• It is the study of the general principles of building intelligent agents.
• An agent is any device that can perceive its environment through sensors and react to it by taking action to achieve a stated goal.
• Mimicking human senses, i.e., sight, sound, touch, smell, taste, is a form of perception.
• Intelligent agents should be able to interpret and process other forms of input such as text, semi-structured, and structured data.
• Output of an intelligent agent could be in multiple forms such as movement (reaching a destination), decision taken, sound etc.

• Several applications of AI that have not only improved our day-to-day lives but help in saving lives
• Google Maps
• Web Search
• Intelligent Assistants (Siri, Cortana etc.)
• Targeted advertising
• Diagnosis of diseases
• Autonomous vehicles
• Playing games (Jeopardy, Chess, Go etc.)
• Robots

Subfields of AI

• Planning
• Natural Language Processing
• Learning (Machine Learning)
• Computer Vision
• Robotics
• Knowledge Representation and Reasoning
• Artificial Neural Networks

• Techniques to capture knowledge about the world in a form that machines can understand
• A Car is a type of Vehicle
• Car has exactly four wheels
• Car has at least two doors and at most four doors
• Reasoning is the process of deriving new facts (knowledge) based on existing facts
• All birds fly
• Pigeon is a bird
• Can Pigeon fly?
• KRR is the field of AI that helps an agent to use what it knows (background knowledge) to decide what to do

KRR Formalisms

• Different mechanisms to capture knowledge and reason over it
• Frames
• Semantic Nets
• Logic
• First Order Logic
• Description Logics
• Ontologies
• Resource Description Framework (RDF)

Three Themes

1. Building Models
• Describe the world in abstract terms to simplify its understanding
2. Computing with Knowledge
• Machines that can do logical deduction/inference from encoded knowledge in order to draw meaningful conclusions
3. Exchanging Information
• Transmission of complex information between machines that allows distribution, interlinking, and reconciliation of knowledge
• RSS - some versions of RSS use RDF

Enabling Technologies

• Purpose is to provide structure to the Web and to the data in general
• Move from web of documents to web of data (Linked Data)
• Semantic Web technologies and W3C standards
• RDF (Resource Description Framework)
• OWL (Web Ontology Language)
• SPARQL (query language)
• SHACL (Shapes Constraint Language)

Linked Data

Structured Data (RDF) Demo

• Google Structured Data Markup Helper


• RDF Translator

RDF Graph

• Triples that describe any resource
• <Delhi> <capitalOf> <India>
• Triples are directed labelled graphs

Property Graph

Knowledge Graph

Knowledge Graph

• There is no standard definition of Knowledge Graphs
• It is a graph that captures knowledge in the form of entities, relationships between them, properties, and additional information including provenance
• "Things" not strings. Things should have semantics.
• Eg: What does it mean to be a "Person", "Organization", etc.
• Things are entities that have properties and are connected by relationships

Applications

• Knowledge Graphs are used in several domains and by several commercial enterprises
• Healthcare
• Geoscience
• Industrial domains such as manufacturing, power, oil and gas
• Web Search
• Recommender systems
• Conversational agents (chatbots, QA systems)
• Google, Microsoft, Amazon, Ebay, LinkedIn, GE, Accenture etc.

Gartner's Hype Cycle