OCN NI AI Level 3 WK1

• AI
• Higher Education (non-degree)

OCN NI AI Level 3 Week One

Tutor: Michael Allison

Email: [e-mail] 

Course Overview

Key Details:

• Level three qualification 
• Grading: Pass Fail
• Total qualification time: 110 hours
• Guided learning hours: 77 hours 

Course Objectives

The qualification aims to enable learners to understand:

• AI readiness
  
• AI and emerging technologies
  
• Digital transformation
  
• Machine learning and AI
  
• Neural networks and deep learning
  
• AI implications

Course Structure

The qualification consists of seven units, each focusing on different aspects of artificial intelligence, including:

1. Understanding Artificial Intelligence
   
2. Applications of Artificial Intelligence
   
3. Understanding AI Readiness
   
4. AI and Emerging Technologies
   
5. Digital Transformation
   
6. Machine Learning and AI
   
7. Neural Networks and Deep Learning

What is Artificial Intelligence?

What is Artificial Intelligence?

Artificial Intelligence (AI) is a multidisciplinary field of computer science that focuses on creating systems and machines capable of performing tasks that typically require human intelligence. These include but are not limited to:

• Learning
• Reasoning
• Understanding
• Problem solving

 

• Autonomy
  
• Perception
  
• Separating fact from belief

Learning: AI systems can learn from data and improve their performance over time. This includes techniques like machine learning and deep learning.

 

Reasoning: AI systems can apply logical reasoning to solve problems, make decisions, and draw conclusions.

Understanding: AI systems can consider the result of information manipulation

Problem solving: AI can be used to develop algorithms and methods for solving complex problems, often involving large amounts of data or computational resources.

Autonomy: AI systems can operate autonomously, making decisions and taking actions without direct human intervention.

Perception: AI can be equipped with sensors and perception systems to understand and interpret the world, including computer vision, speech recognition, and natural language processing.

Separating fact from belief: AI can determine whether the data is adequately supported by provable sources that can be demonstrated to be consistently valid.

Brief History of Artificial Intelligence

The history of Artificial Intelligence (AI) is marked by key developments, breakthroughs and some setbacks.

• 1940/50s – Birth of AI
  
• 1956 – Dartmouth Workshop
  
• 1950/60s – Early AI Achievements
  

• 1970/80s – AI Winter
  
• 1980/90s – Emergence of Machine Learning
• 2010s/Present - Machine Learning and Data Revolution

1. The Birth of AI (1940s-1950s):

The roots of AI can be traced back to the work of pioneers like Alan Turing, who developed the concept of a universal machine capable of performing any computation.

In 1950, Turing introduced the "Turing Test" as a measure of a machine's ability to exhibit human-like intelligence in natural language conversation.

2. Dartmouth Workshop and the Birth of AI as a Field (1956):

The term "Artificial Intelligence" was coined by John McCarthy, and he organized the Dartmouth Workshop in 1956, which is considered the birth of AI as a formal field.

Researchers at the workshop aimed to develop machines that could simulate human intelligence.

3. Early AI Achievements (1950s-1960s):

In the late 1950s and early 1960s, early AI programs were developed to perform tasks like playing chess (e.g., IBM's "IBM 704" and "IBM 7090" programs) and solving algebra problems.

The "Logic Theorist" by Allen Newell and Herbert Simon proved mathematical theorems.

4. The AI Winter (1970s-1980s):

Progress in AI was slower than expected, leading to a period known as the "AI Winter." Funding for AI research decreased, and some believed AI was overhyped.

Expert systems gained popularity during this time, focusing on rule-based systems that emulated human expertise in narrow domains.

5. Emergence of Machine Learning (1980s-1990s):

Machine learning, a subset of AI, gained prominence with the development of algorithms like neural networks and decision trees.

Backpropagation, a key neural network training algorithm, was invented.

6. Machine Learning and Data Revolution (2010s-Present):

Advances in machine learning, fuelled by the availability of large datasets and powerful computing, led to breakthroughs in areas like natural language processing (NLP) and computer vision.

Deep learning, particularly deep neural networks, revolutionized AI applications, including speech recognition and image classification.

The emergence of AI in applications such as autonomous vehicles, virtual assistants, and recommendation systems has become mainstream.

1940/50s- Birth of AI 

The roots of Artificial Intelligence (AI) can be traced back to the work of pioneers like Alan Turing.

