Summary of Five Steps to Create a New AI Model
The video outlines a five-step workflow for creating specialized AI models, emphasizing the role of foundation models in streamlining the process.
- Prepare the Data: Gather extensive data (potentially petabytes) from open-source and proprietary sources. This stage involves categorizing data, applying filters to remove hate speech, profanity, copyrighted, or sensitive information, and eliminating duplicates to create a "base data pile" that is versioned and tagged for governance.
- Train the Model: Select an appropriate foundational model based on the intended use case (e.g., chatbot, classifier). The data pile is tokenized, and the model is trained using these tokens, which can be computationally intensive and time-consuming, often requiring thousands of GPUs.
- Validate: After training, the model is benchmarked to assess its performance against predefined quality metrics. A model card is created to document the training and benchmark scores.
- Tune: This stage involves application developers who refine the model by generating prompts and providing additional local data for fine-tuning, making the process significantly faster than building a model from scratch.
- Deploy: The model can be deployed as a service in the cloud or embedded into applications closer to the network edge. Continuous iteration and improvement of the model are encouraged post-deployment.
The video also introduces IBM's platform, watsonx, which supports all five stages of the workflow. It consists of:
- watsonx.data: A data lakehouse for managing data connections.
- watsonx.governance: Tools for managing data and model cards to ensure a governed AI lifecycle.
- watsonx.ai: A platform for application developers to interact with the model.
Overall, the use of foundation models is highlighted as a transformative approach to building specialized AI models more efficiently.
Main Speakers/Sources
Notable Quotes
— 00:33 — « But foundation models are changing that paradigm. »
— 06:40 — « Overall foundation models are changing the way we build specialized AI models. »
— 06:45 — « This 5-stage workflow allows teams to create AI and AI-derived applications with greater sophistication while rapidly speeding up AI model development. »
Category
Technology