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OpenAI launched an App Store in Nov 2023. A 23 month turnaround from major feature launch, to deprecation, to relaunch is a commitment to product longevity that

OpenAI launched an App Store in Nov 2023. A 23 month turnaround from major feature launch, to deprecation, to relaunch is a commitment to product longevity that’d put Google to shame.

AlphaAndOmega0 1y ago
I found it genuinely impressive how useless their "GPTs" were. Of course, part of it was due to the fact that the out-of-the-box models became so competent that there was no need for a customized model, especially when customization boiled down to barely more than some kind of custom system prompt and hidden instructions. I get the impression that's the same reason their fine-tuning services never took off either, since it was easier to just load necessary information into the context window of a standard instance. Edit: In all fairness, this was before most tool use, connectors or MCP. I am at least open to the idea that these might allow for a reasonable value add, but I'm still skeptical.
- scottoreily 1y ago
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- CharlieDigital 1y ago
  > I get the impression that's the same reason their fine-tuning services never took off either Also, very few workloads that you'd want to use AI for are prime cases for fine-tuning. We had some cases where we used fine tuning because the work was repetitive enough that FT provided benefits in terms of speed and accuracy, but it was a very limited set of workloads.
  - apwell23 1y ago
    > fine tuning because the work was repetitive enough that FT provided benefits in terms of speed and accuracy, can you share anymore info on this. i am curious about what the usecase was and how it improved speed (of inference?) and accuracy.
    - CharlieDigital 1y ago
      Very typical e-commerce use cases processing scraped content: product categorization, review sentiment, etc. where the scope is very limited. We would process tens of thousands of these so faster inference with a cheaper model with FT was advantageous. Disclaimer: this was in the 3.5 Turbo "era" so models like `nano` now might be cheap enough, good enough, fast enough to do this even without FT.
kbar13 1y ago
product roadmap was also ai generated

OpenAI launched an App Store in Nov 2023. A 23 month turnaround from major feature launch, to deprecation, to relaunch is a commitment to product longevity that’d put Google to shame.

AlphaAndOmega0 1y ago

I found it genuinely impressive how useless their "GPTs" were. Of course, part of it was due to the fact that the out-of-the-box models became so competent that there was no need for a customized model, especially when customization boiled down to barely more than some kind of custom system prompt and hidden instructions. I get the impression that's the same reason their fine-tuning services never took off either, since it was easier to just load necessary information into the context window of a standard instance. Edit: In all fairness, this was before most tool use, connectors or MCP. I am at least open to the idea that these might allow for a reasonable value add, but I'm still skeptical.

scottoreily 1y ago
[dead]
CharlieDigital 1y ago
> I get the impression that's the same reason their fine-tuning services never took off either Also, very few workloads that you'd want to use AI for are prime cases for fine-tuning. We had some cases where we used fine tuning because the work was repetitive enough that FT provided benefits in terms of speed and accuracy, but it was a very limited set of workloads.
- apwell23 1y ago
  > fine tuning because the work was repetitive enough that FT provided benefits in terms of speed and accuracy, can you share anymore info on this. i am curious about what the usecase was and how it improved speed (of inference?) and accuracy.
  - CharlieDigital 1y ago
    Very typical e-commerce use cases processing scraped content: product categorization, review sentiment, etc. where the scope is very limited. We would process tens of thousands of these so faster inference with a cheaper model with FT was advantageous. Disclaimer: this was in the 3.5 Turbo "era" so models like `nano` now might be cheap enough, good enough, fast enough to do this even without FT.

kbar13 1y ago

product roadmap was also ai generated