The AI solution accelerators that are provided by IBM are a set of end-to-end solutions that you can run as examples or customize them to address common business issues.
Overview of AI solution accelerators
An AI solution accelerator is designed to help you solve a specific business problem with an AI solution. Browse the accelerators in the Resource hub and create the ones that you want.
An accelerator consists of a sample project that contains everything you need to build an AI solution. The sample project can include data assets, Jupyter notebooks, scripts, jobs, and parameter sets.
Process overview
Each accelerator provides detailed instructions. These steps provide an overview of the process for sample projects:
To get started with an accelerator:
- Go to the sample project in Resource hub. You can filter the samples in the Resource hub to see all sample projects or all AI solution accelerators.
- Click Create project and complete the steps to create the project.
- Follow the instructions to run the notebooks and complete other tasks.
Accelerators
The Q&A with RAG Accelerator guides you through setting up retrieval-augmented generation (RAG) to generate factually accurate output that is grounded in information from provided documents.
The Building ML models in watsonx.ai and batch scoring with Spark in watsonx.data guides you through the end-to-end workflow of training and persisting ML models in watsonx.ai and batch scoring those models with Spark at scale in watsonx.data.
Parent topic: Getting started