How does it seem to compare with GPT 3.5? That really seems like the baseline for what's usable.
That said:
- For many uses, it doesn't matter. For many of the ways I use it, I don't care. For basic use (e.g. clean up an email for me), it's basically the same. For things like complex reasoning, algorithms, or foreign languages, the hosted service is critical.
- GPT3-grade models have more soul. OpenAI trained GPT3.5 and 4 to never do anything offensive, and that has a lot of negative side effects, well-documented in research. The way I'd describe it, though, is the difference between talking to a call center rep and your grandma (with mild Alzheimer's, perhaps). They both have their place.
- Different models are often helpful in workflows.
My experience is anecdotal. Please don't take it as more than one data point. If other people post their anecdotal experiences, you'll get the plural of "anecdote."
I'm absolutely disgusted by OpenAI for this "do no offense" approach. How can people so smart be so damn uneducated?
Then again, this industry has disgusted me for a long time so it's not really a surprise.
Based on the rate of progress in the open source world, it won't be more than a year before we have an open source model that is truly superior to GPT 3.5
The commercial & api based models are still more capable general purpose tools. But the current open tooling can do some nifty stuff, and the community around it is moving at a breakneck speed still.
In some areas, it's acceptably good. In some areas it's not. But it's getting better really fast.
Can you elaborate on what those capabilities are?
It's also not licensed commercially, so I avoid some things with it (ex: I do a lot of personal learning/investigation, but it doesn't touch or write anything related to work or personal projects)
The open models are a little further behind, but it's interesting to see them spin off into niches where they have strengths based on tuning/training.