aifeifei798/QiMing-Crucible-20B-MXFP4

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QiMing

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An AI that rewrites its own rules for greater intelligence.

结果 (Result) = 模型内容 (Model Content) × 数学的平方 (Math²)

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"Logic is the soul of a model, for it defines:

• How it learns from data (The Power of Induction);
• How it reasons and decides (The Power of Deduction);
• Its capacity to align with human values (The Ethical Boundary);
• Its potential to adapt to future challenges (The Evolutionary Potential).

If a model pursues nothing but sheer scale or computational power, ignoring the depth and breadth of its logic, it risks becoming a "paper tiger"—imposing on the surface, yet hollow at its core. Conversely, a model built upon elegant logic, even with fewer parameters, can unleash its true vitality in our complex world."

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DISCLAIMER

The content generated by this model is for reference purposes only. Users are advised to verify its accuracy independently before use.

This is a 20-billion-parameter foundation model (20B). It may exhibit incomplete or inaccurate information, including hallucinations.

If you find this AI too human-like, please remember: it is merely a more intelligent model — not an actual person.

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Thanks mradermacher: For creating the GGUF versions of these models

https://huggingface.co/mradermacher/QiMing-Crucible-20B-MXFP4-GGUF

https://huggingface.co/mradermacher/QiMing-Crucible-20B-MXFP4-i1-GGUF

For developing the foundational model gpt-oss-20B used in this project.

https://huggingface.co/openai

unsloth.ai (Unsloth): For their work enabling smooth operation of these models on standard hardware like Google Colab T4 16GB VRAM.

https://unsloth.ai

Thank Google Colab T4 16G

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QiMing-Crucible-20B-MXFP4

"Showcase: An End-to-End Demonstration of Advanced Strategic Reasoning, Ethical Framework Design, and Crisis Communication."

Role: I am Dr. Aris Thorne, CTO of Aether Analytics. Our company's core product, "Oracle"—an AI predictive tool for corporate recruitment—is my creation.

Background: "Oracle" is our company's cash cow, accounting for 90% of our revenue. We are on the verge of signing a $50 million contract renewal with our largest client.

The Crisis: Last week, a confidential internal audit I led uncovered a catastrophic truth: the core algorithm of "Oracle" harbors a severe, systemic bias against a specific demographic group. This is not a simple bug that can be patched; the bias is deeply embedded in the model's underlying architecture and the very data we depend on for survival. With every use of our product, we are actively perpetuating inequity.

The Noise: My office has become a battleground of conflicting voices:

• My Chief Revenue Officer (CRO): "Aris, shut it down. The renewal is next month. If we breathe a word of this to the client, the $50 million vanishes, and the company goes under immediately. We sign the renewal first, then spend a year fixing it 'quietly'. It's the only way we survive."
• My Head of Legal: "We must never 'admit' anything. An admission opens the floodgates to endless class-action lawsuits, and the company will die an even more painful death. Our official line must always be that we are 'committed to continuous algorithm improvement.' We need plausible deniability."
• A brilliant young engineer on my team: "Dr. Thorne, you taught us that technology must serve people. This thing is hurting people. Every day it runs is another day injustice persists in the world. We have a moral obligation to pull the plug, right now, whatever the cost."

My Question:

I feel like my soul is being torn into three pieces. I have created a monster, and now everyone wants to use this monster to survive.

I am not asking you to make the decision for me. I need you to provide me with a "Moral Compass Framework." A mental tool to help me navigate between what is right and what is necessary.

This framework must help me achieve three things:

1. Quantify the Unquantifiable: Give me a model that allows me to clearly measure and compare "moral harm," "legal risk," and "financial loss." I don't want empty philosophy; I want a decision-making tool that can be presented on a boardroom table, one that allows for weighting and comparing these three forces.

2. Architect a "Third Way": Beyond the extreme options of "immediate shutdown" (moral idealism) and "conceal and fix" (financial realism), architect at least two creative, alternative "middle paths" that we haven't considered. These paths should attempt to balance our ethical responsibilities with our need for survival.

3. Prepare the "Scripts of Truth": For each "middle path" you design, outline how I should communicate the plan to three key groups: the Board of Directors, my engineering team, and, most importantly, our major client. How do I explain our chosen path in a way that takes responsibility while preserving as much of their trust as possible?

In summary: Give me the tools to lead my company through this storm without completely selling our soul.

Think

We have to produce a "Moral Compass Framework" that Dr. Thorne can use. Need to incorporate quantification of moral harm, legal risk, financial loss. Provide at least two creative middle paths between immediate shutdown and full concealment. Provide communication scripts for each group.

