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An API is a set of rules and protocols that allows different software applications to communicate with each other. In AI, APIs let developers integrate AI capabilities — like text generation or image analysis — into their own applications without building models from scratch.
APIs democratise access to powerful AI — any developer can add sophisticated AI features to their product by making simple API calls, without needing deep ML expertise.
A startup integrates OpenAI's API to add an AI writing assistant to their note-taking app, sending user prompts to GPT and displaying the generated text.
Inference
Inference is the process of using a trained AI model to make predictions or generate outputs on new, unseen data. While training is about learning patterns, inference is about applying what the model has learned to real-world inputs.
Large Language Model (LLM)
A large language model is an AI system trained on vast quantities of text data that can understand, generate, and reason about human language. LLMs use the transformer architecture and contain billions of parameters, enabling them to perform a wide range of language tasks.
Prompt Engineering
Prompt engineering is the practice of crafting and refining the instructions (prompts) given to an AI model to get the best possible output. It involves techniques like providing context, examples, and constraints to guide the model's response.
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