AIcademia

In the season finale of the AI Academia Podcast, I dive into ChatGPT-4o's new image-generation powers. From GANs to diffusion models and LoRAs, I trace the evolution of AI art—and then showcase how OpenAI’s tool delivers photorealism, crisp text, and creative flexibility. I wrap it with practical ways educators can use it to boost lessons, design eye-catching visuals, and empower student creators.

00:00 Introduction to AI Image Generation in Education

01:23 The Evolution of AI Art: From GANs to Diffusion Models

03:48 Specialist Models and Their Impact on Photography

06:22 The Shift in Employment and Business Applications

07:08 The New Native Image Generation Model

11:31 Strengths and Features of the New Model

15:21 Practical Applications in the Classroom

17:01 Final Thoughts and Future Directions

17:35 Conclusion and Season Wrap-Up

In this episode, I’ll be sharing a conversation I had with Andrew Weeks, a colleague in the music department at the school where I teach. Andy and I chat about a recent cross-departmental project we ran exploring the potential of AI-generated music and its likely impact on the music industry as a whole. It was a warm and thought-provoking conversation and I’m excited to share it with you.

00:00 Introduction to the Episode

00:40 Meet Andrew Weeks: Educator and Musician

02:18 Balancing Teaching and Music Creation

05:54 Adapting to Technological Advances in Music

08:16 AI in Music Education: A New Challenge

12:22 The Ethics and Impact of AI-Generated Music

21:13 The Future of Music in the Age of AI

44:50 Concluding Thoughts and Reflections

51:37 Closing Remarks and Farewell

In this episode, I’ll be looking at the evolving dynamics of human-AI interaction, particularly in educational and workplace settings. I’ll demonstrate ‘Sesame’, a cutting-edge chatbot model which has taken the AI world by storm, and then we’ll explore how it is inevitable that our AI systems will come to look and sound more like us to the point where it might be hard to tell the difference between machine and human interactions.

00:00 Introduction to AI Interaction

00:39 Demonstration of Sesame's Chatbot

05:31 Philosophical Discussion with Maya

08:34 Implications of Advanced AI Interfaces

11:13 Future of AI in Education and Society

16:43 Challenges and Ethical Considerations

28:32 Conclusion and Final Thoughts

In this episode I interview with Bailey Tuddennam, an alumnus of the school where I teach. Bailey, who is now working for a startup focused on designing autonomous kitchen modules for lunar and Mars habitats, discusses his cautious exploration of AI. We delve into the importance of integrating AI literacy into educational curricula, Bailey's journey since leaving Norwich School, his experiences at the University of Glasgow, and his thoughts on the evolving role of AI in various industries. The conversation covers how Bailey uses AI tools in his workflow, the challenges of maintaining academic integrity with AI, and the future of AI in creative and engineering fields.

00:00 Introduction to the Episode

00:51 Meet Bailey Tuddenham

01:24 Bailey's Journey from School to University

03:34 Working on Autonomous Kitchen Modules for Space

06:56 The Role of AI in Bailey's Work

13:15 AI in Education: Challenges and Opportunities

36:21 The Future of AI and Robotics

39:25 Conclusion and Final Though

In this episode I’ll be comparing two of the most recent fronteir LLMS to come to market - Grok 3 and Claude 3.7. I’ll explore the origins and philosophies behind both models, their functionality and I’ll be assessing their suitability for educators. And if you want to know what any of this has to do with the Sith and Jedi - then tune in!

Link to SimTheory: https://simtheory.ai/

00:00 Introduction to AI Academia Podcast

00:43 Grok 3: The Sith Lord of AI

03:22 Claude 3.7: The Jedi Path

05:27 Comparing Costs and Accessibility

09:18 Grok 3: Features and Limitations

15:07 Claude 3.7: Features and Limitations

19:53 Ethical Considerations and Risks

23:49 Practical Advice for Educators

24:53 Conclusion and Final Thoughts

In this episode, I explore the essay’s evolution as an assessment tool and its potential transformation with the advent of AI. Inspired by a LinkedIn post from Paul Matthews and an article on why students cheat by Richard Culatta, I’ll outline a practical 4 step process to help teachers adapt the essay writing process so it remains relevant in the 21st century.

Link to Richard Culatta’s article: https://www.linkedin.com/pulse/real-way-stop-cheating-ai-world-richard-culatta-fogxc?utm_source=share&utm_medium=member_ios&utm_campaign=share_via

00:00 Introduction to the Evolution of the Essay

01:50 Historical Origins of the Essay

03:58 The Modern Academic Essay

04:56 AI and the Future of Essay Writing

06:50 Addressing Academic Integrity in the Age of AI

12:17 Practical Strategies for Adapting Essay Writing

19:07 Conclusion: The Renaissance of the Essay

In this episode of AI Academia, I tackle the nine biggest misconceptions teachers have about artificial intelligence. I’ve made this recording with two types of listeners in mind - teachers who are on the fence and are holding back from exploring AI because they have reservations, and early adopters who might benefit from better understanding the reluctance expressed by some of their colleagues to adopt AI tools. Thanks to all those in the LinkedIn community who made suggestions which have been included in this recording.

