Foundation Model Choices

Foundation Model Choices

What model are you going to use as the Foundation Model? There are really three major options:

• Commercial models
• Open source models
• Build Your Own (BYO)

Of course, there's that fourth option of not using AI, which, as anyone in the AI industry will tell you, leads to analysts shunning your stock, instant bankruptcy, and your toenails catching on fire.

Building your own model is a viable option for small to medium models, that you want to train on your data set. However, only the major tech companies have been successful at training a massive LLM foundation model, given the expertise required and expense of training.

The alternative is to choose an existing foundation model, that is pre-trained on lots of general data. Then you would fine-tune that model on whatever proprietary data that you want to use.

If you have no specific extra data for fine-tuning, then you're basically using a commercial or open source model underneath. You can still achieve significant customization of an existing model without fine-tuning, using techniques such as prompt engineering, Retrieval-Augmented Generation (RAG), and the simple idea of mixing heuristics with AI inference results.

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