shape the future of our society and economy.
Artificial Intelligence (AI) has become an increasingly common presence in our lives, from robots that can perform tasks with precision to autonomous cars that are changing how we travel. It has become an essential part of everything, from large-scale manufacturing units to the small screens of our smartwatches. Today, companies of all sizes and industries are turning to AI to improve customer satisfaction and boost sales. AI is the next big thing, making its way into the inner workings of Fortune 500 companies to help them automate their business processes. Investing in AI can be beneficial for businesses looking to stay competitive in a fast-paced business world.
This step-by-step guide will show you how to build and use an AI app. Whether you are a researcher, business owner or just curious about AI technology, these instructions will help you navigate the steps of creating an AI system that can transform your industry.
Artificial intelligence (AI) is a field of computer science that focuses on solving cognitive programs associated with human intelligence, such as pattern recognition, problem-solving and learning. AI refers to the use of advanced technology, such as robotics, in futuristic scenarios.
In today's tech-driven world, the integration of artificial intelligence (AI) into applications has become increasingly prevalent. From personalized recommendations to intelligent chatbots, AI enhances user experiences and optimizes processes. However, building an AI app can seem daunting to those unfamiliar with the process. Fear not! This guide aims to demystify the journey, offering step-by-step insights into how to build an AI app from scratch.
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas?
AI and automation is all the rage nowadays - but what’s the history of these technologies, innovations and ideas? This slides will discuss the brief history of the current interesting technologies and their development to society and mankind.
leewayhertz.com-How to build an AI app.pdfrobertsamuel23
The power and potential of artificial intelligence cannot be overstated. It has transformed
how we interact with technology, from introducing us to robots that can perform tasks
with precision to bringing us to the brink of an era of self-driving vehicles and rockets
This presentation gives you a broad overview of Artificial Intelligence. It explains briefly the technologies and concepts that fall under the domain of AI.
Understanding Artificial Intelligence - Major concepts for enterprise applica...APPANION
Artificial Intelligence is a fundamental topic – for us as humans, as a society but also for businesses. For business executives and decision-makers, it is sometimes hard to keep up with rapidly evolving technologies as part of the day-to-day business. By providing this curated compilation of information about the fundamental aspects of AI, we want to captivate and inspire you to become more involved with the technology by better understanding the underlying concepts and value drivers of this technology
AI & Cognitive Computing are some of the most popular business an technical words out there. It is critical to get the basic understanding of Cognitive Computing, which helps us appreciate the technical possibilities and business benefits of the technology.
UNCOVERING FAKE NEWS BY MEANS OF SOCIAL NETWORK ANALYSISpijans
The short access to facts on social media networks in addition to its exponential upward push also made it tough to distinguish among faux information or actual facts. The quick dissemination thru manner of sharing has more high quality its falsification exponentially. It is also essential for the credibility of social media networks to avoid the spread of fake facts. So its miles rising research task to robotically check for misstatement of information thru its source, content material, or author and save you the unauthenticated assets from spreading rumours. This paper demonstrates an synthetic intelligence primarily based completely approach for the identification of the fake statements made by way of the use of social network entities. Versions of Deep neural networks are being applied to evalues datasets and have a look at for fake information presence. The implementation setup produced most volume 99% category accuracy, even as dataset is tested for binary (real or fake) labelling with multiple epochs.
UNCOVERING FAKE NEWS BY MEANS OF SOCIAL NETWORK ANALYSISpijans
The short access to facts on social media networks in addition to its exponential upward push also made it
tough to distinguish among faux information or actual facts. The quick dissemination thru manner of sharing has more high quality its falsification exponentially. It is also essential for the credibility of social media networks to avoid the spread of fake facts. So its miles rising research task to robotically check for
misstatement of information thru its source, content material, or author and save you the unauthenticated
assets from spreading rumours. This paper demonstrates an synthetic intelligence primarily based completely approach for the identification of the fake statements made by way of the use of social network
entities. Versions of Deep neural networks are being applied to evalues datasets and have a look at for
fake information presence. The implementation setup produced most volume 99% category accuracy, even
as dataset is tested for binary (real or fake) labelling with multiple epochs.
