Answer :
I would be happy to help with that question. The term used to define the process of a company using a pre-trained AI model and further training it with their own question-answer dataset is called "Fine-tuning."
Here's a breakdown to explain this process:
1. Initially, a company starts with a pre-trained AI model that has already learned patterns and features from a general dataset.
2. To make the AI model more specific to their needs, the company further trains it using their own question-answer dataset. This additional training process is known as fine-tuning.
3. Fine-tuning helps the AI model adapt to the specific nuances and patterns present in the company's dataset, improving its performance on the particular task at hand.
Therefore, in the context of the question, the correct term to describe this process is "Fine-tuning." This term is commonly used in the field of machine learning and artificial intelligence when refining pre-existing models to suit specific requirements.
Here's a breakdown to explain this process:
1. Initially, a company starts with a pre-trained AI model that has already learned patterns and features from a general dataset.
2. To make the AI model more specific to their needs, the company further trains it using their own question-answer dataset. This additional training process is known as fine-tuning.
3. Fine-tuning helps the AI model adapt to the specific nuances and patterns present in the company's dataset, improving its performance on the particular task at hand.
Therefore, in the context of the question, the correct term to describe this process is "Fine-tuning." This term is commonly used in the field of machine learning and artificial intelligence when refining pre-existing models to suit specific requirements.
