| I'd like to get your recommendations for an AI choice of large language model. That would be efficient for what you might call kind of fairly simple but repetitive tasks in the sense of, let's say, for example, I'm running an agent that's going to process my voice notes and it's going to have a cleanup prompt. And so just cleaning up the format for to make it a bit more coherent basically and then saving that somewhere. So this might be run 50 times a day and I don't want to, you know, you rack up huge API costs on doing so. | |
| Traditionally, the use of a very strong contender for this kind of work was Turbo 3.5 and so on. But I feel like that's a little bit, I personally feel like there's no need to go quite that back far in the models. There are more modern up-to-date cost-efficient models. I'd be interested to know what the current time in terms of what OpenAI has, what maybe Cohere has, or any other LLMs that are really kind of optimized for what you might call, I think there's a big difference between the type of prompting that you might do in a conversational interface where you're looking for a lot of detail and interactivity versus agents for this kind of instructional tasks. | |
| The simple answer is it's an instructional fine-tune and so on. But I see that instructional and conversational are converging and there's less models now being explicitly marketed as instructional. So I'd just like to get your take on that. |