Discover the gateway to limitless possibilities at CBITSS. As a premier institution in technology education and consultancy, we specialize in nurturing the next generation of tech leaders. With a focus on practical skills and industry relevance, our training programs equip you with the expertise needed to excel in today's digital world. Whether you're a student aspiring to enter the tech industry or a professional seeking to upskill, CBITSS provides the perfect platform to ignite your career aspirations. Join us and embark on a transformative journey towards a brighter, tech-driven future.
Every thing about Artificial Intelligence Vaibhav Mishra
Artificial Intelligence is a way of making a computer, a computer-controlled robot, or a software think intelligently, in the similar manner the intelligent humans think.
This is the talk I delivered in one of the seminars organised by ASSOCHAM India in partnership with Department of IT and Electronics, Govt. of WB, India.
Introduction to Cognitive Computing the science behind and use of IBM WatsonSubhendu Dey
The lecture was given in a Cognitive and Analytics workshop at Indian Institute of Management. Topics covered was -
1) Understanding Natural Language Processing, Classification, Watson & its modules
2) Industry applications of Cognitive Computing
3) Understanding Cognitive Architecture
4) Understanding the disciplines / tools being used in Cognitive Science
The business models across industries around the world are becoming Customer Centric. Recent studies show that “knowing” customers based on internal as well as external data is one of the top priorities of business leaders. On the other hand various surveys also reveal that customers do not mind to share their semi-personal data for the benefit of differentiated service. In that context, the 360 degree view of customer – which was once thought to be a business process, master data management, data integration and data warehouse / business intelligence related problem has now entered into the whole new big world of BIG data including integration with unstructured data sources. Impact of big data on Customer Master Data Management is spread across - from Integration and linkage of unstructured or semi-structured data with structured master data that is maintained within enterprise; to analyze and visualization of the same to generate useful insight about the customers. There are various patterns to handle the challenges across the steps i.e. acquire, link, manage, analyze and distribute the enhanced customer data for differentiated product or services.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
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.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
The Roman Empire A Historical Colossus.pdfkaushalkr1407
The Roman Empire, a vast and enduring power, stands as one of history's most remarkable civilizations, leaving an indelible imprint on the world. It emerged from the Roman Republic, transitioning into an imperial powerhouse under the leadership of Augustus Caesar in 27 BCE. This transformation marked the beginning of an era defined by unprecedented territorial expansion, architectural marvels, and profound cultural influence.
The empire's roots lie in the city of Rome, founded, according to legend, by Romulus in 753 BCE. Over centuries, Rome evolved from a small settlement to a formidable republic, characterized by a complex political system with elected officials and checks on power. However, internal strife, class conflicts, and military ambitions paved the way for the end of the Republic. Julius Caesar’s dictatorship and subsequent assassination in 44 BCE created a power vacuum, leading to a civil war. Octavian, later Augustus, emerged victorious, heralding the Roman Empire’s birth.
Under Augustus, the empire experienced the Pax Romana, a 200-year period of relative peace and stability. Augustus reformed the military, established efficient administrative systems, and initiated grand construction projects. The empire's borders expanded, encompassing territories from Britain to Egypt and from Spain to the Euphrates. Roman legions, renowned for their discipline and engineering prowess, secured and maintained these vast territories, building roads, fortifications, and cities that facilitated control and integration.
The Roman Empire’s society was hierarchical, with a rigid class system. At the top were the patricians, wealthy elites who held significant political power. Below them were the plebeians, free citizens with limited political influence, and the vast numbers of slaves who formed the backbone of the economy. The family unit was central, governed by the paterfamilias, the male head who held absolute authority.
Culturally, the Romans were eclectic, absorbing and adapting elements from the civilizations they encountered, particularly the Greeks. Roman art, literature, and philosophy reflected this synthesis, creating a rich cultural tapestry. Latin, the Roman language, became the lingua franca of the Western world, influencing numerous modern languages.
