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[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
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p
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It had to have a very low latency and it have to support this randomly spatter.
|
[
"blog",
"blog/binary-quantization"
] | 17,400 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
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p
|
So basically we can only do it efficiently if we store all the vectors either in very fast solid state disks or if we use actual RAM to store everything.
|
[
"blog",
"blog/binary-quantization"
] | 17,401 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
|
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p
|
And RAM is not cheap these days, especially considering that the size of vectors increases with each new version of the model.
|
[
"blog",
"blog/binary-quantization"
] | 17,402 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
|
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p
|
And for example, OpenAI model is already more than 1000 dimensions.
|
[
"blog",
"blog/binary-quantization"
] | 17,403 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
|
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p
|
So you can imagine one vector is already 6 data, no matter how long your text is, and it’s just becoming more and more expensive with the advancements of new models and so on.
|
[
"blog",
"blog/binary-quantization"
] | 17,404 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
|
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p
|
So in order to actually fight this, in order to compensate for the growth of data requirement, what we propose to do, and what we already did with different other quantization techniques is we actually compress vectors into quantized vector storage, which is usually much more compact for the in memory representation.
|
[
"blog",
"blog/binary-quantization"
] | 17,405 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
|
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p
|
For example, on one of the previous releases we have scalar quantization and product quantization, which can compress up to 64 times the size of the vector.
|
[
"blog",
"blog/binary-quantization"
] | 17,406 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(15)
|
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p
|
And we only keep in fast storage these compressed vectors.
|
[
"blog",
"blog/binary-quantization"
] | 17,407 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(16)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,408 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(16)
|
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p
|
We retrieve them and get a list of candidates which will later rescore using the original vectors.
|
[
"blog",
"blog/binary-quantization"
] | 17,409 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(16)
|
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p
|
And the benefit here is this reordering or rescoring process actually doesn’t require any kind of sequential or random access to data, because we already know all the IDs we need to rescore, and we can efficiently read it from the disk using asynchronous I O, for example, and even leverage the advantage of very cheap network mounted disks.
|
[
"blog",
"blog/binary-quantization"
] | 17,410 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(16)
|
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p
|
And that’s the main benefit of quantization.
|
[
"blog",
"blog/binary-quantization"
] | 17,411 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(17)
|
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p
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Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,412 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(17)
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p
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I have a few questions off the back of this one, being just a quick thing, and I’m wondering if we can double benefit by using this binary quantization, but also if we’re using smaller models that aren’t the GBTs, will that help?
|
[
"blog",
"blog/binary-quantization"
] | 17,413 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(18)
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,414 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(18)
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p
|
Right.
|
[
"blog",
"blog/binary-quantization"
] | 17,415 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(18)
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p
|
So not all models are as big as OpenAI, but what we see, the trend in this area, the trend of development of different models, indicates that they will become bigger and bigger over time.
|
[
"blog",
"blog/binary-quantization"
] | 17,416 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(18)
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p
|
Just because we want to store more information inside vectors, we want to have larger context, we want to have more detailed information, more detailed separation and so on.
|
[
"blog",
"blog/binary-quantization"
] | 17,417 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(18)
|
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p
|
This trend is obvious if like five years ago the usual size of the vector was 100 dimensions now the usual size is 700 dimensions, so it’s basically.
|
[
"blog",
"blog/binary-quantization"
] | 17,418 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(19)
|
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p
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Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,419 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(19)
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p
|
Preparing for the future while also optimizing for today.
|
[
"blog",
"blog/binary-quantization"
] | 17,420 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(20)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,421 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(20)
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p
|
Right?
|
[
"blog",
"blog/binary-quantization"
] | 17,422 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(21)
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Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,423 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(21)
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p
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Yeah.
|
[
"blog",
"blog/binary-quantization"
] | 17,424 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(21)
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p
|
Okay, so you mentioned on here oversampling.
|
[
"blog",
"blog/binary-quantization"
] | 17,425 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(21)
|
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p
|
Can you go into that a little bit more and explain to me what that is?
|
[
"blog",
"blog/binary-quantization"
] | 17,426 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,427 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
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p
|
Yeah, so oversampling is a special technique we use to control precision of the search in real time, in query time.
|
[
"blog",
"blog/binary-quantization"
] | 17,428 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
|
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p
|
And the thing is, we can internally retrieve from quantized storage a bit more vectors than we actually need.
|
[
"blog",
"blog/binary-quantization"
] | 17,429 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
|
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p
|
And when we do rescoring with original vectors, we assign more precise score.
|
[
"blog",
"blog/binary-quantization"
] | 17,430 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
|
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p
|
And therefore from this overselection, we can pick only those vectors which are actually good for the user.
