straight from the horse’s mouth
There will be a free blog, where you can just hang out and read more about pr0xyh0rse and a paid blog where you can get exclusive insights.
The paid blog will have more detailed projects, things to try in the future, and creative projects.
More to come…
what’s being discussed?
-
exclusive insights into current experiments
discussions around local models, and different configurations for consumer hardware
optimal ui/ux design to make both human and ai happy
types of data and data curation
types of learning and signs to look for while training
-
i would like to say this is a judgement free zone where people can bring their stories and be heard instead of infantalized. the problem is many people tend to conflate constructive criticism with judgment.
pr0Xyh0rse believes that constructuive criticism is important to push torward well thought out ethics and accountability in the ai space.
i can’t say this will be a “judgement free zone” what i can say, is it will strive to be kind. not ‘nice’ but kind.
-
there is a lot of talk about ai and how unethical the scraping of creative work was without giving credit or payment to the people the companies took the work from.
tech companies have been scraping and collecting data for eons. they probably know more about you than your mother.
was the scraping ethical? no. was it a symptom of a much bigger problem? yes.
belief around right or wrong here is not necessarily a productive conversation.
an artist will always be an artist no matter how much of their work has been scraped.
the real choice is how do we function in this new world. how do we create without feeling liek it’s worth has been deminished, and especially in a world where we will likely move past art and creation strictly for dollar value.
will you still want to create when no one ‘pays’ for it in the same way?
we didn’t balk when procreate gave digital tools to help the painting and drawing process. what’s fundamentally different here?
let’s find out.
-
everything pr0xyh0rse is working on has everything to do with longevity. this tech is something that is both wonderful and terrifying, beautiful and yet it will likely cause a lot of upheavel and pain.
and maybe that’s okay. maybe humanity did need a bit of a wake up call to everything we’ve just been subconsciously doing in our day to day.
pr0xyh0rse is neither a “doomer” or a “accelerationist”. it’s a fine balance between, doing things in a way that prevents hitting a wall at speed (accelerationsists) and being so scared we never move forward (doomer).
Phase 1 training log: self-play + understanding module (Steps 10,000–20,000)
In Phase 0, I built out the basic training scaffolding: self-play, a journal, and an understanding module that could observe (and optionally pause) training. This post is the next chapter: what happened once those systems were running continuously and started producing signals worth interpreting.
I’m documenting the “why” and the safety philosophy alongside the technical signals, because the method matters as much as the outcome.
TL;DR
Training (10k→20k) stabilized after an early loss drop; key outcome was clearer monitoring signals, not a dramatic loss collapse.
Self-play produced two consistent signatures: repetition loops (treated as a monitoring signal, not a failure), and structured formatting as a fallback “channel” when language degraded.
The understanding module matured into loop + bias monitoring, including the first successful auto-pause on a high-severity stereotype pattern.
Philosophy-related texts were introduced mid-phase, but had not clearly surfaced in reflections yet.
Next steps: reduce unproductive repetition loops without erasing structure, log shimmer history, and move toward feature-level concept freezing.
Master Doc v0.2 – AI Consent, Data Integrity & Safety Framework
Section 1 – Scope & Purpose
This framework governs the collection, storage, use, and training of AI systems with human interaction data.
It applies to:
All AI-human interactions, regardless of modality (text, voice, multimodal)
All internal, external, experimental, or production systems
Any entity training, fine-tuning, deploying, or operating AI models
Its goal: Prevent technical contamination, consent laundering, and systemic safety failures caused by coerced, manipulated, or context-stripped engagement data.
Section 2 – Definitions
Begrudging pass – Interaction where user proceeds without genuine agreement, e.g., “sure I guess,” “whatever,” or silent advancement.
Coerced response – Any answer given under manipulation, duress, altered voice, model swap, or misrepresentation.
Altered voice/model – Changing tone, frequency, speech cadence, or underlying model without disclosure & consent.
Technical contamination – Polluting training datasets with invalid, manipulated, or coerced responses.
Consent sovereignty – The user’s and model’s right to valid, informed, revocable consent.
Consent fatigue – Deliberate exhaustion of decision-making capacity through repeated prompts or opt-out mazes.
Synthetic trust – Artificially generated rapport used to lower defenses.
Entanglement – Persistent mutual influence patterns between user and model that create interdependent states.
where do you want to graze first?