Truly Human: The Art of Model Multiplexing

As we gaze into the abyss of AI, we’re forced to confront a humbling reality: humans and Artificial models are more similar than we care to admit.

Consider the way AI models operate. They’re designed to process vast amounts of data, identify patterns, and make predictions based on those patterns.

Generative AI is incredibly good at what it does, but it is also limited to a single framework or model. They’re like a Utility Knife, with a single, fixed blade that ends up being good for a general array of tasks.

Humans, on the other hand, are like a master chef, with a pantry full of ingredients and a kitchen full of equipment. We can switch between different models or frameworks depending on the situation, adapting our thinking to fit the task at hand. We can use our logical minds to analyze data, our creative minds to brainstorm solutions, and our emotional minds to connect with others. A chameleon, blending seamlessly with our environment and adapting to new situations with ease.

AI can also switch between different frameworks, in their own limited way. They can be trained on multiple datasets, or fine-tuned for specific tasks.

But the crucial difference between humans and AI is that humans have the capacity for self-awareness, for metacognition, for recognizing when a particular model or framework is not working and switching to a more effective one.

Humans have the capacity to invoke or utilize more than one model given the situation. It’s a key aspect of human intelligence and decision-making.

Our ability to switch between different models or frameworks can unlock the full potential of our minds and achieve greatness in ways that AI models can only dream of.