Module assessment

Recurrent Neural Networks (RNNs) and memory retention

Attention and positional encoding

Prompt engineering and groundedness

Large Language Models are trained with vast quantities of text. The text represents a wide range of general subject matter, while Small Language Models are trained with smaller, more subject-focused datasets.

Large Language Models are trained to include an understanding of context, while Small Language Models aren't.

Large Language Models have fewer parameters than Small Language Models.

It's used to manage access, authentication, and data usage in AI models.

It involves connecting a language model to an organization's proprietary database.

It involves further training a pretrained model on a task-specific dataset to make it more suitable for a particular application.

Identify potential benefits, Measure the benefits, Enhance the benefits, Operate the solution responsibly

Identify potential harms, Measure these harms, Mitigate the harms, Operate the solution responsibly

Define the problem, Design the solution, Develop the solution, Deploy the solution