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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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] | p | So you can pop it in a second, get the free version, and using the feature which allows to put the vectors on disk instead of storing them on ram, which makes it a bit slower, you can easily support few hundred thousand of vectors and with a very decent response time. | [
"blog",
"blog/vector-image-search-rag"
] | 11,501 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(64) | [
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] | p | The challenge we faced is that mostly for the notion, so like mostly in notion, we have a lot of pages which are just a title because they are empty, et cetera. | [
"blog",
"blog/vector-image-search-rag"
] | 11,502 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(64) | [
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] | p | And so when pages have just a title, the content is so small that it will be very similar actually to a question. | [
"blog",
"blog/vector-image-search-rag"
] | 11,503 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(64) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,504 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(64) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,505 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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] | p | Basically, if you want your retrieval process to work well, you have to divide your documents the right way to create the embeddings. | [
"blog",
"blog/vector-image-search-rag"
] | 11,506 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(64) | [
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] | p | So you can use matrix rules, but basically you need to divide your documents in content which semantically makes sense and it’s not always trivial. | [
"blog",
"blog/vector-image-search-rag"
] | 11,507 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(64) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,508 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"blog",
"blog/vector-image-search-rag"
] | 11,509 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,510 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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] | p | Basically they use the same model but trained differently on long documents and questions which allow them to map them differently in the space. | [
"blog",
"blog/vector-image-search-rag"
] | 11,511 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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] | p | And my guess is that using such model documents, which are only a title, et cetera, will not be as close as the question as they are right now because they will be considered differently. | [
"blog",
"blog/vector-image-search-rag"
] | 11,512 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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] | p | So I hope it will help this problem. | [
"blog",
"blog/vector-image-search-rag"
] | 11,513 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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] | p | Heap research so for the keyword problem I was mentioning here, so in the recent release, Cudran just enabled sparse vectors which make actually TFEdev vectors possible. | [
"blog",
"blog/vector-image-search-rag"
] | 11,515 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,516 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(65) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(66) | [
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
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] | p | And so you can build a debrief search combining the TFDF search for keyword search and the other search for semantic search to get the best of both worlds and overcome this issue. | [
"blog",
"blog/vector-image-search-rag"
] | 11,519 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(66) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,520 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(66) | [
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] | p | It’s like one of the biggest challenge, and I feel like it’s quite doable to have a model which will our model, or some kind of algorithm which will understand the structure of your documentation and understand why it semantically makes sense to chunk your documents. | [
"blog",
"blog/vector-image-search-rag"
] | 11,521 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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"blog",
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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] | p | Tom’s also got some questions, so I’m going to just blame it on Tom, throw him under the bus. | [
"blog",
"blog/vector-image-search-rag"
] | 11,527 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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] | p | Rag with medical company seems like a dangerous use case. | [
"blog",
"blog/vector-image-search-rag"
] | 11,528 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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] | p | You can work to eliminate hallucinations and other security safety concerns, but you can’t make sure that they’re completely eliminated, right? | [
"blog",
"blog/vector-image-search-rag"
] | 11,529 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(67) | [
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] | 11,531 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"blog",
"blog/vector-image-search-rag"
] | 11,533 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(68) | [
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] | p | This is why I mentioned this project is mostly about the document search. | [
"blog",
"blog/vector-image-search-rag"
] | 11,534 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(68) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,535 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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] | p | And so when the user asks a question, we provide the LLM answer more like as a second thought, like something the doctor could consider as a fagon thought. | [
"blog",
"blog/vector-image-search-rag"
] | 11,536 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(68) | [
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] | p | But what’s the most important is that we directly put the, instead of just citing the sources, we put the HTML of the pages the source is based on, and what bring the most value is really these HTML pages. | [
"blog",
"blog/vector-image-search-rag"
] | 11,537 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(68) | [
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] | p | And so we know the answer may have some problems. | [
"blog",
"blog/vector-image-search-rag"