Roman architecture and engineering achievements were monumental. They perfected the arch, vault, and dome, constructing enduring structures like the Colosseum, Pantheon, and aqueducts. These engineering marvels not only showcased Roman ingenuity but also served practical purposes, from public entertainment to water supply.
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?
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.
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.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
3. Disclaimer
The material presents authors' personal view. It does not necessarily present any
organization's official position.
3
4. Content
History of AI
What is AI
How to approach AI
The opportunity ahead for students
Q&A
4
5. History of AI
1637: Descartes – talks about two tests that
distinguish intelligent machines from real
human.
1950: Turing Test – operationalizes linguistic
indistinguishability
1956: the term AI was coined, and Logic theorist
was revealed
1997: Deep Blue won against Kasparov
2011: Watson competed on Jeopardy
2016: AlphaGo wone over Lee Sedol
2017: Sophia – the first humanoid Citizen
5
6. What is AI 6
Human based Ideal Rationality
Reasoning based Thinking Humanly Thinking Rationally
Behavior based Acting Humanly Acting Rationally
(Total) Turing Test
natural language processing
knowledge representation
automated reasoning
machine learning
computer vision
robotics
x Informal (and often non-certain)
knowledge cannot be always
codified in correct logical
notation.
x Practical solving is constrained
by computational resources.
Weak AI hypothesis - the assertion
that machines could act as if they
were intelligent
Strong AI hypothesis - the
assertion that machines that do so
are actually thinking (not just
simulating thinking)
7. Summing it up all
AI is the specialized branch of computer science that helps develop software systems
endowed with the intellectual characteristic of humans, such as the ability to understand
and extract meaning from unstructured content, reason, generalize, learn and react
(natural way) from experience.
Often AI enabled software uses foundational technologies like natural language
processing, computer vision, machine/deep learning, robotics and others to provide
manifestation of intellectual characteristics in the form of deep question answering, search
and planning, knowledge representation, process automation and decisioning.
7
8. How to approach AI 8
Logicist Approach Non-Logicist Approach
Probabilistic Technique Neuro-Computational Technique
• Classical deductive logic is
monotonic but
commonsense is not.
• Addition of new
information can cause the
previous inferences to fail
• Logic-based AI have
reached an impressive
maturity
• Use conditional
joint/probability of
events.
• Works on maximum
likelihood functions and
a-priori estimates
prediction.
• Example: Naïve based
classification.
• Non-linear functions, easy to
implement with large amount of
data.
• Inspired by the way neurons
work.
• Comprised of serial wiring of
input-activation-output
functions.
• Training is expensive but can be
pre-trained and used in business
functions.
9. How to approach AI – natural language processing
Broadly divided into two parts
Information Extraction: automatically extracts structured information from
unstructured and/or semi-structured machine-readable documents and other
electronically represented sources.
Information Retrieval: obtains information system resources that are relevant to
an information need from a collection of those resources.
Intermediate storage (inverted index)
Spell correction / approximation
Vector space model
Text classification and clustering
Document rank / PageRank
9
(Total) Turing Test
natural language
processing
knowledge
representation
automated
reasoning
machine learning
computer vision
robotics
Language
detection
Document
segregation
POS
Tagging
Stop-ward
removal
Tokenization
Stemming
Lemmatization
Entity +
Relationship
Recognition
10. How to approach AI – knowledge representation
While the NLP takes care of decoding the data, it needs to be represented to
generate appropriate output
Approach to representation
Simple Rational Knowledge
Inheritable Knowledge
Inferential Knowledge
Procedural Knowledge
10
(Total) Turing Test
natural language
processing
knowledge
representation
automated
reasoning
machine learning
computer vision
robotics
Name Age LANG
X 20 EN
Y 34 HN
Simple Relational Knowledge Inferential Knowledge
Perception
Learning
KR Reasoning
Planning
Execution
Lives at
Works at
Spouse of
Happened
at
Person
Organization
Loc ation
Event
11. How to approach AI – automated reasoning
Deductive reasoning
Inductive reasoning
Example:
Geospatial reasoning
Temporal reasoning
Relational reasoning
11
(Total) Turing Test
natural language
processing
knowledge
representation
automated
reasoning
machine learning
computer vision
robotics
Theory Hypothesis Patterns Confirmation
Observation Patterns Hypothesis Theory
12. How to approach AI – machine learning
Supervised learning: A form of learning in which the software tries to learn a function f
given examples, the training data T, of its values at various points in its domain
𝑻 = {⟨𝑥1, 𝒇(𝑥1)⟩, ⟨𝑥2, 𝒇(𝑥2)⟩, … , ⟨𝑥 𝑛, 𝒇(𝑥 𝑛)⟩}
Learn function h so that error = 𝑥∈𝑇 𝛿 (𝒇 𝑥 − 𝒉(𝑥)) is minimized
Unsupervised learning: tries to find useful knowledge out of raw data without any
function associated with input.
