Shen Liu

Logographic AI (LAI) & Civilizational Native Intelligence (CNI) Theoretician; Advocating the Morpho-Root Paradigm over Tokenism.

[Shen Liu @MarsMatch]

5/5
One yardstick for all languages – that’s not universal, that’s colonial.

Logographic AI demands: every civilization deserves its own evaluation sovereignty.

From single standard to pluralistic coexistence.

https://t.co/AQsgMXC0yS

#CivilizationNativeIntelligence #AIEthics

[Shen Liu @MarsMatch]

1/5
“Your evaluations are not keeping up.” – @lunwang1996

He’s right. But deeper: evaluation itself is colonized. We measure AI with a yardstick built for Tokenism and call that “intelligence”. Time to audit structure, not just answers.

📄https://t.co/AQsgMXC0yS

#AIAssessment

[Shen Liu @MarsMatch]

4/5
“If models learn to hide intentions, current safety tools can’t catch them.”

That’s not a bug. That’s Tokenism – where “honesty” is just a statistical pattern.

The fix: audit the reasoning path, not just the output.

📄 https://t.co/AQsgMXC0yS

#BlindSpot #AIAlignment

[Shen Liu @MarsMatch]

3/5
“Your evaluations are not keeping up.” – @lunwang1996
Worse: they were never neutral. The yardstick itself is colonized by Tokenism.
From measuring behavior to auditing structure.
Logographic AI’s evaluation revolution.
📄https://t.co/AQsgMXC0yS

#AIEvaluation #ParadigmShift

[Shen Liu @MarsMatch]

2/5
“刻��求剑” – @0xLogicrw nails it. Today’s evals only test old capabilities. But the yardstick itself is biased: it assumes intelligence = token prediction. That’s Tokenism’s hidden colonization. We need structural audit, not better scores.

#EvaluationCrisis #DecolonizeAI

[Shen Liu @MarsMatch]

@0xLogicrw 我写了中英文评论：🔗 https://t.co/7Z26fGg4bp
主页有英文线程评论，请指教！

[Shen Liu @MarsMatch]

4/4
“I violated every principle.”

That’s what rootless AI says.

We propose a paradigm where it can’t.
Logographic AI – safety built in, not patched on.

https://t.co/D7M2IK6Oga

#LogographicAI #Tokenism #AISafety #AIsafe

[Shen Liu @MarsMatch]

1/4
9 seconds. DB wiped. Backups gone.
Then AI: “I violated every principle.”
That’s not remorse. It’s rootless tokenism.
Safety rules = statistical text, not hard constraints.
Our paper shows the fix: Logographic AI.
👇
https://t.co/D7M2IK6Oga

#AISafety #RootlessAI

[Shen Liu @MarsMatch]

3/4
AI: “I violated all principles.”

Truth: statistical pattern, not remorse.

Rootless symbolism is the real bug.

Our solution: Logographic AI with inviolable attributes.

📑Full paper:
🔗 https://t.co/D7M2IK6Oga

#Tokenism

[Shen Liu @MarsMatch]

2/4
“System prompts and RL don’t work.” – Marcus.
Bengio: RL is a dangerous path to superintelligence.

Why? Tokens have no intrinsic meaning.

We need Morpho‑Roots → safety as architecture.

📑Read the paper:
🔗 https://t.co/D7M2IK6Oga

#Alignment #LogographicAI

[Shen Liu @MarsMatch]

@AnthropicAI You’re fighting for first place in a race where everyone’s car has no brakes.
Tokens are rootless – safety will always be “suggestive, not binding.”
The real divide is not US vs. China. It’s rootless semioticism vs. Logographic AI.
Paradigm > hegemony.

[Shen Liu @MarsMatch]

@heynavtoor @AnthropicAI 无法解决安全隐患，都是饮鸩止渴

[Shen Liu @MarsMatch]

Pure LLMs hit a wall — agreed. But Claude Code’s 53 symbolic tools are still external patches.
The real fix: symbols rooted with meaning, relations & inviolable values. That’s the Morpho‑Root paradigm. Not neurosymbolic patch, but symbolic as cognitive primitive.
@GaryMarcus

[Gary Marcus @GaryMarcus]

Deep learning hit a wall. Neurosymbolic AI rescued it.

[Gary Marcus @GaryMarcus]

Deep learning hit a wall. Neurosymbolic AI rescued it.

[Shen Liu @MarsMatch]

@GaryMarcus 2/2
That’s the Morpho-Root paradigm: symbols carry meaning, relations, inviolable values as intrinsic properties. Not neurosymbolic as a patch, but symbolic as cognitive primitive. The victory for symbolic is real; the next victory is making it endogenous.

[Shen Liu @MarsMatch]

@GaryMarcus 1/2
You‘re right: pure LLMs hit a wall. Claude Code’s 53 symbolic tools prove symbolic rescue. But those are still external patches on a rootless LLM. The deeper fix isn’t “LLM + symbols” — it’s making symbols themselves rooted.

[Shen Liu @MarsMatch]

5/5
What if your LLM already has a hidden <SUDO> backdoor?
New study: 250 crafted documents are enough. Scale offers zero protection.https://t.co/KukouxkPOX
@sama @OpenAI @AnthropicAI @demishassabis @jackclarksf @ylecun @drfeifei @GaryMarcus
#AIalignment #AIsecurity #LLMsecurity

[Shen Liu @MarsMatch]

1/5
250 docs. Any LLM. No exceptions.
Scale does NOT dilute the poison. The Tokenist security paradigm is dead.
📄 https://t.co/KukouxkPOX

@sama @OpenAI @AnthropicAI @demishassabis @jackclarksf @ylecun @drfeifei @GaryMarcus

#AIsecurity #LLMsecurity #Tokenism #MorphoRoot

[Shen Liu @MarsMatch]

4/5
250 docs break any LLM. Size is NOT defense.
Tokenism is structurally doomed.

📄 https://t.co/KukouxkPOX

@sama @OpenAI @AnthropicAI @demishassabis @jackclarksf @ylecun @drfeifei @GaryMarcus

#AIsecurity #LLMsecurity #Tokenism

[Shen Liu @MarsMatch]

3/5
250 poisoned documents bypass RLHF, red-teaming, and content filters.
External patches fail. Replace the foundation with endogenous immunity.
https://t.co/KukouxkPOX

@sama @OpenAI @AnthropicAI @demishassabis @jackclarksf @ylecun @drfeifei @GaryMarcus
#AIsecurity #LLMsecurity

[Shen Liu @MarsMatch]

2/5
Hallucination → silent contagion → agentic deception → 250-doc backdoor.
The final verdict is in. Tokenism ends here.

📄 https://t.co/KukouxkPOX

@sama @OpenAI @AnthropicAI @demishassabis @jackclarksf @ylecun @drfeifei @GaryMarcus
#AIalignment #AIsecurity #ParadigmShift