Plenty of data is ambiguous without additional description or schema to clarify its meaning. It’s easy to come up with structured data that can’t easily be interpreted without its accompanying schema. Here’s an example:
{ "data": [ 12, "21", true, { "name": "John Doe", "age": 30 } ] } You can argue that this is “bad” structured data, but if you have this data structure, there is little meaning you can derive without additional insight into what the data represents.
The most popular language model use cases I’ve seen around have been
chatbots agents chat your X use cases These use cases are quite cool, but often stand alone, separate from existing products or added on as an isolated feature.
Expanding production use cases for language models I’ve been thinking about what could it look like to naturally embed a call to language model in code to flexibility make use of its capabilities in a production application.