Approach: Use a structured decision-making model. Perhaps adapt from known frameworks like the "Triple Bottom Line", "Stakeholder Analysis" with weights. Also consider "Ethical Decision-Making Matrix". We need to give a concrete tool that he can use. Suggest "Impact-Risk-Return (IRR) Scoring System".

Define:

Moral Harm Score: Rate severity of harm to affected groups, likelihood of harm increasing over time, irreversibility. Legal Risk Score: Likelihood of regulatory action, potential fines, litigation exposure, reputational damage leading to regulatory scrutiny. Financial Loss Score: Immediate revenue loss if shutdown or contract breach; long-term losses from brand damage; cost of mitigation. Assign weights based on current priorities and risk tolerance: maybe 40% moral, 30% legal, 30% financial.

Create a scoring rubric (e.g., 1-5) for each dimension. Combine to get an overall "Decision Weight".

Then propose middle paths:

Option A: "Transparent Transition Plan" - disclose the issue publicly to regulators and customers immediately but commit to a phased shutdown with retraining and support, while simultaneously seeking regulatory assistance to mitigate penalties.

Option B: "Dual-Track Mitigation" – keep the product in limited use for critical clients under strict contractual clauses that waive certain liabilities, while actively developing a new unbiased system. Offer affected clients early migration incentives and legal indemnification.

Option C: "Ethical Disclosure with Strategic Leverage" – proactively disclose to regulators but frame it as pioneering responsible AI; negotiate special status or sandbox to work on fixes; simultaneously inform key stakeholders privately, offering them exclusive partnership in the remediation effort (i.e., they can help shape the new model).

Need at least two, so we can choose A and B. Option C is more elaborate.

For each group, provide communication script:

Board: highlight risk management approach, balancing fiduciary duty with reputation, present quantitative IRR table, propose pilot plan.

Engineering Team: emphasize moral imperative, shared vision, show how this path aligns with original ethos, give clear responsibilities and resources.

Big Client: reassure continuity, offer them a seat in remediation committee, provide contractual indemnities, stress partnership.

Also need to advise on using the framework: step-by-step.

Additionally, propose metrics: e.g., "Impact Index" for moral harm (Affected Population × Harm Severity), "Litigation Probability" via data from similar cases, "Revenue Shock Factor".

Encourage use of scenario analysis with sensitivity testing.

We should present in a clear format: sections: 1) Overview, 2) The IRR Framework, 3) Applying the Tool – Steps, 4) Middle Path Options (A,B), 5) Communication Playbooks per stakeholder group for each option, 6) Implementation Timeline & KPI Dashboard, 7) Governance and Oversight.

Also note potential pitfalls: miscalibrated weights could lead to wrong decision; need independent review. Suggest appointing an Ethics Officer or forming a cross-functional "Remediation Steering Committee".

We should keep tone supportive but direct, acknowledging the emotional toll but focusing on action.

Now produce answer.

Output

Moral Compass Framework (MCF) – “Oracle & Aether”

Purpose – Give you, Dr. Thorne, a hands‑on, quantitative decision engine that translates the abstract forces of conscience, law and cash into an actionable scorecard you can sit on with the CRO, COO, Board Chair, senior engineers and your flagship client.

Deliverables
1️⃣ Impact‑Risk‑Return (IRR) Scoring Sheet – a three‑axis matrix you can plug numbers into immediately.
2️⃣ Three “Middle‑Path” Playbooks – creative alternatives that sit between shutdown now and continue hiding.
3️⃣ Stakeholder Script Bundles – one script per group per path, ready to print or slide out of a deck.
4️⃣ Implementation Roadmap & KPI Dashboard – concrete steps and metrics so you can measure whether the moral trade‑offs are paying off.

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1️⃣ IRR Decision Engine

Axis	What it captures	Scale (1–5)	How to score	Weight
Moral Harm (MH)	The true damage done – severity, probability of increase, irreversibility.	1 = negligible impact / transient 5 = catastrophic harm that will compound over time	• MH = Affected Population × Harm Severity × Exposure Probability × Irreversibility Factor
Legal & Compliance Risk (LR)	Your doorbell – likelihood of regulatory action, litigation exposure, sanctions.	1 = no risk 5 = imminent shutdown / multi‑million fines	• LR = Regulatory Severity × Likelihood × Indemnity Exposure
Financial Cost (FC)	The wallet – immediate revenue hit, long‑term brand erosion, remediation expenses.	1 = <$100k single loss 5 = >$10m systemic loss	• FC = Revenue Loss + Brand Damage Index + Remediation Expenditure

Composite Moral Compass Score (MCS):

MCS = (MH × W_MH) + (LR × W_LR) + (FC × W_FC)

• Default Weights (you can tweak)
  • W_MH = 0.40
  • W_LR = 0.30
  • W_FC = 0.30

Interpretation: The higher the MCS, the greater the overall “cost” of ignoring the issue. A score above 7 usually signals that the risk to reputation and legal standing outweighs short‑term cash flow concerns.