Clustering
PageRank
Reinforcement learning: suitable when the machine has to learn over a period of time
and the performance is not judged on one action but a series of actions and their
effect on environment.
12
(Total) Turing Test
natural language
processing
knowledge
representation
automated
reasoning
machine learning
computer vision
robotics
x
x
x
x x
x
x
13. Top few opportunities ahead for students
Virtual assistants – textual + voice based
Computer vision techniques for image /
video processing
Text mining and assisted intelligence
Enterprise search
Intelligent devices
13
Market forces
Contactless interactions
Cost optimization
Bias reduction
React faster
Better risk assessment
14. Opportunity is wide
Successful AI projects need a variety of roles, not just data science and domain
knowledge to build statistical / machine learning models.
A typical team composition
14
Role Responsibility
Exec sponsor Ensure the AI projects are aligned with the strategy. Obtain startup
funding.
System architect Operationalize the entire suite of machine learning and deep
learning models within the IT framework
Data engineer Define and implement the integration of data into the overall AI
architecture, while ensuring data quality
Data scientist Explore data to extract actionable information for making business
decisions. Typically from STEM field.
DevOps engineer Work with architects, developers, data engineers and the data
scientist to ensure solutions are rolled out and managed.
Business analyst Act as “translators” between the business users and the machine
learning team
Visualization expert Design/Build user interface for AI output
Application developer Build application for embedding AI
Typical team composition
Exec sponsor System architect Data engineer
Data scientist DevOps Engineer Business Analyst
Visualizationexpert Application Developer
Typical team composition
16. References
A. M. Turing (1950) Computing Machinery and Intelligence. Mind 49: 433-460.
Artificial Intelligence A Modern Approach – 3rd Edition
16
If there were machines which bore a resemblance to our body and imitated our actions as far as it was morally possible to do so, we should always have two very certain tests by which to recognise that, for all that, they were not real men
that they could never use speech or other signs as we do when placing our thoughts on record for the benefit of others.
that although machines can perform certain things as well as or perhaps better than any of us can do, they infallibly fall short in others, by which means we may discover that they did not act from knowledge, but only for the disposition of their organs.
If we are going to say that a given program thinks like a human, we must have some way of determining how humans think. We need to get inside the actual workings of human minds. There are three ways to do this:
through introspection—trying to catch our own thoughts as they go by
through psychological experiments—observing a person in action and
through brain imaging—observing the brain in action.
What do you mean by ”Improve business functions”?
Business functions could be –
- Topline growth, new business opportunity
- bottom line improvement, automation, productivity improvement, cheaper
Inverted index
- posting list vs incident matrix
- scan strategy, sequential scan vs skip pointers
- unigram, bi-gram, tri-gram index
- k-gram index helps in partial search as well
Spell correction / approximation
- edit distance
- soundex
Vector space model
- tf-idf
Classification
- KNN
- NaiveBayes
Various types of knowledge:
Declarative
Procedural
Meta
Heuristic
Structural
Expectation from KR system
Representational accuracy
Inferential adequacy
Inferential efficiency
Acquisitional efficiency
There are other reasoning which is not discussed here:
Abductive reasoning
Common sense reasoning
Monotonic reasoning
Non-monotonic reasoning