How does Jasper utilize GPT-3 and differ from other AI content creation tools?

When we first started, we just used vanilla GPT-3. It’s a misconception that everyone that uses a specific  model creates the exact same output. 

Maybe 20 to 30% of the output quality can be affected and added to on top of the base model through prompt engineering, the different settings, and so on. So even out of the gate, before we were doing anything fancy, we were consistently getting better quality than all of our competitors just based on knowing marketing and having a use case and knowing how to prompt our model and give it great examples.

Output quality is really what we sell. It’s our northstar and we are relentless in being best in class for that.  We want to have the highest quality output of anybody. For me, I'll use any tool or any model available to do that. 

Some of our outputs will be fine tuned models based on our own proprietary data that learns from our customers. We start to get a little bit of a data flywheel there that helps you just generate better and better models. 

But the fine tuning doesn't always work—it’s not a given that you can just train up a model and it'll be better than a base model—so it really depends.

We’ve also started to experiment and use open source or our own models in various places in the app. Again, there's not a one-size-fits-all. It depends on the use case, it depends on the template, and it depends on a lot of other factors.

I think some people get nervous or they think, "Oh, how can you even build a business if you're using the same kind of foundation models as everybody else?" there's lots of areas to differentiate and if you just stay focused on the core customer it becomes much clearer what you need to build either in the AI or outside of it.