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Jina AI launches open-source 8k text embedding

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Re: Jina AI launches open-source 8k text embedding

#141

Post by itake »

LASR wrote: post #123
moralestapia wrote: post #32

Earlier quoted context omitted.

Oh, thanks for clarifying! Edit: looking at the press release, the improvement over old Ada is ... marginal? And Ada-01 is/was a poor performing model, tbh. I guess I'll have to run some tests, but at first sight it doesn't seem that wow-ey.

So just to be super clear, this is an embedding model. It generates no text. It’s not outputting words. Maybe I am assuming incorrectly, but I think the poor performance you are referring to is the old Ada completion model, where the output is text. That was poor indeed.

This article is not kind to the old ada embeddings model:

https://medium.com/@nils_reimers/openai-gpt-3-text-embedding...

If the new ada model only has marginal improvements, it seems open source is way to go.

Re: Jina AI launches open-source 8k text embedding

#142

Post by gar1t »

simonw wrote: post #72
Grimburger wrote: post #70

Earlier quoted context omitted.

> Have links gone out of fashion? Yes. You wrote far more words than needed to answer the comment, I did it for you instead.

One of the reasons I write so much stuff is so I can provide links to things I've written to answer relevant questions.

I liked your link a lot.

Re: Jina AI launches open-source 8k text embedding

#143

Post by smcl »

3cats-in-a-coat wrote: post #138

Great company name.

I'm gonna try to explain this because I thought the same thing, though you may enjoy it for another reason. Among Czech or other slavic software people - "jiná AI" could be like "another AI" and, to me at least, brings to mind the "yet another {thing}" naming convention (yacc = "yet another compiler compiler" for example).

Re: Jina AI launches open-source 8k text embedding

#144

Post by IanCal »

mike_ivanov wrote: post #103
simonw wrote: post #21

I just shipped a new llm-embed-jina plugin for my LLM tool which provides access to these new Jina models: https://github.com/simonw/llm-embed-jina Here's how to try it out. First, install LLM. Use pip or pipx or brew: brew install llm Next install the new plugin: llm install llm-embed-jina You can confirm the new models are now available to LLM by running: llm embed-models You should see a list that includes "jina-e…

JFYI, this is what happens on my M1 Macbook: $ brew install llm $ llm ModuleNotFoundError: No module named 'typing_extensions' Not sure where to report it.

Probably not this, but check with `which llm` what that's running. I had weird issues not matching the documentation but just had some other random python cli tool called llm I'd put in my home bin for and forgotten about it.

Re: Jina AI launches open-source 8k text embedding

#145

Post by darkwater »

magicalhippo wrote: post #130
losteric wrote: post #92

Earlier quoted context omitted.

The inference runtime software is open, the weights are an opaque binary. Publishing the training data, hyperparameters, process, etc - that would make the whole thing "open source".

The quake engine is still open source even though it doesn't come with the quake game assets, no? It seems unreasonable to require the training data just to be called open source, given it has similar copyright challenges as game assets. Of course, this wouldn't make the model reproducible. But that's different from open source.

Good example. And in fact you are calling the "engine" opensource, not the whole Quake game. The 'assets" in most "opensource" AI models are not available.

Re: Jina AI launches open-source 8k text embedding

#146

Post by woadwarrior01 »

Kubuxu wrote: post #140
3abiton wrote: post #122

Earlier quoted context omitted.

I wonder how the perfomance fair when context size is increased. Intuitively this should be higher, but some quantized models I've tested showed noticeably worst performance.

Your KV cache size is linear with context size which might put you tight on memory. There is also increased cost of recalculating KV cache of context window when the window has to move but this is close to being solved with streaming LLMs.

BERT style encoder-only models, like the embedding model being discussed here, don't need a KV cache for inference. A KV cache is only needed for efficient inference with encoder-decoder and decoder-only (aka GPT) models.

Re: Jina AI launches open-source 8k text embedding

#147

Post by EGreg »

darkwater wrote: post #145
magicalhippo wrote: post #130

Earlier quoted context omitted.

The quake engine is still open source even though it doesn't come with the quake game assets, no? It seems unreasonable to require the training data just to be called open source, given it has similar copyright challenges as game assets. Of course, this wouldn't make the model reproducible. But that's different from open source.

Good example. And in fact you are calling the "engine" opensource, not the whole Quake game. The 'assets" in most "opensource" AI models are not available.

Imagine if the Telegram client was open source but not the backend.

Imagine if Facebook open-sourced their front-end libraries like React but not the back-end.

Imagine if Twitter or Google didn’t publish its Algorithm for how they rank things to display to different people.

You don’t need to imagine. That’s exactly what’s happening! Would you call them open source because their front end is open source? Could you host your own back end on your choice of computers?

No. That’s why I even started https://qbix.com/platform

Re: Jina AI launches open-source 8k text embedding

#148

Post by ekianjo »

okaram wrote: post #86
SOLAR_FIELDS wrote: post #71

Earlier quoted context omitted.

The very definition of what constitutes open source is being called into question in these kinds of discussions about AI. Without the training details and the weights being made fully open it’s hard to really call something truly open, even if it happens to meet some arbitrary definition of “open source”. A good definition of “truly open” is whether the exact same results can be reproduced by someone with no extra in…

Notice you are creating your own arbitrary definition of 'truly open', which IMHO corresponds more with 'reproducible'. We already have a definition of open source. I don't see any reason to change it.

Weights are like binaries. They are not code. It would make more sense to put it under a creative commons license

Re: Jina AI launches open-source 8k text embedding

#149

Post by EGreg »

richardw wrote: post #106
SOLAR_FIELDS wrote: post #71

Earlier quoted context omitted.

The very definition of what constitutes open source is being called into question in these kinds of discussions about AI. Without the training details and the weights being made fully open it’s hard to really call something truly open, even if it happens to meet some arbitrary definition of “open source”. A good definition of “truly open” is whether the exact same results can be reproduced by someone with no extra in…

So if someone includes images in their project they need to tell you every brush stroke that led to the final image? All sorts of intangibles end up in open source projects. This isn’t a science experiment that needs replication. They’re not trying to prove how they came up with the image/code/model.

It’s more like someone giving you an open source front end client, but not giving you a way to host your own backend.

Look into Affero GPL. Images are inert static assets. Here we are talking about the back end engine. The fact that neural networks and model weights are non-von-neumann architecture doesn’t negate the fact that they are executable code and not just static assets!

Re: Jina AI launches open-source 8k text embedding

#150

Post by Gasp0de »

burcs wrote: post #3

This is great news! It feels like open-source is closing the gap with "Open"AI which is really exciting, and the acceleration towards parity is faster than more advancements made on the closed source models. Maybe it's wishful thinking though?

They compare it to OpenAI's ada model though, which is light-years away from ChatGPT.
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