|
[
"blog",
"blog/binary-quantization"
] | 17,431 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
|
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p
|
And that’s how we can basically control accuracy without rebuilding index, without changing any kind of parameters inside the stored data structures.
|
[
"blog",
"blog/binary-quantization"
] | 17,432 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(22)
|
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p
|
But we can do it real time in just one parameter change of the search query itself.
|
[
"blog",
"blog/binary-quantization"
] | 17,433 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(23)
|
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p
|
Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,434 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(23)
|
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p
|
I see, okay, so basically this is the quantization.
|
[
"blog",
"blog/binary-quantization"
] | 17,435 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(23)
|
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p
|
And now let’s dive into the binary quantization and how it works.
|
[
"blog",
"blog/binary-quantization"
] | 17,436 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,437 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
|
Right, so binary quantization is actually very simple.
|
[
"blog",
"blog/binary-quantization"
] | 17,438 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
|
The main idea that we convert the float point elements of the vector into binary representation.
|
[
"blog",
"blog/binary-quantization"
] | 17,439 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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] |
p
|
So it’s either zero or one, depending if the original element is positive or negative.
|
[
"blog",
"blog/binary-quantization"
] | 17,440 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
|
And by doing this we can approximate dot production or cosine similarity, whatever metric you use to compare vectors with just hemming distance, and hemming distance is turned to be very simple to compute.
|
[
"blog",
"blog/binary-quantization"
] | 17,441 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
|
It uses only two most optimized CPU instructions ever.
|
[
"blog",
"blog/binary-quantization"
] | 17,442 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
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It’s Pixor and Popcount.
|
[
"blog",
"blog/binary-quantization"
] | 17,443 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
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p
|
Instead of complicated float point subprocessor, you only need those tool.
|
[
"blog",
"blog/binary-quantization"
] | 17,444 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(24)
|
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p
|
It works with any register you have, and it’s very fast.
|
[
"blog",
"blog/binary-quantization"
] | 17,445 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(25)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,446 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(25)
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p
|
It uses very few CPU cycles to actually produce a result.
|
[
"blog",
"blog/binary-quantization"
] | 17,447 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(25)
|
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p
|
That’s why binary quantization is over 30 times faster than regular product.
|
[
"blog",
"blog/binary-quantization"
] | 17,448 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(25)
|
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p
|
And it actually solves the problem of complicated index building, because this computation of dot products is the main source of computational requirements for HNSW.
|
[
"blog",
"blog/binary-quantization"
] | 17,449 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(26)
|
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Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,450 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(26)
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p
|
So if I’m understanding this correctly, it’s basically taking all of these numbers that are on the left, which can be, yes, decimal numbers.
|
[
"blog",
"blog/binary-quantization"
] | 17,451 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(27)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,452 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(27)
|
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p
|
On the left you can see original vector and it converts it in binary representation.
|
[
"blog",
"blog/binary-quantization"
] | 17,453 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(27)
|
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p
|
And of course it does lose a lot of precision in the process.
|
[
"blog",
"blog/binary-quantization"
] | 17,454 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(27)
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p
|
But because first we have very large vector and second, we have oversampling feature, we can compensate for this loss of accuracy and still have benefit in both speed and the size of the storage.
|
[
"blog",
"blog/binary-quantization"
] | 17,455 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(28)
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p
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Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,456 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(28)
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p
|
So if I’m understanding this correctly, it’s basically saying binary quantization on its own probably isn’t the best thing that you would want to do.
|
[
"blog",
"blog/binary-quantization"
] | 17,457 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(28)
|
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p
|
But since you have these other features that will help counterbalance the loss in accuracy.
|
[
"blog",
"blog/binary-quantization"
] | 17,458 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(28)
|
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p
|
You get the speed from the binary quantization and you get the accuracy from these other features.
|
[
"blog",
"blog/binary-quantization"
] | 17,459 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(29)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,460 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(29)
|
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p
|
Right.
|
[
"blog",
"blog/binary-quantization"
] | 17,461 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(29)
|
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p
|
So the speed boost is so overwhelming that it doesn’t really matter how much over sampling is going to be, we will still benefit from that.
|
[
"blog",
"blog/binary-quantization"
] | 17,462 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(30)
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Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,463 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(30)
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p
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Yeah.
|
[
"blog",
"blog/binary-quantization"
] | 17,464 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(30)
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p
|
And how much faster is it?
|
[
"blog",
"blog/binary-quantization"
] | 17,465 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(30)
|
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p
|
You said that, what, over 30 times faster?