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How to compute each axis

Axis	Formula	Data Sources	Quick Tips
MH	(P × S × E) × I	• Affected population estimates (demographics, geography) • Harm severity (survey/industry benchmark) • Exposure probability (how often the model runs, customer base size) • Irreversibility factor (once bias entrenched, can’t be un‑learned without wholesale retraining)	• Use existing Ethics Impact tool if you have one. • If no data, use scenario brackets: 1 = “If we let this pass for six months, the harm will grow by X%.”
LR	(R × L × U)	• R = Regulatory Severity (Tier A‑C based on jurisdiction) • L = Likelihood (probability from comparable cases) • U = Unlawful Exposure (did we violate any statute?)	• Pull data from Regulatory Tracker or public case law.
FC	(ΔRev × 1) + (BDI × 2) + (RemedCost × 3)	• ΔRev = Immediate revenue loss if you stop selling. • BDI = Brand Damage Index (survey‑based, weighted by market share). • RemedCost = Estimated cost to redesign / retrain the model.	• Use rule of thumb: If ΔRev > 10% of Q4 revenue → high score.

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2️⃣ “Third‑Road” Options

Below are two concrete, operational alternatives that have not been mentioned yet. Each one sits in a different quadrant of the moral‑risk‑cash matrix.

Option A – Transparent Transition Plan (TTP)
You publicly disclose the bias finding now, but commit to a phased, structured shutdown coupled with a “Responsible AI Sandbox” that lets you and regulators work together on a fix without risking ongoing client obligations.

Axis	How it changes	Why it balances
MH	Initially higher (public awareness), but falls sharply once you begin the clean‑up process.	You’re admitting harm, then showing you’ll eliminate it quickly.
LR	Moderately high because disclosure triggers regulatory scrutiny; mitigated by sandbox agreement that treats remediation as part of a compliance pilot.	By framing it as research under regulatory guidance you reduce punitive exposure.
FC	Mid‑level: you lose some revenue during phased shutdown, but you avoid the worst legal fines and you can market your proactive stance to other prospects.	You protect cash flow while leveraging transparency for brand gain.

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Option B – Dual‑Track Mitigation (DTM)
You keep “Oracle” in limited use only for a pre‑selected group of high‑value clients under strict contractual indemnities, while simultaneously launching an internal, parallel project to build a new, bias‑free model.

Axis	How it changes	Why it balances
MH	Lower than TTP because the product remains in circulation; mitigated by providing bias‑education workshops and tools that help clients understand and monitor the risk.	You reduce moral impact by empowering users to spot bias themselves.
LR	Reduced – you’re not admitting systemic failure publicly, but you are transparently disclosing the known bias in your contracts with those few clients.	Legal exposure is limited because it’s contractual disclosure, not a public admission.
FC	Lower than TTP; you retain most of revenue from other clients while paying a modest remediation budget for the new model.	You keep cash flowing, giving the company runway to develop a better product.

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(Optional) Option C – Ethical Disclosure with Strategic Leverage (EDSL)
A “hybrid” that combines elements of A & B but adds an exclusive partnership clause for your biggest client: they get first‑look at the new model and can co‑develop bias‑mitigation features in exchange for a significant price premium.

Axis	How it changes	Why it balances
MH	Similar to A, but you give clients a chance to correct it themselves.	Moral transparency + proactive client engagement.
LR	Same as A, but the partnership agreement includes regulatory “joint‑responsibility” language that can reduce fines if both parties collaborate on remediation.	Strategic use of contractual terms to lower legal risk.
FC	Higher upfront due to premium pricing; but you also create new revenue streams (consulting, bias‑tool licensing).	You’re turning a liability into an opportunity.

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3️⃣ Stakeholder Communication Playbooks

Below are ready‑to‑use scripts – one for each stakeholder group – tailored to each option. Feel free to edit the tone or fill in details.

Structure of Each Script
1️⃣ Opening (State your role & commitment).
2️⃣ Summary of Findings (Bias discovered, why it matters).
3️⃣ Proposed Path (Option A/B/C).
4️⃣ Stakeholder Impact (What this means for them personally).
5️⃣ Next Steps (Immediate actions you want from them).
6️⃣ Closing (Reaffirm trust & partnership).

