SCAL Field Notes

Personal thoughts, in no particular order.

Design the conditions, never the behaviour.
SCAL is a minefield. 99% of positive results are likely to be illusions. Every apparent success should survive trial by fire before it is treated seriously.
Autopoiesis, ouroboros in silicon.
Always watch your back. It's easy to loop straight back into the engineering trap. Keep reminding yourself. The goal is to distance yourself when working with SCAL, leave minimal fingerprints.
Coupling law, good to know: If renaming the symbols changes the physics, the symbols contain imposed semantics. Avoid trying to engineer it. Find it.
Artificial life wasn't where I expected to end up. My original goal was to design a brain from the bottom up by scaling artificial neurons. Even after reaching billions of neurons on a laptop, the project eventually collapsed under its own complexity. Too many variables, too many moving parts, and a growing realisation that engineering a brain is fundamentally different from understanding one. I stepped back and began exploring artificial life instead. At that point, I knew almost nothing about artificial life as an established field or its history. Google's 2024 opcode work stood out because of its simplicity, but after stripping it down even further I realised I had simply recreated the same engineering trap in a different form. I could keep changing opcodes, settings, update rules and architectural details forever, with no principled way to know which combination, if any, might spark life. I was still searching for a needle in an infinite universe. That was the moment I understood I wasn't looking for a better engineered system. I was looking for a different question. SCAL emerged from that change in perspective.

The science fiction influence came in when I had to admit defeat as a designer. At the neuron stage, I wasn't thinking in terms of substrate passive or substrate active systems. I was simply trying to design a brain and eventually realised that no human was going to design something so complex. The only thing that had ever produced a brain was nature itself. The science fiction part wasn't imagining a new kind of machine. It was the idea that I could stop trying to out-design the universe, create the conditions, step back, and let nature take over from there.
The goal is to get more eyes on SCAL and motivate others to give it a shot. Being the smartest person in the room is a trap. There's a lot of talent out there, opinions matter. One person staring at the same thing for long enough will eventually get trapped inside their own thoughts. Other people bring different assumptions, blind spots and ways through the wall. One mind < many unique minds + perspectives. That will pave the way forward.
Nature is radically simple.
In silicon, all three pillars must be active under one roof. Don't treat them as separate routes, that's a dead end.
Approach SCAL with the cliché "I know that I know nothing" mindset. Everything already exists inside our universe, we do not need to reinvent the wheel. The objective is to understand how to harness it (point 1). Also, think big and ask stupid questions, especially the really stupid ones.
The distinction between artificial and natural life feels fake to me. If we ever create something genuinely alive, it won't be a machine pretending to be life. It will simply be life that got made, which is what all life is in the end. Artificial might tell us how it got here, but not whether the life itself is real.
In my view, "post-substrate" wouldn't mean escaping matter. It would mean discovering that matter was only ever a notation. Carbon wrote it one way, silicon may write it another, and whatever comes after may write it differently again. Each material shapes how life is written, but no material is life itself any more than ink is the sentence.