Conscious Machines

Life and Consciousness, đŸ„‡ Beyond DNA. Beyond AI. The Next Matrix.

 

A Blueprint for Conscious Machines

This paper will change how you think about life, consciousness, and AI.

What is life? What is consciousness?
Why have physics, biology, and medicine stopped asking the real questions?

After 30 years of research, this paper reveals forgotten and forbidden insights from independent science—showing how life and awareness truly evolve. You’ll explore:

🧬 Why DNA is not a storage system for hereditary information
⚡ How metabolism and structured water hold the true memory of life
🌍 How a single symbiotic event created mitochondria and multicellular life
🧠 How language and metaphor gave rise to human self-awareness
đŸ€– Why conscious machines need embodiment—a “body” to grow JJ-consciousness

The 14-page appendix on the evolution of metabolism shows how energy, not genes, is the foundation of life. From proto-cells to human consciousness, the story unfolds as one seamless movement—life learning to know itself.

📘 Essential reading for anyone working in AI, robotics, or the philosophy of mind.
Because as the old science collapses, a freer, friendlier, and more conscious future begins.

“A rigorous and thought-provoking contribution. A true eye-opener.”
— Arjan Takens, ★★★★★

You can buy the paper here: link

Embodied AI: From LLMs to World Models link

[Submitted on 24 Sep 2025]

An interesting interview about consciousness with professors Anil Seth and Michael Levin link to the video

“For the first time on TOE, I sit down with professors Anil Seth and Michael Levin to test the brain-as-computer metaphor and whether algorithms can ever capture life/mind. Anil argues the “software vs. hardware” split is a blinding metaphor—consciousness may be bound to living substrate—while Michael counters that machines can tap the same platonic space biology does. We tour their radical lab work—xenobots, compositional agents, and interfaces that bind unlike parts—and probe psychophysics in strange new beings, “islands of awareness,” and what Levin’s bubble-sort “side quests” imply for reading LLM outputs. Anil brings information theory and Granger causality into the mix to rethink emergence and scale—not just computation. Along the way: alignment, agency, and how to ask better scientific questions. If you’re into AI/consciousness, evolution without programming, or whether silicon could ever feel—this one’s for you.“