Describe natural language generation capabilities of Azure OpenAI Service
OpenAI’s NLP models employ sophisticated algorithms to understand and generate human-like text. As you learned in Chapter 10, Identify Features of Generative AI Solutions, these models are trained on vast datasets consisting of words or sequences of characters, referred to as tokens.
For instance, a complex word such as juggernaut might be segmented into smaller tokens such as jug, ger, and naut for more granular analysis, whereas a simpler and more common word such as train may be treated as a single token. Each token is then converted into a numerical vector, a process that transforms the textual information into a format that the ML model can efficiently process and learn from.
This vectorization of tokens allows the model to discern patterns, relationships, and contexts within the language, facilitating a deep understanding of linguistic structures. When interacting with user input, the model...
