When it comes to large language models, should you build or buy?
Last summer could only be described as an “AI summer,” especially with large language models making an explosive entrance. We saw huge neural networks trained on a massive corpora of data that can accomplish exceedingly impressive tasks, none more famous than OpenAI’s GPT-3 and its newer, hyped offspring, ChatGPT.
Companies of all shapes and sizes across industries are rushing to figure out how to incorporate and extract value from this new technology. But OpenAI’s business model has been no less transformative than its contributions to natural language processing. Unlike almost every previous release of a flagship model, this one does not come with open-source pretrained weights — that is, machine learning teams cannot simply download the models and fine-tune them for their own use cases.
Instead, they must either pay to use them as-is, or pay to fine-tune the models and then pay four times the as-is usage rate to employ it. Of course, companies can still choose other peer open-sourced models.
