The good startups are building, fine tuning, and running models locally.
I know it can be wrong, but usually when it is, it’s obviously wrong
Support workload on our Slack was reduced by 50-75% and the output is steadily improving.
I wouldn’t want to go back tbh.
- Writing: emails, documentation, marketing - Write a bunch of unstructured skeleton of information. Add a prompt about the intended audience and a purpose. Possibly ask it to add some detail.
- Coding: Especially things like "Is there a method for this in this library" - a lot quicker than browsing through documentation. Some errors - copy-paste the error from the console, maybe a little bit for context, and quite often I get the solution.
And API based:
- Support bot
- Prompt engineering of some text models that normally would require labeling, training, and evaluation for weeks or months. A couple of use cases - unstructured text as an input + prompt, JSON as an output.
more efficient than just googling "<method description> <library name>"?
I use DALLE3 extensively for my woodworking hobby, where I ask it to come up with ideas for different pieces of furniture, and have constructed several based on those suggestions.
For work I use it to write emails, to come up with skeletons for performance reviews, look back look ahead documents, ideas for what questions to bring up during sprint reviews based on data points I provide it etc.
It’s just so much more efficient in getting the answers I need. And it makes a great pair programmer partner.