How to use LLM technology alongside Wolfram Language, including the conversational interface of Chat Notebooks and the programmatic operations possible with LLM functions.
Modern LLMs can be incorporated into traditional computational workflows and used to power programming operations. This course will show you different ways you can use LLM technology alongside Wolfram Language, including how to use the conversational interface of Chat Notebooks and the programmatic operations possible with LLM functions. See examples of writing both fun and functional LLM prompts. Write code that interfaces with different service providers' LLM models from within the Wolfram environment as well as provides symbolic representation of tools that can be used by LLMs.
Featured Products & Technologies: Wolfram Language and Wolfram Notebooks (available in Mathematica, Wolfram|One and Wolfram|Alpha Notebook Edition)
Outline
Using Chat Notebooks: Set up Wolfram Chat Notebooks to work with an LLM model. Utilize chat interactions with an LLM within a notebook for responses to questions and also to write code.
Adding LLM Functionality to Your Wolfram Workflow: Access an LLM model from within Wolfram Language. Use built-in functions like LLMSynthesize, LLMFunction, LLMExampleFunction, etc. See examples of other available AI-related functionality.
Engineering Better Prompts: Understand the benefits of prompt engineering and how it can be used to fine-tune responses from the LLM.
Creating New Content and Functionality: Explore the Wolfram Prompt Repository to find pre-built prompts that can be used as building blocks of "LLM programming." Create and submit your own prompts.
Modern LLMs can be incorporated into traditional computational workflows and used to power programming operations. This course will show you different ways you can use LLM technology alongside Wolfram Language, including how to use the conversational interface of Chat Notebooks and the programmatic operations possible with LLM functions. See examples of writing both fun and functional LLM prompts. Write code that interfaces with different service providers' LLM models from within the Wolfram environment as well as provides symbolic representation of tools that can be used by LLMs.
Featured Products & Technologies: Wolfram Language and Wolfram Notebooks (available in Mathematica, Wolfram|One and Wolfram|Alpha Notebook Edition)
Outline
Using Chat Notebooks: Set up Wolfram Chat Notebooks to work with an LLM model. Utilize chat interactions with an LLM within a notebook for responses to questions and also to write code.
Adding LLM Functionality to Your Wolfram Workflow: Access an LLM model from within Wolfram Language. Use built-in functions like LLMSynthesize, LLMFunction, LLMExampleFunction, etc. See examples of other available AI-related functionality.
Engineering Better Prompts: Understand the benefits of prompt engineering and how it can be used to fine-tune responses from the LLM.
Creating New Content and Functionality: Explore the Wolfram Prompt Repository to find pre-built prompts that can be used as building blocks of "LLM programming." Create and submit your own prompts.
