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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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] | p | So some relevant experience on vector DB is why I’m here today, because I did four projects, four vector soft projects, and I also wrote an article on how to choose your database in 2023, your vector database. | [
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"tags/vector-space-talks"
] | 11,700 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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"tags",
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] | 11,701 |
[
"Vector Space Talks - Qdrant",
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] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Space Talks - Qdrant",
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] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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] | p | Just to give you an idea of the kind of projects we can do with vector search. | [
"tags",
"tags/vector-space-talks"
] | 11,704 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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] | p | Then we will dive into the specificities of the image search project and then into the specificities of the text search project. | [
"tags",
"tags/vector-space-talks"
] | 11,705 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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] | p | So here are the four projects. | [
"tags",
"tags/vector-space-talks"
] | 11,706 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | So like it can be a lamp, it can be a piece of clothes, anything, we classify it and then we compare it to a large selection of similar objects to retrieve the most similar one to a large collection of sellable objects. | [
"tags",
"tags/vector-space-talks"
] | 11,712 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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] | p | So when agencies want to sell a property, like sometimes you have several agencies coming to take pictures of the same good. | [
"tags",
"tags/vector-space-talks"
] | 11,714 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Space Talks - Qdrant",
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] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
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] | p | I have been a victim of that. | [
"tags",
"tags/vector-space-talks"
] | 11,719 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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[
"Vector Space Talks - Qdrant",
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] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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[
"Vector Space Talks - Qdrant",
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] | p | Sorry to interrupt. | [
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"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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] | p | So now we know all about this project, let’s dive into them. | [
"tags",
"tags/vector-space-talks"
] | 11,730 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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] | p | And what’s amazing about it is that using the attention map, you can actually segment what’s important in the picture, although you haven’t told it specifically what’s important. | [
"tags",
"tags/vector-space-talks"
] | 11,734 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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"tags",
"tags/vector-space-talks"
] | 11,736 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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] | p | I’ll be happy to talk about it. | [
"tags",
"tags/vector-space-talks"
] | 11,738 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
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[
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[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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"tags",
"tags/vector-space-talks"
] | 11,744 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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"tags",
"tags/vector-space-talks"
] | 11,745 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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] | p | And also it’s known to be not very resilient with the changes of angles when it changes too much, et cetera. | [
"tags",
"tags/vector-space-talks"
] | 11,746 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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"tags/vector-space-talks"
] | 11,747 |
[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
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[
"Vector Space Talks - Qdrant",
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"tags",
"tags/vector-space-talks"
] | 11,752 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(23) | [
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"tags",
"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(23) | [
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] | p | So this is how it works and how it works. | [
"tags",
"tags/vector-space-talks"
] | 11,754 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(23) | [
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[
"Vector Space Talks - Qdrant",
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[
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"tags",
"tags/vector-space-talks"
] | 11,757 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(23) | [
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] | p | And then it will output the most similar lamp here. | [
"tags",
"tags/vector-space-talks"
] | 11,758 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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] | p | Now we’re going to try to analyze how this project went regarding the positive outcomes and the changes we faced. | [
"tags",
"tags/vector-space-talks"
] | 11,760 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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] | p | So you can get an off the shelf model and get started very quickly and start bringing value very quickly without having to go through all the fine tuning processes. | [
"tags",
"tags/vector-space-talks"
] | 11,762 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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] | p | What I mean here is that we’re going to get a box of the object, and in this box there will be a very noisy background which may disturb the matching process. | [
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"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Space Talks - Qdrant",
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] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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[
"Vector Space Talks - Qdrant",
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] | p | Regarding the vector database, this project started a while ago, and I think we chose the vector database something like a year and a half ago. | [
"tags",
"tags/vector-space-talks"
] | 11,767 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Space Talks - Qdrant",
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[
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"tags",
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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"tags",
"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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] | p | So the clients lost a lot of time and money in this deployment. | [
"tags",
"tags/vector-space-talks"
] | 11,775 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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] | p | So for furnitures like lamps, it’s fine. | [
"tags",
"tags/vector-space-talks"
] | 11,778 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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[
"Vector Space Talks - Qdrant",
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] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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[
"Vector Space Talks - Qdrant",
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] | p | And then in the matching, instead of matching trouser, which looks similar, it will just match trouser where in the product picture the person will be working as well, which is not really what we want. | [
"tags",
"tags/vector-space-talks"
] | 11,783 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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] | p | And the other challenges we faced is that we tried to fine tune the model, but our first fine tuning wasn’t very good because we tried to take an open source model and, and get the labels it had, like on different furnitures, clothes, et cetera, to basically train a model to classify the different classes and then remove the classification layer to just keep the embedding parts. | [
"tags",
"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(27) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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"tags",
"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(27) | [
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"tags",
"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(27) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(27) | [
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"tags/vector-space-talks"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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] | p | So it’s where it kind of is interesting to level to then be able to fine tune your model and make it learn more complex things according to your tasks. | [
"tags",
"tags/vector-space-talks"
] | 11,791 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(27) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(27) | [
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[
"Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(28) | [
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] | p | And concatenating all these scores together, you can get an embedding which you can put in a vector database for your vector search. | [
"tags",
"tags/vector-space-talks"
] | 11,797 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(28) | [
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] | p | It’s kind of hard to scale because you need to do a specific model and labeling for each type of object. | [
"tags",
"tags/vector-space-talks"
] | 11,798 |
[
"Vector Space Talks - Qdrant",
"Transcript:"
] | /tags/vector-space-talks/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div:nth-of-type(1) > div > div:nth-of-type(2) > article > p:nth-of-type(28) | [
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] | p | And I really wonder how Google lens does because their algorithm work very well. | [
"tags",
"tags/vector-space-talks"
] | 11,799 |
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