My ContentArtificial IntelligenceGoals of AIWhat Contributes to AIApplication of AIExpert Systems and Artificial Intelligence Characteristics of Expert System Component of Expert System Expert System in LIS fieldSocial Mobile Analytics cloud (SMAC) Social Mobile AnalyticsCloud ComputingWhat is CloudWhat is Cloud ComputingBasic Concepts Deployment Models Service Models Infrastructure as a service (IaaS)
Platform as a Service (PaaS)
Software as a Service (SaaS) Advantages Disadvantages
My Content
Platform as a Service (PaaS)
Software as a Service (SaaS)
Application of Artificial intelligence, Expert Systems and Robotics in Libraries, Social Mobile Analytics Cloud (SMAC); Cloud Computing
Artificial Intelligence
Since the invention of computers or machines, their capability to perform various tasks went on growing exponentially. Humans have developed the power of computer systems in terms of their diverse working domains, their increasing speed and reducing size with respect to time. A branch of computer science named artificial Intelligence pursues creating the computers or machines as intelligent as human beings.
According to the father of Artificial Intelligence, Jhon McCarthy, it is "the Science and engineering of making intelligent machines, especially intelligent computer programs ".
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.
Al is accomplished by studying how human brain thinks, and how humans learn, decide, and work while trying to solve a problem, and them using the outcomes of this study as a basis of developing intelligent software and systems.
Philosophy of AI : While exploiting the power of the computer systems, the curiosity of human, lead him to wonder, can a machine think and behave like humans do? Thus, the development of Al started with the intention of creating similar intelligence in machines that we find and regard high in humans.
Goals of AI
i. To Create Expert Systems : The system which exhibit intelligent behavior, learn, demonstrate, explain and advice its users.
ii. To Implement Human Intelligence in Machines : Creating systems that understand, think, learn and behave like humans.
What Contributes to AI
Artificial intelligence is a science and technology based on disciplines such as computer science, biology, psychology, linguistics, mathematics and engineering. A major thrust of Al is in the development of computer functions associated with human intelligence, such as reasoning, learning and problem solving.
Application of AI
i. Al in Gaming
ii. Al in Natural Language Processing (NLP)
iii. AI in Healthcare.
iv. Al in Finance.
v. Al in Data Security.
vi. Export System.
vii. Computer vision
viii. Speach Recognition
x. Robotics.
xi. Al in e-commerce.
Expert Systems and Artificial Intelligence
The export systems are the computer application developed to solve complex problems in a particular domain, at the level of extra-ordinary human intelligence and expertise.
Characteristics of Expert System
i. High Performance.
ii. Understandable.
iii. Reliable.
iv. Highly responsive.
Component of Expert System
The component of ES include.
i. Knowledge Base
ii. Inference Engine.
iii. User interface.
Expert System are meant to solve real problems, which normally would require a specialised human export. Building an expert system first involves extracting the relevant knowledge from the human expert. The application of expert system in LIS field in the following areas :
i. Intelligent interfaces, in particular interfaces for online information retrieval system.
ii. Subject analysis and representation including classification, indexing and abstracting services.
iii. Information storage and retrieval system in general.
iv. References and referral systems.
v. Hypertext and hypermedia
vi. Collection development.
Social Mobile Analytics cloud (SMAC)
Social :
Social Media platform such as Twitter, Facebook, Instagram and Snapchat have enabled new ways to reach, interact with targeted and acquire customers. It has influenced new marketing strategy to campaigns, and new data source such as reports; hashtags, and network connection.
According to survey, there are over 465 million active twitter accounts; 1.06 billions users at facebook, approx. (15% of world's population).
With the use of social Media : Understanding of consumer perception will be easier, easy of branding, better customer service, SEO etc.
Mobile :
Mobile technologies such as iphone, smartphones, iPad have changed the way people communicate, shop and work. It helps to find the location of users, cost effective marketing, direct selling opportunities.
Analytics :
Analyties in SMAC refers to big data (OLAP) which is fast growing dataset - both structure and unstructure data which is used to predict the future customer behaviors tools : SAP HANA etc.
According to survey, over 2.5 billion gigabytes old data is generated Per day; 90% of data was created in the last 3 to 4 years; Amount of data will be double in every two years.
Cloud : Cloud refers cloud computing concept that shares resources pool on the internet instead of personal hard drive. It reduces cost of IT and infrastructure. Example: Amazom web services.
Cloud Computing
Cloud computing provides us a meand by which we can access the application as utilities, over the internet. It allows us to create, configure and customize applications online.
With cloud computing users can access database resources via the internet from anywhere for as long as they need without worrying about any maintenance or management of actual resources.
What is Cloud
The term cloud refers to a Network or internet. In other words, we can say that cloud is something, which is present at remote location.
Cloud can provide services over network, i.e. on public networks or on private networks. i.e. WAM, LAN on VPN.
Applications such as e-mail web conferencing, Customer Relationship Management (CRM) all run in cloud.
What is Cloud Computing
Cloud computing refers to manipulating, configuring and accessing the application online. It offers online data storage, infrastructure and application.
Cloud computing is both a combination of software and hardware based computing resources delivered as a network service.
Basic Concepts
There are certain services and models working behind the scene making the cloud computing feasible and accessible to and users. Following are the working models for cloud computing.
1. Deployment Models.
2. Service Models.
1. Deployment Models
Deployment models define the type of access to the cloud, i.e. how the cloud is located ? cloud can have any of the four types of access : public, private, hybrid and community.
2. Service Models
Service Models are the reference modes on which the cloud computing is based. These can be categorized into three basic service models as listed below :
i. Infrastructure as a service (IaaS)
ii. Platform as a Service (PaaS)
iii. Software as a Service (SaaS)
i. Infrastructure as a Service (IaaS)
IaaS is the delivery of technology infrastructure as an on demands scalable service. IaaS provides access to fundamental resources such as physical machines, virtual machines, virtual storage, etc.
• Usually billed based on usage.
• Usually multi tenant virtualized environment.
• Can be coupled with managed services for OS and application support.
ii. Platform as a Service (PaaS)
PaaS provides the routine environment for applications, development and deployment tools, etc.
PaaS provides all of the facilities required to support the complete life cycle of building and delivering web applications and services entirely from the internet.
Typically applications must be developed with a particular platform in mind.
• Multi tenant environments.
• Highly scalable multi tier architecture.
iii. Software as a Service (SaaS)
SaaS model allows to use software applications as a service to end users.
SaaS is a software delivery methodology that provides licensed multi-tenant access to software and its functions remotely as a web based service.
• Usually billed based on usage.
• Usually multi tenant environment
• Highly scalable architecture.
Advantages
• Lower Computer costs.
• Improved Performance.
• Reduced software costs.
• Instant software updates.
• Improved document format compatibility
• Unlimited storage capacity.
• Increased data reliability.
• Universal document access
• Latest version availability
• Easier group collaboration.
• Device independence.
Disadvantages
• Requires a constant internet connection
• Does not work well with low
• Features might be limited
• Can be slow
• Stored data can be lost
• Stored data might no be secure.
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