About

Theoretical Tinker is the brainchild of a solo innovator
with a passion for biomimicry and diverse theoretical problem-solving methodologies.
Theoretical Tinker is a collection of user-driven problem-solving exercises with LLMs.

This is my own journey of creative and intellectual problem-solving, where I combine natural world inspiration with modern technical concepts.

Carmelyne Thompson
The story of

Carmelyne Thompson

I’m the mind behind Theoretical Tinker, a dedicated enthusiast of the convergence of nature, technology, and innovative problem-solving. With a keen interest in how biomimicry can inform technological advancements, I delve into exploring and sharing unique perspectives on adapting traditional expertise for the digital age. My journey is fueled by a passion for continuous learning and a desire to contribute to meaningful and sustainable solutions.

Current interests are in…

Human-AI Interaction & User Experience

Ethical AI & Responsible Data Usage

AI in Environmental Conservation

AI in Creative Industries (Art, Writing, Design)

Machine Learning & Predictive Analytics

AI in Healthcare & Biotechnology

Natural Language Processing & Communication

Robotics & Automation

AI in Education & Learning

Futuristic AI Technologies & Innovations

12

Books Published

08

Best Selling Books

User-Driven Problem-Solving Exercise with LLMs

With LLMs as my supportive partners, providing feedback and insights

In my problem-solving exercise, the process is uniquely user-driven. I, as the thinker, present the initial problem or challenge, brainstorming and proposing solutions. The LLM’s role is to support my ideas by offering feedback, asking probing questions, and providing relevant information to enrich my thought process. The key here is that my suggestions and solutions are central to this exercise. While LLMs may offer insights, they are intended to enhance and challenge my thinking, not to replace it. The LLMs help refine my concepts, ensuring my creativity and problem-solving skills are at the forefront of the journey.

Problem Solving Exercises

Theoretical Solutions

How Displaced Journalists Can Reinvent the AI Landscape