ITM 100: Emerging Technologies & AI

Emerging Technologies & AI

• This class, ITM 100, is about emerging technologies and AI.
• The notes are adapted from "Management Information Systems: Managing the Digital Firm, 17th Edition" by Kenneth C. Laudon and Jane P. Laudon.

Hardware Platform Trends

• The mobile digital platform is a key trend.
• Consumerization of IT and BYOD (Bring Your Own Device)
• Virtualization
• Cloud computing
• Green computing
• Quantum computing

The Mobile Digital Platform

• Smartphones
• Netbooks
• Tablet computers
• Digital e-book readers (Kindle)
• Wearable devices

Wearable Devices

• Transforming the way people live.
• Fitness, wellness, and healthcare applications.
• Infotainment (information and entertainment) through smart glasses.
• Fashion and military applications.
• Example: A Montreal-based fashion designer's wearable device.

Consumerization of IT and BYOD

• Technology emerges in the consumer market and then spreads into businesses.
• BYOD forces businesses and IT departments to rethink how IT equipment and services are acquired and managed.

Virtualization

• Presents computing resources so that they can be accessed in ways not restricted by configuration.
• Allows single physical resources to act as multiple resources.
• Reduces hardware and power expenditures.
• Facilitates hardware centralization.
• Software-defined storage (SDS).

Cloud Computing

• Off-loads peak demand for computing power to remote, large-scale data processing centers.
• Pay only for the computing power used.
• Excellent for firms with spiked demand curves (e.g., holiday shopping).
• Saves firms from purchasing excessive levels of infrastructure.
• Stores data permanently in remote servers accessible through the internet.

Cloud Computing Services

• Infrastructure as a service (IaaS)
  • Customers use computing resources to run their information systems.
  • They pay only for the computing capacity used.
• Platform as a service (PaaS)
  • Customers use infrastructure and programming tools for developing their applications (e.g., Bluemix).
• Software as a service (SaaS)
  • Customers use software hosted on a vendor's cloud (e.g., Google Apps).

Cloud Computing (General)

• A cloud can be private or public.
• Amazon Web Service (AWS) is a public cloud.
• A private cloud is operated only for a single organisation.
• Concerns include security and availability.

Green Computing

• Practices and technologies for manufacturing, using, and disposing of computing and networking hardware.
• Reducing power consumption is a priority.
• Data centers use as much energy as the output of 30 nuclear power plants.

Quantum Computing

• Uses quantum physics to represent and operate on data.
• Dramatic increase in computing speed.
• Conventional computers handle bits as 0 or 1; quantum computers can handle bits as 0, 1, or both simultaneously.
• Solves business and scientific problems millions of times faster.

Software Platform Trends

• Open-source software
• Software for the web (Java, HTML, HTML5)
• Web services and service-oriented architecture
• Software outsourcing and cloud services

Open-source Software

• Free and modifiable by users.
• Developed and maintained by a worldwide network of programmers and designers.
• Examples: Apache web server, Mozilla Firefox browser, OpenOffice, Linux.

Software for the web

• Java is a prominent object-oriented (OO) language for PC and mobile environments.
• Java Virtual Machine (JVM) converts Java code to native computer language.
• Python is used for building cloud computing applications.
• Objective-C is a predecessor to Swift for iOS mobile app development.
• Swift is a popular mobile app language for iOS.

Hypertext Markup Language (HTML)

• Used to create or build webpages.
• A markup language that uses tags to annotate information in a document.
• Tags are syntactic elements in a markup language that annotate information in a document.

Apps and Mashups

• Apps are small software pieces for internet, computer, or mobile use.
• Generally delivered over the internet.
• Mashups combine two or more online applications (e.g., Google Maps with local content).

Web Services and Service-Oriented Architecture (SOA)

• SOA: Set of self-contained services communicating to form a software application.
• Software developers reuse these services in different combinations.
• Web Services: software components exchanging information via web standards and languages.
• XML: Extensible Markup Language (more powerful and flexible than HTML).
• Tagging enables computer processing of data automatically.

XML (Extensible Markup Language)

• A language allowing users to describe document content.
• HTML describes how a document looks; XML describes its meaning.

Software Outsourcing and Cloud Services

• Three external software sources:
  • Software packages (prewritten).
  • Software outsourcing (contracting with external providers).
  • Cloud-based software (e.g., Salesforce.com).
• Service Level Agreements (SLAs) are formal agreements with service providers.

Changing Sources of Firm Software

• Shows the trend of increasing software spending and outsourced software.

Artificial Intelligence (AI)

• Grand Vision: Computer hardware and software systems as intelligent as humans.
• Realistic Vision: Systems taking data inputs, processing them, and producing outputs (like software) that perform complex tasks difficult or impossible for humans.

Examples of AI

• Recognizing millions of faces in seconds.
• Interpreting medical scans (CT scans).
• Analyzing financial records.
• Detecting patterns in large datasets (Big Data).
• Improving performance over time ("learning").
• Navigating in certain conditions (like self-driving cars).

Major Types of AI

• Expert systems
• Machine learning
• Neural networks and deep learning networks
• Natural language processing (NLP)
• Computer vision
• Robotics

Intelligent Systems

• Expert systems are used to capture tacit knowledge of human experts.
• Rules in an expert system are captured from skilled employees using if-then rules.
• Capture expert knowledge in a reusable form, accessible by others.

Knowledge-Based systems

• Software that uses a specific set of information to extract and process particular pieces.
• Example: Expert system.
  • Rule-based system: a software system based on a set of if-then rules.
  • Inference engine: software that processes rules to draw conclusions.

Rules in an Expert System

• Examples of if-then rules for credit granting.

Inference Engines

• Examples of rules based for insurance, real estate, etc.

Machine Learning

• Improving computer program performance without explicit programming.
• Recognizing patterns and experiencing/learning from prior learnings/databases.
• Supervised vs. unsupervised learning.
• Contemporary examples: Google searches, recommender systems on Amazon, Netflix.

Neural Networks

• Finding patterns and relationships in massive amounts of data.
• "Learning" through relationships, building models, and correcting.
• Training neural networks by feeding data inputs and expected outputs.
• Used in medicine, science, and business. (e.g., pattern classification, prediction, financial analysis)

Artificial Neural Networks

• Processing elements analogous to biological neurons.
• Input values (dendrites), output values (axon), and numerical weights (synapse).
• Effective weights are the sum of weights multiplied by their respective input values.

Training Artificial Neural Networks

• Adjusting weights and threshold values.
• Training the network by providing input values and target outputs to recognize specific patterns (e.g., identifying a cat in a picture).

Natural Language Processing (NLP)

• Understanding and speaking in natural language.
• Based on machine learning and large databases of common phrases and sentences.
• Examples: Google Translate, spam filtering, customer call center interactions, digital assistants (Siri, Alexa, Cortana, Google Assistant).

Computer Vision Systems

• Create digital maps of images and recognize those patterns in databases.
• Examples are visual recognition, facial recognition, autonomous vehicles, industrial machines, passport control, and crowd identification.

Robotics

• Design, construction, and operation of machines substituting for humans.
• Applications include factory, office, and home use (e.g., home vacuums, assembling parts, welding, movement).

Intelligent Agents

• Work without direct human interaction.
• Tasks include deleting junk email, finding the cheapest airfare, using limited knowledge bases (e.g., Siri), chatbots, agent-based modeling applications for stock markets, consumer behavior, supply chains, and epidemic predictions.