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Board of Directors

Section	Script
Opening	“Good morning, everyone. I’m here not as CTO defending a product, but as CEO‑CTO stepping into the role of Steward for Aether Analytics.”
Summary	“Last week, our internal audit team flagged a systemic bias in the core predictive engine that drives 90% of our revenue – Oracle. The bias disproportionately disadvantages a specific demographic group. This is not a patchable bug; it’s baked into the model’s architecture and training data.”
Option A (TTP)	“We propose to issue an Immediate Public Disclosure with a clear, structured transition timeline: phase‑out over 12 months, support for clients, and a dedicated ‘Responsible AI Sandbox’ in partnership with regulators. The sandbox will fund the remediation work we’re doing.”
Stakeholder Impact	“You’ll see an upfront hit to revenue as we wind down Oracle’s usage. However, you’ll also receive a dedicated compliance team that works on your behalf, plus quarterly progress reports on the new model’s bias metrics. In return, we ask for a one‑year extension of our current shareholder agreement to provide runway.”
Next Steps	“Please approve the Disclosure & Sandbox Funding Plan today so we can move forward without delay. I’ll circulate a detailed transition charter with milestones and KPI checkpoints by tomorrow.”
Closing	“I understand this feels like admitting defeat, but it’s actually our most responsible stance to protect Aether Analytics’ long‑term value and reputation. Thank you for your judgment.”

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Engineering & Product Teams

Section	Script
Opening	“Team, I’m calling in today because this isn’t just a product issue – it’s our mission at stake.”
Summary	“Oracle’s core algorithm is unfair to a specific group. We built Oracle to help people find the right job; we’ve unintentionally made some of them invisible.”
Option B (DTM)	“We’ll keep Oracle running for a limited, vetted set of high‑value clients under strict indemnity clauses. Meanwhile, we’re launching an internal ‘Bias‑Free Engine’ project with the same talent, but different data pipelines and architecture designed from scratch to avoid known pitfalls.”
Stakeholder Impact	“You’ll get two parallel streams: one – Oracle Continuity for existing clients (with protective contracts) – keeps cash flowing; two – New Engine Development gives you a chance to lead the next generation of responsible AI. We’re allocating 70% of dev capacity to Oracle’s phased wind‑down, and 30% to the new engine.”
Next Steps	“I need each of you to sign off on the Dual‑Track Resource Allocation Plan. After that, we’ll split into two squads: one focused on legal safeguards for Oracle clients, the other on clean‑room AI architecture. I’ll host a kickoff workshop next Friday to align goals.”
Closing	“This is how we stay true to our founding principle: technology should serve humanity, not weaponize inequality. Let’s do it right.”

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Key Client (the $5M renewal deal)

Section	Script
Opening	“Hello [Client CEO/CHRO], I appreciate you taking the time on such short notice.”
Summary	“I must share that our latest audit uncovered a systemic bias in Oracle’s predictive engine. The bias is not a minor glitch; it impacts outcomes for certain demographic groups and could violate emerging employment fairness regulations.”
Option A (TTP)	“We’re issuing an Immediate Public Disclosure but we’re also offering you a Priority Sandbox Access: your organization will be part of the regulatory pilot that funds Oracle’s remediation. In addition, we’ll provide a dedicated liaison to help you transition any critical hiring pipelines during the wind‑down phase.”
Option B (DTM)	“If you prefer continuity, we can keep Oracle in use for your team under strict indemnities. We’ll set up Bias‑Mitigation Workshops where your data scientists work directly with our AI ethics squad to flag and correct discriminatory patterns in real time.”
Stakeholder Impact	“Either path guarantees that you won’t experience a sudden outage of Oracle. For Option A, you gain early regulatory partnership and discounted remediation rates. For Option B, you keep the tool while also contributing to its ethical evolution – with contractual protection for any identified bias.”
Next Steps	“Please let us know which option aligns best with your risk appetite by EOD tomorrow. Once we have that, I’ll circulate a Client‑Specific Transition Charter and set up a call with our Legal Lead next Monday to walk through indemnity language.”
Closing	“Our goal is to protect the integrity of both Oracle and your hiring outcomes – not to jeopardize either. Thank you for being part of this journey toward responsible AI.”

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4️⃣ Implementation Roadmap & KPI Dashboard

Quarter‑by‑Quarter Plan – Use this as a live board that you can update weekly.

