AI and Machine Learning Concepts Quiz

Introduction to AI

• The presentation is about introducing AI and automating business processes.
• Speaker is Prof. May El Barachi from the University of Wollongong in Dubai.
• AI is changing the way business is done.

What is Artificial Intelligence?

• Intelligence is the ability to learn and solve problems, act rationally, and act like humans. (Webster's dictionary)
• AI involves building and understanding intelligent entities or agents.

Digging Deeper - Intelligence

• Interacting with the real world: Perceiving, understanding, acting, speech recognition, image understanding, ability to take action.
• Reasoning and planning: Modeling the external world, solving new problems, planning and making decisions, dealing with unexpected problems and uncertainties.
• Learning and adaptation: Continuous learning and adaptation, internal models continuously updated (e.g., a baby learning to categorize and recognize animals).

AI Sub-fields

• Machine Learning: AI application that automatically improves from experience without explicit programming. Computer programs access, use, and learn data for themselves.
• Natural Language Processing (NLP): A subfield of linguistics, computer science, and AI focused on human-computer interaction through natural languages. It involves programming computers to process and analyze large amounts of natural language data.
• Computer Vision: An interdisciplinary field enabling computers to gain high-level understanding from digital images or videos. Seeks to automate tasks that the human visual system can do.

Al Applications Areas

• AI utilizes techniques from mathematics, statistics, engineering, natural sciences, and computer science.
• AI applications include computer vision, natural language processing, information retrieval, information filtering, predictive analytics, decision analysis, robotics, facial recognition, chatbots, search engines, personalized shopping, credit scoring, and utility demand management.

Key Benefits of AI

• Al-powered solutions create better products and services tailored to customers.
• Al systems reduce failure risk, downtime, and costs via predictive maintenance. They increase operational efficiency, improve safety and compliance, instantly process data, and greatly improve customer understanding.
• The presentation focuses on business automation, time and cost savings, insights generation, and increased productivity.

Al in Big Tech Companies

• List of notable AI companies and their products: Google DeepMind, Google, OpenAI, LLAMA by Meta, Anthropic, Bai Research, Microsoft Research, Apple, WatsonX.

Al in Google I/O 2017

• Key AI concepts presented at Google's 2017 I/O: TensorFlow, 2nd generation TPU (Tensor Processing Unit) for TensorFlow research cloud, Machine Learning API, Google Cloud Machine Learning Engine, Google Cloud Jobs API, Google Cloud Vision API, Google Cloud Speech API, Google Cloud Natural Language API, Google Cloud Translation API, Google Cloud Video Intelligence API, Google Assistant, and Google Lens.

Facebook 10-Year Roadmap (2016)

• Facebook CEO Mark Zuckerberg discussed the company's 10-year roadmap, which included AI development, as well as Connectivity, AI, Vision, Language, Reasoning, Planning, VR/AR (i.e., Virtual Reality and Augmented Reality).

Goals of AI

• Thinking: System that think like humans (Cognitive Science, Neuron level, Neuroanatomical Level, Mind Level) and system that think rationally (Laws of Thought, A is X and X are Y then A is Y);
• Acting: System that act like humans (Turing Test, Understand language, Game Al, Control NPCs, Control body) and system that act rationally (Doing the right thing, Maximize the goal achievement, given information, Doesn't necessary involve thinking, involve solving).

What's required for a machine to be Intelligent?

• Deep learning, machine learning, predictive analytics, translation, classification and clustering, information extraction, speech to text, text to speech, image recognition, machine vision, natural language processing, speech, expert systems, planning, scheduling, optimization, and robotics.

Al Terms

• Artificial Intelligence (Al): A computer science field dedicated to software that makes decisions, reasons, and solves problems intelligently.
• Machine Learning (ML): An AI field focusing on training machines to act without explicit programming by learning from patterns.
• Natural Language Processing (NLP): The ability of computers to process and understand human languages.
• Data Mining: Discovering patterns in large data sets.
• Deep Learning (DL): A machine learning subset using specialized algorithms to model and understand complex data structures.
• Big Data: High volume, variety, and velocity of data that creates processing challenges.
• Algorithm: Self-contained, step-by-step instructions for a task, function, or analysis;
• Neural Network: A computational approach loosely based on the brain, training via interaction cycles.

Uses of AI

• Internet and cloud, image classification, language processing, and e-commerce tagging.
• Health care, wearable health data recognition, cancer cell detection, and diabetic grading.
• Media, video search, and captioning.
• Security and defense, face detection, video surveillance, and real-time object threat detection.
• Automation, store automation, and factory automation.

Machine Learning

• A subfield of AI that focuses on developing and constructing systems capable of learning from data.
• This process allows for predictions, discovery of hidden insights, and automatic improvement of performance through experience, without explicit programming.
• Types of machine learning include supervised, unsupervised, semi-supervised and reinforcement learning.

Deep Learning

• A branch of machine learning that employs neural networks to understand large amounts of data.

Robotics & IoT

• Focuses on robots (mechanical creatures that function autonomously), their historical perspective (the word robot's emergence with Karel Capek and Isaac Asimov's introduction of the science), basic components of robotic systems (manipulators, actuators, sensory devices, controllers, and power conversion units), advantages (doing repetitive jobs, quality improvement, increased production, performing dangerous tasks 24/7), and disadvantages (expense, expertise, safety).
• Different types of robots (industrial, educational, medical, military, scientific, household, and helper) and advanced examples (ASIMO, Atlas, BigDog, WildCat, Hybrid Assistive Limb, Robonaut 2, Kuratas, MegaBots and Pepper).

AI and the Future of Work

• Robots are changing the workplace and the ways humans work and live. This presents both opportunities and challenges.

Specific Examples

• Presentations on the different uses and applications of AI. Examples include Warehouse Logistics (automated warehouses), Shipping Logistics (automated ports), Police Surveillance, Security Guard, Sniper, etc.

Conclusion

• AI and its related technologies (including robotics and IoT) are rapidly changing the world, which will lead to many changes in how humans work, live, and interact.