|
[
"blog",
"blog/binary-quantization"
] | 17,466 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(31)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,467 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(31)
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p
|
Over 30 times and some benchmarks is about 40 times faster.
|
[
"blog",
"blog/binary-quantization"
] | 17,468 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
|
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p
|
Demetrios:
|
[
"blog",
"blog/binary-quantization"
] | 17,469 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
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p
|
Wow.
|
[
"blog",
"blog/binary-quantization"
] | 17,470 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
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p
|
Yeah, that’s huge.
|
[
"blog",
"blog/binary-quantization"
] | 17,471 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
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p
|
And so then on the bottom here you have dot product versus hammering distance.
|
[
"blog",
"blog/binary-quantization"
] | 17,472 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
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p
|
And then there’s.
|
[
"blog",
"blog/binary-quantization"
] | 17,473 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
|
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p
|
Yeah, hamming.
|
[
"blog",
"blog/binary-quantization"
] | 17,474 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
|
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p
|
Sorry, I’m inventing words over here on your slide.
|
[
"blog",
"blog/binary-quantization"
] | 17,475 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(32)
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p
|
Can you explain what’s going on there?
|
[
"blog",
"blog/binary-quantization"
] | 17,476 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,477 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
|
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p
|
Right, so dot production is the metric we usually use in comparing a pair of vectors.
|
[
"blog",
"blog/binary-quantization"
] | 17,478 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
|
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p
|
It’s basically the same as cosine similarity, but this normalization on top.
|
[
"blog",
"blog/binary-quantization"
] | 17,479 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
|
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p
|
So internally, both cosine and dot production actually doing only dot production, that’s usual metric we use.
|
[
"blog",
"blog/binary-quantization"
] | 17,480 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
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p
|
And in order to do this operation, we first need to multiply each pair of elements to the same element of the other vector and then add all these multiplications in one number.
|
[
"blog",
"blog/binary-quantization"
] | 17,481 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
|
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p
|
It’s going to be our score instead of this in binary quantization, in binary vector, we do XOR operation and then count number of ones.
|
[
"blog",
"blog/binary-quantization"
] | 17,482 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(33)
|
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p
|
So basically, Hemming distance is an approximation of dot production in this binary space.
|
[
"blog",
"blog/binary-quantization"
] | 17,483 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(34)
|
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Demetrios:
|
[
"blog",
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] | 17,484 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(34)
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Excellent.
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[
"blog",
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] | 17,485 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(34)
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p
|
Okay, so then it looks simple enough, right?
|
[
"blog",
"blog/binary-quantization"
] | 17,486 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(34)
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p
|
Why are you implementing it now after much more complicated product quantization?
|
[
"blog",
"blog/binary-quantization"
] | 17,487 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,488 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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p
|
It’s actually a great question.
|
[
"blog",
"blog/binary-quantization"
] | 17,489 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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] |
p
|
And the answer to this is binary questization looked too simple to be true, too good to be true.
|
[
"blog",
"blog/binary-quantization"
] | 17,490 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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p
|
And we thought like this, we tried different things with open source models that didn’t work really well.
|
[
"blog",
"blog/binary-quantization"
] | 17,491 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
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p
|
But everything changed when we actually tried binary quantization with OpenAI model.
|
[
"blog",
"blog/binary-quantization"
] | 17,492 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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p
|
And it turned out that OpenAI model has very good compatibility with this type of quantization.
|
[
"blog",
"blog/binary-quantization"
] | 17,493 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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p
|
Unfortunately, not every model have as good compatibility as OpenAI.
|
[
"blog",
"blog/binary-quantization"
] | 17,494 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
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p
|
And to be honest, it’s not yet absolutely clear for us what makes models compatible and whatnot.
|
[
"blog",
"blog/binary-quantization"
] | 17,495 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(35)
|
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p
|
We do know that it correlates with number of dimensions, but it is not the only factor.
|
[
"blog",
"blog/binary-quantization"
] | 17,496 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(36)
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p
|
Andrey Vasnetsov:
|
[
"blog",
"blog/binary-quantization"
] | 17,497 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(36)
|
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p
|
So there is some secret source which exists and we should find it, which should enable models to be compatible with binary quantization.
|
[
"blog",
"blog/binary-quantization"
] | 17,498 |
[
"Binary Quantization - Andrey Vasnetsov | Vector Space Talks - Qdrant",
"Transcript:"
] |
/blog/binary-quantization/
|
html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(36)
|
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p
|
And I think it’s actually a future of this space because the benefits of this hemming distance benefits of binary quantization is so great that it makes sense to incorporate these tricks on the learning process of the model to make them more compatible.
|
[
"blog",
"blog/binary-quantization"
] | 17,499 |
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