Technical terms explained clearly
An AI system that can independently plan, make decisions, and take actions to accomplish goals — rather than just answering questions.
A software development practice where code changes are automatically tested, integrated, and deployed to production.
A distributed computing paradigm that processes data closer to the source, reducing latency and bandwidth usage.
A deep learning model trained on vast text data that can understand and generate human-like text.
The practice of reverse-engineering AI models to understand how they actually arrive at their answers, rather than treating them as black boxes.
An AI architecture that enhances LLM responses by retrieving relevant context from external knowledge bases before generating answers.
A database optimized for storing and querying high-dimensional vector embeddings used in similarity search and AI applications.
Mental Bound