The AI Stack: A Practical Guide to Building Your Own Intelligent Applications
This article explores the concept of the
Why it matters
This article provides a practical, transparent approach to building intelligent applications, empowering developers to move beyond being consumers of AI-as-a-service and become creators of tailored AI solutions.
Key Points
- 1The AI stack is composed of distinct, interoperable layers that work together to create intelligent applications
- 2Developers can choose from open-source or proprietary foundation models like GPT-4 or Llama 3 to build their AI stack
- 3LangChain is a powerful orchestration framework that abstracts model calls, provides prompt templates, and manages context
- 4Embedding and vector stores like Pinecone or Chroma are used to store and retrieve contextual information for the model
Details
The article explains that building an AI application is similar to building a web app, with distinct layers that work together. The Foundation Model Layer is the raw intelligence, such as a Large Language Model (LLM) or diffusion model. The Orchestration & Framework Layer handles communication with models, manages prompts, and sequences complex tasks, with LangChain being a popular choice. The Embedding & Vector Store Layer is where contextual information is stored and retrieved for the model. Finally, the Application & Integration Layer is the user-facing interface and business logic. The article walks through an example of building a
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