The Generative AI Frontier: Utopia, Dystopia, or Something In Between?
 
Credits: Translation from textbook tedium to blog bliss by ChatGPT-4o
 
A Life with Generative AI
 
When it comes to the future of AI, opinions are as diverse as they are passionate. Some envision a utopian world where AI transforms lives for the better - think paradise on Earth. Others brace themselves for dystopian outcomes, fearing that AI might take over the world, a reality straight out of a Terminator film. What is the reality? Probably somewhere in between. Below, I have compiled a list of perspectives that capture the wide spectrum of thoughts about living with generative AI. Let's dive into the possibilities and pitfalls.
 
These are the visions that get people excited about a future with AI:
  • AI Assistants for All: AI seamlessly integrated into our lives, managing schedules, personalising healthcare, and providing real-time education.

  • Supercharged Science: AI could accelerate scientific discovery, leading to breakthroughs in medicine, materials science, and clean energy.

  • Enhanced Creativity: AI could collaborate with artists and designers, leading to new forms of artistic expression and innovation.

  • Personalised Learning: AI tutors could tailor education to individual students’ needs, maximising learning potential.

  • Robotic Workforce: Advanced robots could handle dangerous or repetitive tasks, freeing up humans for more creative and strategic work.

On the flip side, here are the concerns that keep people up at night:
  • Fear of Being Replaced: The worry that AI will automate jobs and make human skills obsolete.

  • Misinformation and Deepfakes: Generative AI could be used to create extremely realistic but fake videos or text, making it difficult to distinguish truth from fiction.

  • Loss of Control: As AI becomes more complex, some fear we might not fully understand how it works or control its decision-making.

A Fun Fact on the Side: Curious about what ChatGPT itself thinks of these fears? Here is what it had to say: "These anxieties are valid, but it's important to remember that AI is still under development. Researchers are actively working on ways to ensure AI is used ethically and safely."
 
Where Do We Go from Here?
 
As we move forward, it is clear that generative AI has the potential to reshape our world - for better or worse. Whether we are living in a utopian dream or facing dystopian challenges depends on how we as a society choose to use this transformative technology.
 
 
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My Personal 'Generative AI Artefact Schema'
 
Credits: Translation from textbook tedium to blog bliss by ChatGPT-4o
 
Unpacking the Generative AI Technology Stack: A Journey Through Endless Exploration
 
Building the 'Generative AI Technology Stack' was no small feat. While crafting it, I encountered a wealth of fascinating bits of information - too many, in fact, to fit neatly into the final stack. What did I do with all those extra insights? I decided to dive deeper and conduct a cluster analysis to identify meaningful categories and allocate these stray pieces accordingly.

But, as any researcher will tell you, this was just the beginning of a much larger adventure.
 
The Snowball Effect of Curiosity
 
As I worked to classify these artefacts, I found myself on a continuous quest for deeper understanding. Each discovery opened up new questions:
  • Was this artefact truly unique, or did it belong in an existing category?
  • Was my classification accurate, or was I missing a nuance that needed further research?
This process was like a snowball rolling downhill, growing larger and larger. Just when I thought I had wrapped my head around a concept, ten more items would appear on my to-do list, begging for integration, research, and understanding.
 
Knowing When to Stop
 
Eventually, I had to acknowledge the reality: this is an endless endeavour. The technology and the knowledge around Generative AI evolve so rapidly that achieving 'completion' is an illusion. At some point, I simply had to call it a day and take pride in what I had built.
 
The Result
 
Below, you will find the derived scheme - a snapshot of my explorations. It is not exhaustive, and it never will be, but it is a starting point. My hope is that it serves as a useful framework for understanding the rich and complex world of Generative AI.

Stay curious, stay questioning, and don't be afraid to call it a day - sometimes, progress is about knowing when to pause and share what you have learned.
 
 
 
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My Personal 'Generative AI Technology Stack'
 
Credits: Translation from textbook tedium to blog bliss by ChatGPT-4o
 
Introducing the Generative AI Technology Stack: Making Sense of a Complex World
 
Welcome to the very first post on my blog! Over the past few months, I have been on a fascinating journey, diving deep into the world of Large Language Models (LLMs) and Generative AI. It is an exciting yet challenging field, bursting with potential - and, let's face it, a fair share of confusion.
  • Misinformation: Misleading or oversimplified explanations abound.
  • Misused Terminology: Key concepts are often misunderstood or used inconsistently.
This made it difficult to build a clear mental map of the field. But instead of getting frustrated, I rolled up my sleeves and started piecing things together myself.
 
A Framework Built from Curiosity
 
Bit by bit, I began gathering insights from various sources online. Each fragment of information, no matter how small, contributed to a bigger picture. I evaluated these pieces, challenged assumptions, and asked questions. Slowly but surely, I organised them into something meaningful: my very own Generative AI Technology Stack.

This stack is not just a collection of random facts. It is a structured attempt to synthesise the chaos, providing a framework that helps us understand how the technologies behind LLMs and Generative AI fit together.
 
Why This Matters
 
Generative AI is reshaping industries and redefining what is possible in technology. But to harness its power, we need clarity and shared understanding. My hope is that this stack serves as a helpful guide - not just for me, but for anyone exploring this rapidly evolving space.

So here it is: my Generative AI Technology Stack. It is a living framework, one that I will (hopefully) refine over time as I continue learning. Stay tuned, as there’s much more to come!
 
 
Thanks to the many fellow explorers whose shared knowledge made the creation of this stack possible.
 
 
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Streamlining ABSS Model Design with Conversational AI
 
Credits: Translation from textbook tedium to blog bliss by ChatGPT-4o
 
Unlocking the Potential of Conversational AI
 
In our recent work, we explore how Conversational AI Systems (CAISs) like ChatGPT can support the design of Agent-Based Social Simulation (ABSS) models. By leveraging advanced prompt engineering techniques and the Engineering ABSS framework, we developed a structured script that guides ChatGPT in generating conceptual ABSS models efficiently and with minimal case-specific knowledge. Our proof-of-concept demonstrates this through a case study on adaptive architecture in museums, highlighting the system's ability to assist in model design while reducing the time and expertise traditionally required.
 
Opportunities and Challenges in Harnessing CAISs
 
While our results show promise, we also identified challenges. ChatGPT occasionally produced inaccuracies or strayed off-topic during the enacted discussions. Despite these limitations, its value as a creative and efficient collaborator in ABSS modelling is undeniable. This paper underscores the potential for Conversational AI to accelerate ABSS modelling and invites further exploration into refining and expanding these techniques. Read the full paper on arXiv to learn more about this transformative approach!
 
 
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