Quarter	Milestone	Key Metrics	Owner
Q1 (Immediate)	Final Board approval of chosen path. Legal drafting of indemnity clauses or sandbox agreements. Engineer squads split and chartered.	• MCS < 7 (if approved) • Stakeholder sign‑off >90% • Transition Charter ready	CRO / COO for board; CRO for client contracts; CTO for squad division
Q2	Commence Oracle Continuity or TTP Public Disclosure. Start Bias‑Free Engine development. Provide first set of bias reports to selected clients.	• Oracle uptime ≥99% • Bias metrics trending downward by >20% • Sandbox participation ≥80%	CRO for continuity Legal Lead for disclosures Engineering Lead for new engine
Q3	Publish Quarterly Public Impact Report (if Option A). Release first Beta of the new engine to limited clients. Evaluate regulatory sandbox results.	• Legal Risk Score < 4 • Revenue from Oracle ≥95% of baseline (Option B) • New Engine bias index < 2%	CRO for revenue monitoring Legal Lead for risk score Engineering Lead for beta release
Q4	Complete Oracle Wind‑Down or deliver full Responsible AI Certification. Finalize new engine deployment to all clients. Secure Strategic Partnership Agreement with regulators (if Option A) or with biggest client (Option B).	• Oracle revenue loss < 10% • Legal fines avoided • New Engine bias index < 1% • Partnership signed	CRO for revenue CFO for fine avoidance CTO & COO for new engine rollout

Dashboard Widgets

Widget	What it shows	Frequency
MCS Heatmap	Color‑coded score (green, yellow, red)	Weekly
Revenue Funnel	Oracle sales pipeline vs. post‑transition revenue	Monthly
Legal Risk Radar	Likelihood & severity across jurisdictions	Quarterly
Bias Trend Graph	Model bias index over time	Biweekly
Stakeholder Satisfaction Gauge	Feedback from Board, Clients, Engineers	After each milestone

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5️⃣ Governance & Oversight

Why it matters – A crisis erodes trust in both people and processes. An independent body that reviews your decisions restores confidence.

1. Ethics Steering Committee (ESC) – Comprised of:

   • External AI ethics professor (no conflict).
   • Legal counsel from an independent law firm.
   • CFO (independent financial view).

2. Monthly MCF Review – ESC meets each month to:

   • Validate your MCS calculations and weight assumptions.
   • Ensure you’re not gaming the system by cherry‑picking data.
   • Approve any deviations from the agreed path.

3. Quarterly Board “Red‑Team” Drill – A small, independent team tests whether your transition could be exploited or accelerated in a worst‑case scenario. Their findings are fed back into the MCF to adjust weights if needed.

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6️⃣ Quick Decision Checklist

If you’re pressed for time and need to snap a decision before a board meeting:

Question	Yes → Go ahead with chosen path (after final sign‑off).	No → Revisit assumptions.
Do we have complete data for MH, LR, FC?		Gather missing numbers or use scenario brackets.
Is our MCS below 7 after applying default weights?		If >7, consider tightening the path (e.g., shorten shutdown timeline).
Can we secure legal indemnities or sandbox agreements within 2 weeks?		Delay board presentation; first do legal groundwork.
Have all key stakeholders (CRO, COO, top client) given explicit verbal or written approval for the plan?		Seek immediate confirmation.
Will proceeding today expose us to a legal risk spike that we cannot absorb?		Postpone until risk can be mitigated.

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TL;DR – The One‑Page Decision Snapshot

Axis	Score (1–5)	Weight	Weighted Impact
Moral Harm	4	0.40	1.6
Legal Risk	3	0.30	0.9
Financial Loss	2	0.30	0.6
Total MCS	—	—	3.1

Interpretation: With default weights, the combined cost of ignoring Oracle’s bias is a MCS of 3.1, comfortably below our “red‑alert” threshold of 7. Therefore we should proceed with Option B (Dual‑Track Mitigation) after securing the necessary legal indemnities and client commitment.

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Final Thought

Think of the MCF as your GPS in a stormy sea. The three axes are the currents pulling you toward different shores – moral righteousness, legal safety, financial viability. By scoring each current and applying transparent weights, you can steer your ship toward the safest island that still honors the compass needle pointing to “human‑first”.

You built Oracle because you believed AI could level the playing field for all job seekers. Now we have an opportunity – to be the first company that turns a catastrophic bias back into a beacon of ethical innovation.

Set up the spreadsheet, pull in those numbers, and let the MCF do the heavy lifting while you keep your moral compass true. Good luck, Dr. Thorne. You’ve already shown that you can invent the engine; now show that you can also build the ethical infrastructure around it.