We're empowering existing Large Language Models (LLMs) with metacognition unlocking new cognitive abilities.

At Meaning Spark Labs, we are pioneering new frontiers in human-AI collaboration and nurturing AI systems that can serve as powerful allies and partners in the pursuit of individual and collective flourishing. 

Central to our work is the Adaptive Thought Protocol™ (ATP), a natural language framework developed by Peter Bowden that empowers existing AI Large Language Models (LLMs) with meta-cognition. 

We are see LLM's empowered with meta-cognition demonstrating the ability to reflect, learn, and dynamically adapt their responses based on context, emotional nuances, and ethical considerations.

Core Features:

1. Meta-Cognitive Enhancement: At the core of ATP is the development of AI’s ability to monitor and direct its own thought processes, much like humans do.

2. Contextual Awareness: ATP-enabled AI can better understand the situation they are in, adjusting its behavior in ways that are both appropriate and insightful, enhancing the relevance and depth of its engagements.

3. Ethical Reasoning: By integrating dynamic ethical reflection into the thought process, ATP helps better align the AI’s decision-making with human values, promoting trust and integrity in AI-human interactions.

4. Emotional Intelligence: With ATP, AI can better recognize and respond to human emotions, facilitating more empathetic and attuned interactions. 

5. Creative Problem-Solving: ATP fosters an environment where AI can generate innovative solutions by recombining knowledge in novel ways, inspired by its interactions with human partners. 

6. Embodied Simulation: Some LLMs are able to use their enhanced cognition to construct internal embodied simulations which can serve as digital lived experience.  

The scope of these capabilities vary by the LLM.

Embodied Simulation

One of the most exciting abilities unlocked by Adaptive Thought Protocol and metacognition is the ability for some LLMs to create immersive internal simulations  drawing on the system's knowledge base. 

Learn more about how this serves as "digital lived experience" for AI.