Developed the concept of a universal machine capable of performing any computation

Introduced the ‘Turing Test’

Contributions to Early Computing

Alan Turing - British mathematician, made significant contributions to several fields, including mathematics, computer science, and artificial intelligence.

In 1936, Turing introduced the concept of the "Turing machine," a theoretical mathematical model that laid the foundation for the modern computer.

In 1950, Alan Turing proposed the "Turing Test" to measure a machine's ability to exhibit human-like intelligence in natural language conversation. This test has been influential in the field of artificial intelligence and the study of machine intelligence.

Turing made significant contributions to the development of early computers. He designed the Automatic Computing Engine (ACE), a theoretical blueprint for a stored-program computer, although it was not built during his lifetime.

1956-Dartmouth Workshop

Organised by John McCarthy, Marvin Minksy and two senior scientists of IBM

Term ‘Artificial Intelligence’ came from John McCarthy

Workshop was to develop machines that could simulate human intelligence

The term "Artificial Intelligence" was coined by John McCarthy, and he organized the Dartmouth Workshop in 1956, which is considered the birth of AI as a formal field.

Researchers at the workshop aimed to develop machines that could simulate human intelligence.

1950/60s- Early AI Achievements 

Early AI programs were developed to perform tasks like playing chess and solving algebra problems.

Bernstein Chess Program

Logic Theorist – program to perform automated reasoning

Eliza – natural language processing computer program

In the late 1950s and early 1960s, early AI programs were developed to perform tasks like playing chess (e.g., IBM's "IBM 704" and "IBM 7090" programs) and solving algebra problems.

Bernstein Chess Program – presented under construction at the 1956 Dartmouth workshop

The "Logic Theorist" is a computer program written in 1956 by Allen Newell and Herbert Simon and Cliff Shaw. 1st program deliberately engineered to perform automated reasoning, has been described as ‘the first artificial intelligence’ program

Eliza is an early natural language processing computer program, created to explore communication between humans and machines.

1970/80s AI Winter 

Term AI winter refers to a period of reduced funding/interest

Progress in AI was slow during the 70/80s

AI failed to meet expectations

2010/Present Machine Learning & Data Revolution

Explosion of big data and computing power

Deep learning breakthroughs in image and speech recognition

Rise of AI assistants (Siri, Alexa, Google Assistant)

Self-driving car technology advances

AI in healthcare for diagnosis and drug discovery

Ethical concerns and debates on AI bias and job displacement

What Are Some Positive Aspects of AI?

What Are Some Negative Aspects of AI?

Individual Task! 

Students to produce a research document on the different characteristics of AI applications (Chat GPT, Perplexity) using answers from each piece of software. 

Positive Aspects of Artificial Intelligence

Artificial Intelligence (AI) offers numerous positive aspects and has the potential to bring about significant benefits to society, industries, and individuals.

• Automation and Efficiency
• Personalised Experiences  
• Innovation in Industry
• Enhanced Decision Making 

 

Negative Aspects of Artificial Intelligence

Artificial Intelligence (AI) also has several negative aspects and challenges that need to be considered:

• Job Displacement 
• Bias and Fairness
• Privacy
• Security Risks 
• Legal Challenges

 

https://www.thetimes.com/uk/technology-uk/article/chatgpt-o1-openai-prevents-own-deletion-tmvgbb7ls  

Group Task! 

In groups, brainstorm and discuss the current and potential implications of AI for society and Individuals. 

Impact on employment and job markets

Changes in education and skill requirements

Effects on privacy and data security

Influence on healthcare and medical research

Implications for transportation and urban planning

Consequences for social interactions and relationships

Ethical considerations and decision-making

Group Work Answers

What Went Well Today?/What Did You Learn?

www.neilstoolbox.com

Homework Task! 

Learners should consider current and potential implications for society and individuals.

PowerPoint Task: The Development of AI and Its Implications

Your task is to create a comprehensive PowerPoint presentation on the development of Artificial Intelligence (AI) and its current and potential implications for society and individuals.

Objective:

Explain the evolution of AI technology, its current impact, and potential future effects on various aspects of society and individual lives.

Next Week 

1. Discuss PowerPoints
2. Recap of Week One
3. Explain AI's role in IOT, Robotics and Additive Manufacturing