Does anyone else think this? The new models are much less creative, and the variety of outputs that I can produce is so much smaller. Yes, they follow instructions, but the outputs are short and repetitive. What is the point of using GPT-3 to tell me something I could find on Wikipedia? What is the point of using it for summarization, something that I could easily do with a smaller model? OpenAI is moving in the wrong direction with this. I understand you are trying to respond to the way users are leveraging the playground, but you are just giving them a “faster horse” at the price of limiting the true capabilities of the model.
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I find that it depends on the prompt. If one gives it 2000 magical tokens, twice the magic back ye shall receive 
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Tokens are in fourths. Divide by 4. I understand what you mean by boring though.
Its definitely prompt-specific, but if I’m going to long form prompts, I will still say that the original Davincis are going to give me better, more creative results. I can’t just give them one sentence zero shot commands, but I also can just coax a far vaster variety of reactions from them.
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Thanks @amandamariemoore714 for the advice…good to remember that its generating token-wise, not word-wise.
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I still use davinci-instruct-beta for a lot of things. It’s the most creative, I think, better than davinci, but without as much fine control as basic davinci.
text-davinci has its niche, but I think it works best for “lazier” prompts. The older versions need a lot more work to have good output. The new ones are basically cheaper and more consistent. I have a poetry generator that runs on text-davinci-002 and it’s surprisingly accurate.
I do think it’s the wrong direction, but it’s fine as long as they keep the older versions too.
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I hadn’t tried it tons/much but I felt it too, much less impressive than the original GPT-3.
Agreed, for creative writing, one of the best features of the original davinci model is the ability to press the regenerate button and get a completely different completion.
The new models output the same thing almost every time, which makes them useful only in marginal situations for creative writing.
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My experience is that it became more neutral, more objective and less controversial. For example, when I ask it for phone recommendation, it tells me “there’s no one answer to which the phone is the best” instead of actually recommending something. I can change the prompt and I will get what I want, but I also preferred if the model was more subjective. The neutral and objective answers are often useless.
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