The 5-Stage Workflow for Building Specialized AI Models

🔑Deep learning has enabled the development of specialized AI models by gathering, labeling, and training data.

🚀Foundation models provide a base model that can be adapted to create specialized models through fine-tuning.

🗂️The 5-stage workflow for building AI models includes data preparation, model training, validation, tuning, and deployment.

💻Application developers can engage with models in the tuning stage to improve performance using prompts and additional data.

🌐IBM's watsonx platform provides the tools and infrastructure to support the entire AI model development workflow.

What is a foundation model?

—A foundation model is a base model that can be adapted to create specialized AI models through fine-tuning.

What are the stages of the AI model development workflow?

—The stages include data preparation, model training, validation, tuning, and deployment.

Who can engage with the model in the tuning stage?

—Application developers can engage with the model in the tuning stage to improve performance.

What is IBM's watsonx platform?

—Watsonx is a platform provided by IBM that supports the entire AI model development workflow.

How do foundation models speed up AI model development?

—Foundation models provide a base that can be fine-tuned, reducing the time and computational cost of building models from scratch.

00:00Deep learning enables the development of specialized AI models through data gathering, labeling, and training.

02:20The 5-stage workflow for building AI models includes data preparation, model training, validation, tuning, and deployment.

04:32Application developers can engage with the model in the tuning stage to improve performance using prompts and additional data.

05:19IBM's watsonx platform provides the tools and infrastructure to support the entire AI model development workflow.

06:45Foundation models speed up AI model development by providing a base that can be fine-tuned, reducing time and computational cost.