Artificial Intelligence Overview

Artificial Intelligence (AI)

• AI is a branch of computer science aiming to create computer systems that mimic human intelligence.
• Early concepts of intelligent machines date back to ancient times.
• Modern AI research focuses on mimicking human thought processes, understanding speech, and surpassing human capabilities in fields like chess.

AI History

• Turing's Test: A test proposed by Alan Turing to evaluate machine intelligence.
• The Imitation Game (Turing's Test): A test where a judge tries to determine if a human or a machine is communicating. The computer passes the test if the judge cannot reliably distinguish between the two.
• The test involves modifying the game from two contestants to one (human or computer), and if the judge cannot distinguish, the computer passes.

AI Applications

• Game Playing: Programming computers to play strategy games like chess (Deep Blue, IBM's chess-playing computer, defeated Gary Kasparov).
• Speech Recognition: Enabling computers to understand and respond to human speech; it has practical applications for limited tasks but was not fully realised as it was predicted.
• Natural Language Understanding: Developing systems capable of understanding human language; still under development, with potential for natural interactions with computers.
• Computer Vision: Enabling computers to "see" and understand images and scenes; used for image and object recognition, and is progressing, with limitations in the 3D representation of data compared to humans.
• Expert Systems: Programming computers to make decisions in specific fields (e.g., medical diagnosis); not as widely adopted as hoped for.
• Heuristic Classification: One type of expert system; used for tasks like evaluating credit card purchases.

AI Websites

• Multiple AI-powered websites are available for various tasks like searching, quiz creation, presentation generation, video lessons, audio conversion, mind mapping, and homework assistance.

The Rise of AI: Advancements and Adoption

• Rapid Progress: AI capabilities are evolving rapidly due to breakthroughs in machine learning, natural language processing, and computer vision.
• Widespread Adoption: AI is integrated into many everyday technologies, like virtual assistants and autonomous vehicles.
• Transformative Potential: AI can revolutionize industries, enhance decision-making, and address global challenges.

Machine Learning

• Data Acquisition: Gathering and preparing large datasets for training AI models.
• Model Training: Using AI algorithms to enable machines to learn from experience.
• Deployment: Integrating trained AI models into applications to solve real-world problems.

Natural Language Processing (NLP)

• Language Understanding: Enabling AI systems to interpret human language context.
• Multilingual Capabilities: Supporting diverse languages and cultural nuances.
• Conversational Abilities: Developing AI chatbots and virtual assistants.
• Personalized Interactions: Tailoring responses to individual user needs and preferences.

Computer Vision

• Image Recognition: Identifying and classifying objects and people in images.
• Video Analysis: Understanding video content context.
• Augmented Reality (AR): Combining computer vision with AR to overlay digital information.
• Medical Imaging: Assisting medical professionals with diagnoses.

Autonomous Systems

• Perception: Enabling autonomous systems to interpret their surroundings.
• Decision Making: Developing AI algorithms to make decisions and navigate complex environments.
• Control: Precisely operating vehicles, robots, and automated machinery.

Ethical Considerations

• Bias and Fairness: Addressing biases in AI systems.
• Privacy and Security: Protecting user data, implementing robust security measures.
• Transparency and Accountability: Establishing clear decision-making processes and mechanisms.
• Human-AI Interaction: Ensuring AI technologies enhance human capabilities, not replace them.

AI and the Future of Work

• Automation and Augmentation: AI enhancing productivity, allowing humans to focus on strategic tasks.
• Workforce Transformation: Preparing the workforce for changing job requirements through reskilling and upskilling.
• New Job Creation: Generating new job roles and industries centered around AI capabilities.

Data Privacy and Security in the Age of AI

• Data Collection: Ensuring transparency, obtaining informed consent.
• Data Storage: Implementing robust security measures against breaches.
• Data Usage: Establishing clear guidelines and policies for ethical data analysis.

The Road Ahead

• Continuous Innovation: Pushing the boundaries of what's possible.
• Persisting Challenges: Addressing bias, privacy, and ethical concerns.
• Collaborative Approach: Working together among technologists, policymakers, and ethicists.

E-Commerce

• Electronic Commerce (EC): A new model of selling and merchandising that uses electronic tools for purchase decisions.
• Key Processes: Enabling customers to access products, make selections, buy securely, and receive purchases.
• Different Perspectives on EC: Communication, business, service, and online.
• Historical Development: Growing from EFT to EDI, Internet use, and online applications.

E-Commerce Benefits

• Merchants: Expanded marketplace, lower costs, reduced time-to-market, improved customer service, efficiency, flexibility.
• Consumers: 24/7 availability, wider selection, comparative shopping, lower costs, faster information access.

E-Commerce Disadvantages

• High development costs, security and privacy concerns, lack of trust, lack of tactile experience.

Major Types of E-Commerce

• B2C (Business-to-Consumer): Businesses selling directly to consumers.
  • Benefits for Businesses: Lower costs, new opportunities, better data, added services, support, lower costs.
  • Benefits for Consumers: Convenience, information, comparison, potentially lower prices, personalized service.
• B2B (Business-to-Business): Businesses buying and selling to other businesses.
  • Advantages: Reduced costs (purchasing, sales, marketing). Efficient inventory, logistics and lower cycle times, improved customer support.
• C2C (Consumer-to-Consumer): Consumers selling directly to other consumers. (e.g., classified ads, auctions)
• P2P (Peer-to-Peer): Direct user-to-user file/resource sharing.

Mobile Commerce

• Uses wireless devices for transactions.
• Popular in Japan and Europe.
• Employing technologies like 3G, Wi-Fi, and Bluetooth.

Web Technology

• Internet: A global network of computer networks carrying data; includes email, video conferencing, among others, and web pages.
• Intranet: A private network within an organization to share company information.
• Extranet: A private network extending to external businesses or partners for secure collaboration
• Web Browsers: Applications accessing and displaying web pages. (e.g., Microsoft Internet Explorer, Mozilla Firefox).
• Web Pages: HTML documents displayed by browsers.
• Web Sites: Collections of connected web pages.
• HTTP and HTML: Key protocols for Web communications and page formatting.
• Hypertext: Links between documents.
• URL: Unique address for a website page.
• Web Servers: Host web pages.

Web Services

• Portals: Combining various internet services like search engines, news, and shopping.
• News sites: Provide current events and articles.
• Informational sites: Offer factual information.
• Business/marketing sites: Promote and sell products/services.
• Educational sites: Offer online learning.
• Entertainment sites: Offer entertainment content.
• Advocacy sites: Convey a particular cause or opinion.
• Blogs: Regularly updated journals with personal opinions.
• Search Engines: Find website information based on keywords or phrases (e.g., Google, Yahoo).
• Search algorithms: Rank pages by relevance (e.g., PageRank).