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0 pointse1g2y ago0 comments

LLMs and embedding models are certainly different, but it's a useful benchmark to calibrate expectations. OpenAI released text-embedding-ada-002 a year ago, and they describe the ada model as[1] "the original GPT-3 base model [...] capable of very simple tasks, usually the fastest model in the GPT-3 series".

It's fair to expect GPT3-level results - not GPT 3.5 and certainly not open-source tiny GPT4 as some might think when they read "rivaling OpenAI".

[1] https://platform.openai.com/docs/models/whisper

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simonw2y ago

No, you're confusing two things here.

"text-ada-001" is LLM in the GPT3 family, described as "Capable of very simple tasks, usually the fastest model in the GPT-3 series, and lowest cost"

"text-embedding-ada-002" is entirely different - that page describes it as "Our second generation embedding model, text-embedding-ada-002 is a designed to replace the previous 16 first-generation embedding models at a fraction of the cost."

e1gOP2y ago

OpenAI doesn't say directly what text-embedding-ada-002 is, but in the release blog post they show that performance is comparable to davinci/curie, which places it firmly in the universe of GPT3. I understand it's not a straight line comparison, but to me it's still a useful mental heuristic about what to expect.

[1] https://openai.com/blog/new-and-improved-embedding-model (see "Model improvements")

simonw2y ago

You mean this table here?

    text-embedding-ada-002     53.3
    text-search-davinci-*-001 52.8
    text-search-curie-*-001     50.9
    text-search-babbage-*-001 50.4
    text-search-ada-*-001     49.0

That's not comparing it to the davinci/curie/babbage GPT3 models, it's comparing to the "search-text-*" family.

Those were introduced in https://openai.com/blog/introducing-text-and-code-embeddings as the first public release of embeddings models from OpenAI.

> We’re releasing three families of embedding models, each tuned to perform well on different functionalities: text similarity, text search, and code search. The models take either text or code as input and return an embedding vector.

It's not at all clear to me if there's any relationship between those and the GPT3 davinci/curie/babbage/ada models.

My guess is that OpenAI's naming convention back then was "davinci is the best one, then curie, then babbage, then ada".

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helloplanets2y ago

Reading through that article, the specific Davinci/Curie models they seem to be referring to are called the following: 'text-search-davinci-001', 'text-search-curie-001', 'text-similarity-davinci-001' and 'text-similarity-curie-001'.

Are you sure these have anything to do with 'text-davinci-003' or 'text-curie-001'?

Will have to agree with everyone here that OpenAI is good at being extremely confusing. It seems like the logic might be something along the lines of the 'text-search' portion being the actual type of the model, while the 'curie-001' / '<name>-<number>' format is just a personalized way of expressing the version of that type of model. And the whole 'GPT<number>' category used to be a sort family of models, but now they've just switched it to the actual name of the newer gargantuan LLMs. Then, because the 'GPT<number>' models are now that different thing altogether these days, the newest 'text-embedding' model is just named 'ada-<number>' because it's on that iteration of the 'text-embedding' type of model, adhering to the older principle of naming their models? Not sure, ha. Definitely feels like doing some detective work.

minimaxir2y ago

tl;dr OpenAI is bad at product naming.

minimaxir2y ago

When people talked about GPT-3 they always referred to davinci which is the largest model, not ada.

j / k navigate · click thread line to collapse

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simonw2y ago

No, you're confusing two things here.

"text-ada-001" is LLM in the GPT3 family, described as "Capable of very simple tasks, usually the fastest model in the GPT-3 series, and lowest cost"

e1gOP2y ago

[1] https://openai.com/blog/new-and-improved-embedding-model (see "Model improvements")

simonw2y ago

You mean this table here?

    text-embedding-ada-002     53.3
    text-search-davinci-*-001 52.8
    text-search-curie-*-001     50.9
    text-search-babbage-*-001 50.4
    text-search-ada-*-001     49.0

That's not comparing it to the davinci/curie/babbage GPT3 models, it's comparing to the "search-text-*" family.

Those were introduced in https://openai.com/blog/introducing-text-and-code-embeddings as the first public release of embeddings models from OpenAI.

It's not at all clear to me if there's any relationship between those and the GPT3 davinci/curie/babbage/ada models.

My guess is that OpenAI's naming convention back then was "davinci is the best one, then curie, then babbage, then ada".

1 more reply

helloplanets2y ago

Are you sure these have anything to do with 'text-davinci-003' or 'text-curie-001'?

minimaxir2y ago

tl;dr OpenAI is bad at product naming.

minimaxir2y ago

When people talked about GPT-3 they always referred to davinci which is the largest model, not ada.

j / k navigate · click thread line to collapse