"個人工作室" 相關案件

RD 工作

web 接案

1. 網站,後台管理系統,電腦應用程式,電腦遊戲,其他 2. 其他 3. 其他 4. 其他 5. 其他

描述： 1. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency 2. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency 3. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency, with future SaaS scalability. Vision Create a single-node, fully offline AI system capable of: • Real-time doctor-avatar interaction • Low-latency speech-to-speech response • WebRTC-based video interface (Meet-like UX) • Modular LLM / STT / TTS architecture • Local knowledge ingestion & daily sync • Deployable on high-performance laptops or edge machines Phase 1 is a commercial MVP. Phase 2 expands into multi-clinic deployment and enterprise orchestration. ⸻ Technical Scope We are looking for engineers comfortable with: • Local LLM inference (7B–13B class models) • CUDA optimization & VRAM management • Quantization strategies • Streaming STT + TTS pipelines • WebRTC video + data channel integration • Audio-driven avatar rendering • Docker-based modular architecture • Offline RAG and versioned data ingestion This system must: • Run fully offline • Maintain ~1–2s response latency • Be modular and replaceable at each layer • Deliver full source code and deployment documentation ⸻ Who We Want Engineers who: • Have deployed local inference systems before • Understand performance bottlenecks • Can design scalable architecture from day one • Think in systems, not scripts This is an opportunity to build a foundational AI platform — not a contract task. All IP and derivative rights belong to 弛雅有限公司. ⸻ 4. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency, with future SaaS scalability. Vision Create a single-node, fully offline AI system capable of: • Real-time doctor-avatar interaction • Low-latency speech-to-speech response • WebRTC-based video interface (Meet-like UX) • Modular LLM / STT / TTS architecture • Local knowledge ingestion & daily sync • Deployable on high-performance laptops or edge machines Phase 1 is a commercial MVP. Phase 2 expands into multi-clinic deployment and enterprise orchestration. ⸻ Technical Scope We are looking for engineers comfortable with: • Local LLM inference (7B–13B class models) • CUDA optimization & VRAM management • Quantization strategies • Streaming STT + TTS pipelines • WebRTC video + data channel integration • Audio-driven avatar rendering • Docker-based modular architecture • Offline RAG and versioned data ingestion This system must: • Run fully offline • Maintain ~1–2s response latency • Be modular and replaceable at each layer • Deliver full source code and deployment documentation ⸻ Who We Want Engineers who: • Have deployed local inference systems before • Understand performance bottlenecks • Can design scalable architecture from day one • Think in systems, not scripts This is an opportunity to build a foundational AI platform — not a contract task. All IP and derivative rights belong to 弛雅有限公司. ⸻ 5. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency 6. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency, with future SaaS scalability. Vision Create a single-node, fully offline AI system capable of: • Real-time doctor-avatar interaction • Low-latency speech-to-speech response • WebRTC-based video interface (Meet-like UX) • Modular LLM / STT / TTS architecture • Local knowledge ingestion & daily sync • Deployable on high-performance laptops or edge machines Phase 1 is a commercial MVP. Phase 2 expands into multi-clinic deployment and enterprise orchestration. ⸻ Technical Scope We are looking for engineers comfortable with: • Local LLM inference (7B–13B class models) • CUDA optimization & VRAM management • Quantization strategies • Streaming STT + TTS pipelines • WebRTC video + data channel integration • Audio-driven avatar rendering • Docker-based modular architecture • Offline RAG and versioned data ingestion This system must: • Run fully offline • Maintain ~1–2s response latency • Be modular and replaceable at each layer • Deliver full source code and deployment documentation ⸻ Who We Want Engineers who: • Have deployed local inference systems before • Understand performance bottlenecks • Can design scalable architecture from day one • Think in systems, not scripts This is an opportunity to build a foundational AI platform — not a contract task. All IP and derivative rights belong to 弛雅有限公司. 7. We are building an offline-first AI Digital Doctor Platform — a real-time interactive avatar system that runs entirely on local hardware. This is not a chatbot project. This is not a website. This is a product-level AI system designed to operate without cloud dependency, with future SaaS scalability. Vision Create a single-node, fully offline AI system capable of: • Real-time doctor-avatar interaction • Low-latency speech-to-speech response • WebRTC-based video interface (Meet-like UX) • Modular LLM / STT / TTS architecture • Local knowledge ingestion & daily sync • Deployable on high-performance laptops or edge machines Phase 1 is a commercial MVP. Phase 2 expands into multi-clinic deployment and enterprise orchestration. ⸻ Technical Scope We are looking for engineers comfortable with: • Local LLM inference (7B–13B class models) • CUDA optimization & VRAM management • Quantization strategies • Streaming STT + TTS pipelines • WebRTC video + data channel integration • Audio-driven avatar rendering • Docker-based modular architecture • Offline RAG and versioned data ingestion This system must: • Run fully offline • Maintain ~1–2s response latency • Be modular and replaceable at each layer • Deliver full source code and deployment documentation ⸻ Who We Want Engineers who: • Have deployed local inference systems before • Understand performance bottlenecks • Can design scalable architecture from day one • Think in systems, not scripts This is an opportunity to build a foundational AI platform — not a contract task. All IP and derivative rights belong to 弛雅有限公司.

低音大提琴教學

蔡〇樺

台中市太平區

單堂時長：60分鐘

上課頻率：每週一次

9小時前

搶先接洽

音樂家教

音樂工作

1. 無經驗 2. 古典樂 3. 準備檢定考試 4. 會 5. 小於13歲

日文家教

阿〇

台南市新營區

上課頻率：每週一次

上課預算：每小時500-750元

9小時前

日文老師

日語家教

1. 初級（約N5-N4） 2. 18-50歲 3. 女性老師 4. 60分鐘 5. 日常會話

軟體開發

段〇〇光

台北市中正區

顧客預算：十萬到五十萬

交件時限：急件: • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合

9小時前

RD 工作

web 接案

1. 網站,後台管理系統,電腦應用程式,其他 2. 其他 3. 其他 4. 其他 5. 其他

描述： 1. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 2. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 3. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 4. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 5. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 6. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 7. • AI 系統整合 • LLM 本地部署 • 語音辨識 STT • WebRTC 視訊工程 • GPU CUDA 優化 • Docker 部署工程師 • 全端工程師 AI 整合 8. 本專案為本地離線 AI 醫師分身即時影音互動系統，需包含： 1. 本地 LL M 部署（不可依賴******** 2. 語音辨識 STT 與語音合成 TTS 串接 3. WebRTC 即時視訊架構（類 Google Meet 介面） 4. 2D 或簡易 3D 分身動畫整合（嘴型同步） 5. GPU CUDA 優化與效能調校 6. Docker 容器化部署與一鍵啟動 7. 開機自動執行 8. 醫師知識可每日更新並同步 9. 全部原始碼與部署文件完整交付 10. 著作權、修改權、擴充權歸屬弛雅有限公司 11. 不得使用侵權模型或未授權素材