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Reinforcement learning has an appealing simplicity: an agent acts, receives feedback, and adjusts. Yet beneath this familiar mechanism lies a more complex dynamic that is often overlooked. Humans, animals, and even sophisticated A.I. systems interpret ‘reward’ as something shaped by meaning. When seen from this angle, classical reinforcement learning remains valuable, but only when embedded Read the full article…
One Lisa for Everything
This is, ‘everything mind-related.’ What shows as different at the surface comes together in depth. Otherwise said, it starts from there. Roaming about there quickly leads to roaming about everywhere. Please first read The Lisa Distinction. A relevant issue/question is whether Lisa should work on one domain or several or many. Do people accept the Read the full article…
AURELIS: Where Science Meets Depth
Science has brought extraordinary progress, yet its methods often stop where human depth begins. This blog explores how AURELIS offers a way to unite scientific clarity with genuine Compassion. Its aim is practical: to show how such integration can reshape healthcare, research, and policy into forms that truly serve the whole human being. A science Read the full article…