A missing layer before compute begins
Over the past three months, I built a Semantic Firewall –
a “CPU before the GPU” to judge whether a question should activate compute. AI giants like OpenAI / Anthropic / AWS / Google / NVIDIA / Microsoft focus on model speed — but AI still cannot judge if a question is valid. That is why efficiency must start BEFORE token generation.
🔍 What it does:
• Validate intent & logic before execution • Trigger compute only when necessary • Reduce 70–99.9% redundant tokens • Add governance & auditability (WORM + Hash) • Can be deployed on Bedrock / SageMaker / Vertex / Enterprise AI / Physical AI
📁 Cloud folder (PDF / infographic / press coverage):
https://drive.google.com/drive/folders/16Xx3YmoeMeqgVCpQi7cf67q6oKDRJt9R
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🇹🇼 沈耀語意防火牆 V1
算力啟動前，先判斷語意是否成立
我開發了一套語義治理層，可視為：
「在 GPU 前運行的 CPU」 判斷問題是否值得啟動模型。 AI 巨頭如 Google / AWS / Anthropic / OpenAI / NVIDIA / Microsoft 都在加速算力，卻忽略—— AI 並不會判斷問題是否成立。
🛡 核心功能：
✔ 語意判斷 → 才啟動算力 ✔ 減少 70–99.9% Token 成本 ✔ 可稽核 / 可追蹤 ✔ 可部署於 Bedrock / SageMaker / Physical AI
📁 技術資料夾（持續更新）：
https://drive.google.com/drive/folders/16Xx3YmoeMeqgVCpQi7cf67q6oKDRJt9R
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🧠 Before Compute, Then What?
This layer may answer it.
#SemanticFirewall #ShenYao #AIGovernance #AIEfficiency #AISafety #ComputeCost #LLM #PhysicalAI #Robotics #OpenAI #Anthropic #AWS #AmazonWebServices #GoogleCloud #DeepMind #Microsoft #Azure #NVIDIA #MetaAI #SageMaker #Bedrock #VertexAI #EnterpriseAI #Regulation #MAS #FinTech #Taiwan #Taichung #SilentSchoolStudio
