Another hike in the forest with wild ideas about quantum mechanics, consciousness, the world as a multi-player game and anti-reductionist mindsets. The first 10 min may be a bit too technical for some ....

Just thinking and talking during another weekend hike.

Spotify has detected a few seconds of copyright-protected music at the end of this old episode. So I had to cut that piece out and upload the episode again (-:

This is an embarrassing episode, recorded spontaneously during a little hiking tour. It has practically zero content and is mostly about my private fears and fancies. Better don't listen to it, or you will be angry that I have wasted your time !

In this episode, I (again) challenge the classical reductionist worldview, arguing that it fails to account for quantum non-locality, context-dependent particle properties, and the emergence of meaning. I suggest that higher-level phenomena — like intention and top-down causality — are not mere illusions, but play a real role in shaping the world. I propose that quantum 'randomness' could allow for creative influences, possibly even from a higher consciousness, to guide evolution and complex organization.

I have written about some of these ideas in my blog: https://www.tumblr.com/cm-shorts

Why are most of you satisfied with consensus reality ?

From now on, in between the regular 'CM Memes' episodes, I will publish free-style improvised recordings, called 'CM Jam'.

In this episode, I explore the concept of "Trained Creators" - systems like AI, humans, or nature that generate novel, functional patterns by leveraging deep learned correlations. Building on ideas from episode #61, I discuss how these systems, after training, act as probabilistic generative models, creating outputs that combine past knowledge in surprising and innovative ways. Creativity, I argue, exists on a spectrum, from small variations to groundbreaking ideas, and emerges through hierarchical processes within these models.

Using examples from physics, jazz improvisation, and AI like ChatGPT, I show how compressing known data into generative systems opens up vast possibilities, often surprising even their creators. This dynamic, where humans feed models and draw insights from them, forms a feedback loop that could drive a new era of collective innovation.