Unlocking AI's Potential: A Cybernetic-Style Approach
Analysis
Key Takeaways
- •The core idea revolves around compressing action and perception data into manageable 'mechanisms'.
- •It aims to create adaptable AI by recombining learned patterns.
- •The inspiration is drawn from Friston's Active Inference, hinting at a connection to advanced AI models.
“The general idea is to view agent action and perception as part of the same discrete data stream, and model intelligence as compression of sub-segments of this stream into independent "mechanisms" (patterns of action-perception) which can be used for prediction/action and potentially recombined into more general frameworks as the agent learns.”