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This is rather abstract. There is an agent with a goal, a sensor, and an actor. Occasionally, the agent uses a model of the environment. There are rewards and one or more value functions that value the rewards. Maximizing the goal (through acting) based on rewards (through sensing) is reinforcement learning (R.L.). The agent’s policy Read the full article…
Open Leadership in International Conflict
When conflict erupts or threatens to, leadership is tested at its deepest level. Traditional reactions – faster, louder, tougher – too often worsen what they try to solve. In a complex, interconnected world, real strength comes from inner clarity, not outer force. This blog explores Open Leadership as the next evolution: leadership that can face Read the full article…
The Power of Embedding
This is the power of complexity in humans and in present-day Large Language Models (the most visible form of A.I. nowadays). ‘Embedding’ is the transformation of information/knowledge into a format of many subconceptual elements interacting in multifaceted systems that makes this information prone to emerge in novel ways. A multitude of relatively simple (smaller than Read the full article…