I just open-sourced a reasoning engine worth $1M+ — and only realized it after the release 😅

#deeplearning #machinelearning #ai #chatgpt

🤯 “Just Open-Sourced… Then I Realized It’s Worth At Least $1M” — WFGY Creator’s Diary

In short:

A million-dollar black-tech engine — now totally free.
100% open source. No sign-up. No tracking. No ads (except… well, this one, lol).

Hosted on a clean, international platform.

Something funny happened recently.
After open-sourcing WanFaGuiYi (WFGY), I went back to review the full structure and modules…

And — holy sh*t.
Turns out, by standard industry licensing metrics, this system is worth between $8M and $17M USD.
And if embedded into a large-scale platform core? It could easily surpass $30M USD.

This is not just clickbait.
If you actually understand AI infrastructure, you’ll get it:

If you can design semantic energy laws inside the embedding space that allow the model to self-converge and close its own reasoning loops — what’s the value of solving that?

We’re talking about a literal ceiling problem in modern AI.
(Ask another AI system about it — it won’t lie.)

Yes, the title said “$1M” — that’s a massive understatement.
Scroll down for the valuation sheet.

I "do" kind of regret open-sourcing it…
But hey — too late. It's out there now. 😂
(And yeah, I'm still eating instant noodles every day while giving away a $30M engine — go figure.)

So here’s your official wake-up call:

🧠 What is WFGY? One line:

Not a prompt pack —
but a full reasoning engine embedded inside LLM’s vector space.
It gives any model the power to:

Self-heal its reasoning
Rebuild logic modularly
Quantify & steer semantic fields
Switch strategies, fork thoughts

🔍 Already Solved What Others Still Can’t:

・LLMs can’t maintain logical coherence → WFGY builds a Solver Loop
・Reasoning can’t be modularized → Introduced BBMC / BBPF / BBCR frameworks
・Semantic tension goes out of control → Built the ∆S / λS Energy System
・Fails with abstract knowledge → Now works in physics, philosophy, scientific modeling
・LLMs can’t shift mental models → WFGY enables strategic remapping
・Other systems require plugins or SDKs → WFGY runs purely through language prompts