From the course: Text to SQL: Amazon Redshift Serverless for Generative SQL in Amazon Q

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Understanding the solution architecture

Understanding the solution architecture

From the course: Text to SQL: Amazon Redshift Serverless for Generative SQL in Amazon Q

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Understanding the solution architecture

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- [Instructor] Just last week, I was watching a documentary about the Eiffel Tower. The landmark of Paris, as we admire the aesthetics of architecture today, it is also built with strong engineering principles. To appreciate the art in the science, let's take a closer look at the architecture of Amazon Q. Large language models, like OpenAI's ChatGPT, are built on a pre-trained transformer architecture. Therefore, a transformer represents a neural network architecture. It was developed by Google researchers who conceptualize the attention mechanism. In our prompt, our words or text are tokens. In natural language processing, tokens are represented by vectors, which are numerical representation of words, sentences and even documents so that computers can process and understand meaning and relationships via numbers. To illustrate in an example, if we take the text, "British blue cat," the words equal three tokens. In a vector, three tokens would be assigned with the corresponding…

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