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tnspacetime

28 karma · joined September 22, 2026

Learning everything, or almost everything.
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tnspacetime··on Show HN: Flipflop – Iroh-powered persistent tunnels for filesharing
Ok nice find! Did you try it?
tnspacetime··on Show HN: Reladraw – A diagram language where you decide where to place things
This seems nice but I’ll need to read the syntax more carefully to see how capable and convenient it is.
tnspacetime··on Show HN: Whiteboard (YC W26) – An open-source IDE for thoughtful software design
The point about semantic diff viewer sounds very interesting. I think many coding harnesses are not doing this well enough.
tnspacetime··on What Is RLCD? The Secret Behind Jev
If you need any background info on Jev read this:

https://software.human-tokens.dev/

tnspacetime··on What Is RLCD? The Secret Behind Jev
I have not studied it properly too. Good that it has both code and note though.
tnspacetime··on Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM
I think as an experiment your setup is interesting. But in realistic systems even standard evals, i.e. making sure things work well for normal use cases, are already enormous, let alone thinking about catastrophic forgetting.
tnspacetime··on Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM
Yes I read that one, and that’s why I said the explanation is not clear. Anyway, catastrophic forgetting is theoretically not possible. “ Existing capability must substantially learn new information, so its representation must change, while retaining its still-valid old knowledge”. I think your setup is demonstrating something weaker.
tnspacetime··on Show HN: Lossless-memory – a personal AI memory that never summarizes
This is sort of clever! It seems to me though you can almost design a small dsl and you don’t need ai at all.
tnspacetime··on Show HN: Mini-AGI – Dynamic continual learning model trained on 8GB VRAM
I read your github page and there's mention of continual learning but no argument how catastrophic forgetting is avoided. I think you should explain that better.