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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(13) | [
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(14) | [
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[
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[
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] | p | Thank you for that. | [
"tags",
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[
"LLM - Qdrant",
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] | p | I really like your joke of the carrier pigeon. | [
"tags",
"tags/llm"
] | 13,576 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(14) | [
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] | p | Is it a geni carrier pigeon with multiple areas and h 100 attached to it? | [
"tags",
"tags/llm"
] | 13,577 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(15) | [
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] | p | Those are the expensive carrier pigeons. | [
"tags",
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[
"LLM - Qdrant",
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[
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[
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"tags",
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(16) | [
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[
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] | p | I think that’s a great segue. | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(16) | [
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] | p | I usually tell people that I’m going to teach you all how to be a GPU poor AI gap person, and my job is to basically teach everyone, or the thesis of my organization is also, how can we build powerful solutions, LLM powered solutions by using open source products and open source llms and architectures so that we can stretch the dollar as much as possible. | [
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] | 13,587 |
[
"LLM - Qdrant",
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] | p | That’s been my thesis and I have always pushed for open source because they’ve done some great job over there and they are coming in close to pretty much at par of what the industry standard is. | [
"tags",
"tags/llm"
] | 13,588 |
[
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] | p | But I digress. | [
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[
"LLM - Qdrant",
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] | p | I’m here to talk about the future of search and copilots and just the overall experience which we are looking with llms. | [
"tags",
"tags/llm"
] | 13,591 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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[
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[
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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] | p | I have quite a few years of experience in machine learning. | [
"tags",
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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"tags",
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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"tags",
"tags/llm"
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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] | p | I have had the experience of teaching at multiple universities and that sort of experience has really helped me do better at what I do, because when you can teach something, you actually truly understand that. | [
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[
"LLM - Qdrant",
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(17) | [
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[
"LLM - Qdrant",
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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[
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] | p | So we started almost a year ago, Char GPT came into our lives and almost all of a sudden we started using it. | [
"tags",
"tags/llm"
] | 13,604 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | And I think in January, February, March, it was just an explosion of usage. | [
"tags",
"tags/llm"
] | 13,605 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | And now we know all the different things that have been going on and we’ve seen peripheration of a lot of startups that have come in this space. | [
"tags",
"tags/llm"
] | 13,606 |
[
"LLM - Qdrant",
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] | p | Some of them are wrappers, some of them have done a lot, have a lot more motor. | [
"tags",
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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"tags",
"tags/llm"
] | 13,608 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | I don’t think we even know how many ways we can use charge GBT, but most often it’s just been text generation, one form or the other. | [
"tags",
"tags/llm"
] | 13,609 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | And that is what the focus has been. | [
"tags",
"tags/llm"
] | 13,610 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(18) | [
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] | p | But if we look deeper, the llms that we know, they also can help us with a very important part, something which is called complex search. | [
"tags",
"tags/llm"
] | 13,611 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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"tags",
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[
"LLM - Qdrant",
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"tags",
"tags/llm"
] | 13,613 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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"tags",
"tags/llm"
] | 13,614 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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[
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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] | p | What you see is that their search is really basic and this is an opportunity for a lot of companies to actually create a great search experience for the users with a multi tier engagement model. | [
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"tags/llm"
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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] | p | So you basically make a request. | [
"tags",
"tags/llm"
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(19) | [
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] | p | I would like to buy a Nike blue t shirt specially designed for golf with all these features which I need and at a reasonable price point. | [
"tags",
"tags/llm"
] | 13,620 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
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[
"LLM - Qdrant",
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] | p | That is the power of what we have at hand with complex search. | [
"tags",
"tags/llm"
] | 13,623 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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"tags/llm"
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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"tags",
"tags/llm"
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
"LLM - Qdrant",
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] | p | So I’ll share this example. | [
"tags",
"tags/llm"
] | 13,628 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(20) | [
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[
"LLM - Qdrant",
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"tags",
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[
"LLM - Qdrant",
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"tags/llm"
] | 13,632 |
[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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[
"LLM - Qdrant",
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] | p | I basically just want to see almost everything. | [
"tags",
"tags/llm"
] | 13,634 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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] | p | And then when I hit submit, the great thing what it does is that it sort of becomes a starting point for something that would have taken me quite a while to put it together, sort of takes all my information and generates an itinerary. | [
"tags",
"tags/llm"
] | 13,635 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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] | p | Now see what’s different about this. | [
"tags",
"tags/llm"
] | 13,636 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(21) | [
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[
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[
"LLM - Qdrant",
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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] | p | Hamza Farooq: | [
"tags",
"tags/llm"
] | 13,640 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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] | p | GPT if you’ve started this year, you would say seven day itinerary to London and it would identify a few things over here. | [
"tags",
"tags/llm"
] | 13,641 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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[
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] | p | And this is the truest form of taking complex search and putting that into production and sort of create a great experience for the user so that they can understand what they can select. | [
"tags",
"tags/llm"
] | 13,644 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(22) | [
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] | p | Going to pause here. | [
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[
"LLM - Qdrant",
"Transcript:"
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] | p | Is there any question or I can help answer anything? | [
"tags",
"tags/llm"
] | 13,647 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(23) | [
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"tags",
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(23) | [
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[
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[
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[
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] | p | I didn’t even realize that this is already live, but it’s 100% what a travel agent would be doing. | [
"tags",
"tags/llm"
] | 13,652 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(24) | [
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[
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] | p | So they have built a user experience which takes 10 seconds to build. | [
"tags",
"tags/llm"
] | 13,655 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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] | p | You have this macro task that I want to plan a vacation in Paris, I want to plan a vacation to London. | [
"tags",
"tags/llm"
] | 13,657 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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"tags",
"tags/llm"
] | 13,658 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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] | p | And when you reach to an individual atomic subtask, it is able to divide it into actions which can be taken. | [
"tags",
"tags/llm"
] | 13,659 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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] | p | So there’s a task decomposition and a task recognition scene that is going on. | [
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[
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"tags",
"tags/llm"
] | 13,661 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(25) | [
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"tags",
"tags/llm"
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[
"LLM - Qdrant",
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[
"LLM - Qdrant",
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[
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[
"LLM - Qdrant",
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"tags",
"tags/llm"
] | 13,666 |
[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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] | p | It’s an atomic thing. | [
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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] | p | Do you want to get a flight? | [
"tags",
"tags/llm"
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[
"LLM - Qdrant",
"Transcript:"
] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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[
"LLM - Qdrant",
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] | /tags/llm/ | html > body > div:nth-of-type(1) > div > section > div > div > div > div > div:nth-of-type(2) > div > div > div > div:nth-of-type(2) > article > p:nth-of-type(26) | [
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[
"LLM - Qdrant",
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] | p | What kind of overall grade do I need to go to a glacier? | [
"tags",
"tags/llm"
] | 13,671 |
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