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Algolia Acquires Search.io

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Re: Algolia Acquires Search.io

#11

Post by gk1 »

O__________O wrote: post #10

From the Search.io homepage, “we are the only search technology supporting full upserts. Your updates are instantly live in milliseconds, no matter the scale.“ Anyone able to speculate how they were able to achieve this? Or for that matter beyond good sales & marketing - what technically gave them an edge that market actually needed?

This is easily disproved: Pinecone (disclaimer: I work there) also supports live index updates... "no matter the scale." I think their marketing folks have gone a little far, and I say that as a marketing person.

Re: Algolia Acquires Search.io

#12

Post by tomrod »

dustincoates wrote: post #4
swyx wrote: post #3

some interesting points from this other piece "While the acquisition price was undisclosed, media reports suggest Algolia paid more than $100 million for Search.io" https://www.businessnewsaustralia.com/articles/french-unicor... "Search.io’s mission is to “enable every organization to build smart search and discovery solutions.” The company was founded in 2014 by Hamish Ogilvy and David Howden (originally named Sajar…

Vector search is incredibly powerful on matching on context or similarity. For example, automobile and car are semantically similar and, and one will rank well for the other in a search. Vector search, though, isn't as good on handling typos and not good at all when it comes to as you type searching. Vehic won't match on auto, for example. We believe that there is use for each of these approaches and a use in a singl…

Do yall have a technical blog? I would love to both understand the problem and methods, domains yall cross (eg biometrics and fuzzy matching?), and how yall integrate in different industries.

A good search partner is hard to find. PageRank is fun and all, but I believe better methods exist these days.

Re: Algolia Acquires Search.io

#13

Post by O__________O »

evrydayhustling wrote: post #7
marcinzm wrote: post #6

Earlier quoted context omitted.

Aren't typos just a question of how you generate your vectors/embeddings? I'd be surprised if a transformer with a character level tokenizer trained on a representative source of data (ie: with typos) wouldn't be able to make sense of typos.

Can confirm. We use sentence-level transformer embeddings for (vector) search, clustering, and classification tasks. As an old school ML guy I've been amazed at how robust they are to typos, slang, punctuation, etc. However, I'm sure there are still applications where you don't have access to a robust embedding for your domain but can apply other techniques to deal with that domain's noise.

Here is decent intro to sentence level transformers & embeddings:

https://www.pinecone.io/learn/sentence-embeddings/

Re: Algolia Acquires Search.io

#15

Post by csmpltn »

> "... both keyword and semantic search in a single API. This new API platform is blazing fast, massively scalable, and, importantly, cost effective. No other vendor offers this today."

Where's the proof that "no other vendor offers this today"?

Re: Algolia Acquires Search.io

#16

Post by ddorian43 »

O__________O wrote: post #10

From the Search.io homepage, “we are the only search technology supporting full upserts. Your updates are instantly live in milliseconds, no matter the scale.“ Anyone able to speculate how they were able to achieve this? Or for that matter beyond good sales & marketing - what technically gave them an edge that market actually needed?

> Anyone able to speculate how they were able to achieve this?

vespa.ai does it and it's open source

Re: Algolia Acquires Search.io

#17

Post by marcinzm »

tomrod wrote: post #12
dustincoates wrote: post #4

Earlier quoted context omitted.

Vector search is incredibly powerful on matching on context or similarity. For example, automobile and car are semantically similar and, and one will rank well for the other in a search. Vector search, though, isn't as good on handling typos and not good at all when it comes to as you type searching. Vehic won't match on auto, for example. We believe that there is use for each of these approaches and a use in a singl…

Do yall have a technical blog? I would love to both understand the problem and methods, domains yall cross (eg biometrics and fuzzy matching?), and how yall integrate in different industries. A good search partner is hard to find. PageRank is fun and all, but I believe better methods exist these days.

There's two related problems here: finding relevant results and ranking those results. The first is historically done with massive inverted indexes. Page rank is for the second one of ranking those relevant results.

For the first part you can look into "embeddings" and "approximate nearest neighbor lookup" for the modern approaches. That said inverted indexes are still very popular.

The second one is generally called "learning to rank" so you can find a lot of things written on that topic. The biggest issue here imho is what training data you use which gives you examples of good rankings. The best algorithm trained on garbage will give you garbage.

Re: Algolia Acquires Search.io

#18

Post by peterstjohn »

swyx wrote: post #3

some interesting points from this other piece "While the acquisition price was undisclosed, media reports suggest Algolia paid more than $100 million for Search.io" https://www.businessnewsaustralia.com/articles/french-unicor... "Search.io’s mission is to “enable every organization to build smart search and discovery solutions.” The company was founded in 2014 by Hamish Ogilvy and David Howden (originally named Sajar…

It really does give you the best of both worlds - resistant to typos, handling synonyms without all the usual hand-written rules, but still able to handle direct searches like ISBNs.

(disclaimer: I work on Semantic Search at Lucidworks)

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