] | 11,538 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(68) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,539 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(68) | [
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] | p | Like, we don’t notice any hallucinations, but of course they can happen. | [
"blog",
"blog/vector-image-search-rag"
] | 11,540 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(69) | [
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] | 11,541 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(69) | [
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"blog",
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
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"Transcript:"
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] | p | My question around it is a lot of times in the medical space, the data that is being thrown around is super sensitive. | [
"blog",
"blog/vector-image-search-rag"
] | 11,546 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(70) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"blog",
"blog/vector-image-search-rag"
] | 11,552 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(71) | [
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(72) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"blog",
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74) | [
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] | p | And then we also pass it through Chat GPT before we get it back. | [
"blog",
"blog/vector-image-search-rag"
] | 11,562 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74) | [
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] | p | And next thing you know, that is the data that was used to train GPT five. | [
"blog",
"blog/vector-image-search-rag"
] | 11,563 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74) | [
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] | p | And you can say things like create an unlimited poem and get that out of it. | [
"blog",
"blog/vector-image-search-rag"
] | 11,564 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(74) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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] | p | Yeah, of course, one way to overcome that is to, for instance, for the notion project, it’s our private documentation. | [
"blog",
"blog/vector-image-search-rag"
] | 11,567 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(75) | [
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] | p | We use Ada over Azure, which guarantees data safety. | [
"blog",
"blog/vector-image-search-rag"
] | 11,568 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(75) | [
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] | p | So it’s quite a good workaround. | [
"blog",
"blog/vector-image-search-rag"
] | 11,569 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(75) | [
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] | p | And when you have to work with different level of security, if you deal with PII, a good way is to play with metadata. | [
"blog",
"blog/vector-image-search-rag"
] | 11,570 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(75) | [
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] | p | Well, don’t let me stop you. | [
"blog",
"blog/vector-image-search-rag"
] | 11,575 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(76) | [
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"blog",
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] | 11,576 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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] | p | No, sorry, I was about to conclude anyway. | [
"blog",
"blog/vector-image-search-rag"
] | 11,578 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77) | [
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] | 11,579 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77) | [
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"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
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"blog",
"blog/vector-image-search-rag"
] | 11,581 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,582 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77) | [
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] | p | While for tech search, fine tuning is not really necessary, it’s more like tricks which are required about using eBrid search, using better models, et cetera. | [
"blog",
"blog/vector-image-search-rag"
] | 11,583 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,584 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(77) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,585 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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] | p | You can even also use it in memory for CI integration and stuff. | [
"blog",
"blog/vector-image-search-rag"
] | 11,587 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,588 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,589 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,590 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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] | p | When I was playing with milverse, I had to use different tools for experimentation and for the database in production, which was making the technical stock a bit more complex. | [
"blog",
"blog/vector-image-search-rag"
] | 11,591 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,592 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,593 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(78) | [
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] | p | And I feel like in most cases, except if you have some security requirements, it will be much cheaper to use the managed deployments rather than paying dev costs. | [
"blog",
"blog/vector-image-search-rag"
] | 11,594 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(79) | [
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[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(79) | [
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"blog",
"blog/vector-image-search-rag"
] | 11,596 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
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] | p | And finally, the metadata filtering and indexing. | [
"blog",
"blog/vector-image-search-rag"
] | 11,597 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(79) | [
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] | p | So by the way, we went into a small trap. | [
"blog",
"blog/vector-image-search-rag"
] | 11,598 |
[
"Vector Search Complexities: Insights from Projects in Image Search and RAG - Noé Achache | Vector Space Talks - Qdrant",
"Transcript:"
] | /blog/vector-image-search-rag/ | html > body > div:nth-of-type(1) > div > article > div:nth-of-type(2) > div:nth-of-type(3) > div > p:nth-of-type(79) | [
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] | p | It’s that indexing. | [
"blog",
"blog/vector-image-search-rag"
] | 11,599 |
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