Amazon Web Services 的託管平台,透過統一的 API 存取和部署來自多個供應商(Anthropic、Meta、Mistral、Cohere、Stability AI、Amazon 自己的 Titan 模型)的基礎模型。Bedrock 處理模型託管、擴展、fine-tuning,讓企業無需管理 GPU 基礎設施就能用 AI。它還提供 guardrail、知識庫(RAG)、agent 能力。
為什麼重要
AWS Bedrock 是大多數 Fortune 500 公司存取 AI 模型的方式。它的多模型方法讓企業透過單個 API 比較和切換供應商(Claude、Llama、Mistral),避免供應商鎖定。對已經在 AWS 上的公司(大多數大公司都是),Bedrock 是採用 AI 阻力最小的路徑 — 同一個帳戶、同一個帳單、同樣的合規框架。
Deep Dive
Bedrock's key features: model access (API calls to multiple foundation models without hosting them yourself), fine-tuning (customize models on your data without managing training infrastructure), knowledge bases (managed RAG with automatic document processing and vector storage), agents (models that can call APIs and execute multi-step tasks), and guardrails (content filtering and safety controls applied across all models).
The Multi-Model Strategy
Unlike OpenAI (which offers only its own models) or Anthropic (Claude only), Bedrock provides access to models from many providers. This lets enterprises: evaluate models for their specific use case, use different models for different tasks (Claude for reasoning, Llama for high-volume simple tasks), and switch providers without changing application code. The unified API abstracts away provider-specific differences, though each model still has its own strengths and limitations.