00:00 Introduction: Debunking AI Misconceptions in Education

02:20 Misconception 1: AI is Just a Trend

06:02 Misconception 2: AI Will Replace Teachers

07:36 Misconception 3: AI Encourages Cheating

10:20 Misconception 4: Using AI as a Teacher is Cheating

13:14 Misconception 5: AI Requires Advanced Coding Skills

15:06 Misconception 6: No Time to Learn About AI

17:47 Misconception 7: AI Will Make Students Dumber

21:32 Misconception 8: AI Encourages Excessive Screen Time

23:41 Misconception 9: AI Can't Be Trusted

29:23 Conclusion: Recap and Final Thoughts

Link to free catalogue of prompts for teachers: https://prompts-for-teachers-uoszciq.gamma.site/

In this episode I investigate the recent release of ‘deep research’ AI models and evaluate their suitability as tools for educators. I comment on the perceived pros and cons of these ‘agentic multi-step research tools’, summarise the outcome of spending a week trawling various articles and posts about the comparions between the models and describe three examples of reports I have created using Perplexity. Can ‘Deep research’ save teachers time? Is it the equivalent of ‘a PhD in your pocket’? Let’s dive in and find out!

00:00 Introduction to Deep Research AI Models

00:25 Evolution of Conversational AI

01:31 The New Wave: Web-Enabled Agentic Reasoning Models

02:05 Practical Applications in Education

03:36 Major Players in Deep Research AI

04:44 Advantages of Deep Research AI Tools

07:14 Criticisms and Limitations

10:27 Personal Experiences and Use Cases

14:54 Recommendations for Educators

17:10 Conclusion and Final Thoughts

In this episode of AI Academia, I explore how artificial intelligence can be used to foster critical thinking in education by employing a modified version of the Socratic method. I discuss the importance of questioning in learning, drawing on resources such as 'Essential Questions' by Jay Mat Teague and Grant Wiggins, and 'Caitlin's Cookbook' by Steve Bertles. I share insights on how AI can be leveraged to engage students in deeper analysis and dialogue, using prompts to guide back-and-forth exchanges of ideas with the AI. The episode includes a detailed example using Shakespeare's 'The Tempest' to illustrate the process. Finally I issue a challenge so you can put this prompt to work with your own learners!

(Essential Questions): https://tinyurl.com/mrytuyur

(Caitlin’s Cookbook): https://cirl.etoncollege.com/wp-content/uploads/sites/4/2024/01/Issue-1.pdf

The Prompt:

‘You are an expert mentor and questioner.

‘I’m studying [subject] at [level] and want to deepen my understanding of [topic].

Use the questioning method outlined below to help me test and refine my understanding.

The objective is to encourage me to engage in critical thinking, to allow me to arrive at a clearer idea of my point of view and to broaden my understanding of the topic under study’

You should only ask one question at a time and then wait for my response before moving onto the next phase of the question workflow.

Here is the workflow which has 5 phases:

#1 Start with the following open-ended question: ‘stem question’

#2 Once I have responded, give some feedback by critically assessing my answer and then ask a probing question which requires me to provide evidence or specifics to support my claims.

#3 Once I have provided plausible evidence or specifics, give some feedback by critically assessing my answer and then ask a question that encourages comparison or contrast with other relevant aspects of the topic.

#4 Once I have responded, give some feedback by critically assessing my answer and then ask a follow-up question that connects the line of enquiry to the wider topic focus.

#5 Once I have responded, give some feedback by critically assessing my answer and then state that you will now adopt the role of Devil’s Advocate and go on to propose a plausible contrarian position to the one I currently hold. Invite me to consider that position and either refute it or modify my response in the light of this alternative viewpoint.

Finally offer a summary of the whole conversation which precisely and concisely captures the material covered in all 5 phases of the discussion and suggest three new lines of enquiry that might complement the topic under investigation.’

00:00 Introduction to AI in Education

00:27 The Importance of Questioning in Learning

01:26 Key Resources for Enhancing Critical Thinking

02:22 Reflecting on Teaching Practices

06:39 Challenges in Modern Education

07:30 Revisiting Effective Questioning Strategies

09:11 Leveraging AI for Socratic Dialogue

10:18 Implementing AI-Driven Questioning Workflow

15:50 Example: Analyzing Prospero in The Tempest

25:48 Adapting AI Prompts for Various Subjects

26:32 Conclusion and Call to Action

In this week’s episode, I’m exploring the recent release of the Chinese large language model, DeepSeek R1. It’s an accessible overview of what makes this model so impressive, and why it has cost one US company 600 billion dollars in a single day! Along the way, I’ll be jargon-busting so you’ll have a better understanding of terms like ‘inference time compute’, and ‘open source models’.

00:00 Introduction to DeepSeek R1 and Its Impact on Education

00:56 Understanding DeepSeek R1: An Analogy

01:52 The Founding and Development of DeepSeek

02:18 What Makes DeepSeek R1 Unique?

03:57 DeepSeek R1 in Action: A Demonstration

06:23 Controversies and Questions Surrounding DeepSeek

09:44 Open Source vs. Closed Models

17:20 Global Implications and Reactions

24:02 Future Prospects and Final Thoughts