GPT-4 API was just made generally available, and:
We are working on safely enabling fine-tuning for GPT-4 and GPT-3.5 Turbo and expect this feature to be available later this year.
Also:
Developers wishing to continue using their fine-tuned models beyond January 4, 2024 will need to fine-tune replacements atop the new base GPT-3 models […] or newer models (gpt-3.5-turbo, gpt-4). Once this feature is available later this year, we will give priority access to GPT-3.5 Turbo and GPT-4 fine-tuning to users who previously fine-tuned older models. We acknowledge that migrating off of models that are fine-tuned on your own data is challenging. We will be providing support to users who previously fine-tuned models to make this transition as smooth as possible.
The OpenAI deprecation notice about the „embeddings models“ highlights that the embeddings vector method for indexing/matching content is not just subject to vendor lock-in, but also locks users into a specific model generation. This general issue is relevant to users of LlamaIndex, pgvector, etc.
OpenAI are saying that they‘ll cover the costs, but it‘s not clear if this just translates to „free ada-002 API use“ or additional costs of re-indexing everything, like for EC2, will be covered as well:
Users of older embeddings models (e.g., text-search-davinci-doc-001) will need to migrate to text-embedding-ada-002 by January 4, 2024. […] We recognize this is a significant change for developers using those older models. Winding down these models is not a decision we are making lightly. We will cover the financial cost of users re-embedding content with these new models. We will be in touch with impacted users over the coming days.