I agree with you on that a good integrator can get successful, but we should not forget here that the underlying code running all of this is in the order of hundreds of lines (see alpaca.cpp for example) in combination with a boatload of money required for training (that is quickly going down), to simplify the argument a bit.
It's hardly comparable to the gigantic ecosystem of services and micro-services that your comparison alludes to with IBM and Microsoft. OpenAI is nowhere near such a brand recognition, and grassroots support for it within a company would quickly move to the next free chatgpt-clone that is better or cheaper or faster or more accessible just as what happened with Dalle-2.
The value of the models themselves will quickly come down to just a slight bit over the underlying hardware costs and Altman knows this.
Microsoft bought themselves a $10B time window to try to do what you're saying, so let's see :) But even for them, when they've built LLM-adaptations to their most popular products, it's fairly simple to just swap it out with something new and more shiny and cheaper that's not OpenAI, and the end customer won't notice as it's the Microsoft or Office brand that they buy into. They are not going to advertise what's inside their products with big banners "Powered by OpenAI" in the long run, I think (do they now?)
What you refer as 'the underlying code' isn't the real underlying code, the underlying code is the model. Your underlying code is just the runtime, which is commercially the least interesting part (which is why it is/will be/ open sourced). Both the model and the integration are way more interesting commercially. I'm sure the code Microsoft has to integrate their assistant to Windows is way more than hundreds of lines. How long until GNOME/KDE even start on something similar? Probably not before 2030.
Anyway, I treat OpenAI and Microsoft as two sides of the same coin given level of integration between the two. It's arguable the Microsoft has the upper hand here but OpenAI is their main LLM talent. [EDIT: I don't see MS switching backends from a backend they control, especially when performance apparently is adequate enough already and the real cost isn't licensing the code, but Azure, so open source doesn't necessarily have an advantage here.]
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I agree with you on that a good integrator can get successful, but we should not forget here that the underlying code running all of this is in the order of hundreds of lines (see alpaca.cpp for example) in combination with a boatload of money required for training (that is quickly going down), to simplify the argument a bit.
It's hardly comparable to the gigantic ecosystem of services and micro-services that your comparison alludes to with IBM and Microsoft. OpenAI is nowhere near such a brand recognition, and grassroots support for it within a company would quickly move to the next free chatgpt-clone that is better or cheaper or faster or more accessible just as what happened with Dalle-2.
The value of the models themselves will quickly come down to just a slight bit over the underlying hardware costs and Altman knows this.
Microsoft bought themselves a $10B time window to try to do what you're saying, so let's see :) But even for them, when they've built LLM-adaptations to their most popular products, it's fairly simple to just swap it out with something new and more shiny and cheaper that's not OpenAI, and the end customer won't notice as it's the Microsoft or Office brand that they buy into. They are not going to advertise what's inside their products with big banners "Powered by OpenAI" in the long run, I think (do they now?)
What you refer as 'the underlying code' isn't the real underlying code, the underlying code is the model. Your underlying code is just the runtime, which is commercially the least interesting part (which is why it is/will be/ open sourced). Both the model and the integration are way more interesting commercially. I'm sure the code Microsoft has to integrate their assistant to Windows is way more than hundreds of lines. How long until GNOME/KDE even start on something similar? Probably not before 2030.
Anyway, I treat OpenAI and Microsoft as two sides of the same coin given level of integration between the two. It's arguable the Microsoft has the upper hand here but OpenAI is their main LLM talent. [EDIT: I don't see MS switching backends from a backend they control, especially when performance apparently is adequate enough already and the real cost isn't licensing the code, but Azure, so open source doesn't necessarily have an advantage here.]