What underlying tech does Algolia use? Elastic search?
Algolia raises $110M for its search-as-a-service
101–110 of 115 posts
Re: Algolia raises $110M for its search-as-a-service
#102It's interesting to see this valuation on search as a service, given the leader, Elastic, is in obvious valuation trouble. The market is unimpressed: the Elastic stock hasn't net moved higher since mid January (so most of the time they've been public). Just take a look at the actual business performance of Elastic. $271m in sales for the last fiscal year. Negative $101 million operating loss. Pretty bad, although not…
Maybe Elastic isn't growing because Algolia is eating their lunch?
Re: Algolia raises $110M for its search-as-a-service
#103Re: Algolia raises $110M for its search-as-a-service
#104Earlier quoted context omitted.
Except this would be prohibitively expensive. The labor cost of those specialized employees as consultants would be huge.
So you are saying it’s too expensive to hire those specialists but you need those specialists to setup a working search solution? Is your stance that only companies that can afford a bespoke solution should implement search?
Re: Algolia raises $110M for its search-as-a-service
#105I’ve always had a hard time understanding the value proposition in the same way I don’t understand the value proposition of e.g. AWS Rekognition. Paying per use certainly doesn’t make sense, because it has to be qualified by the accuracy you get per use. And there’s no serious way to understand the accuracy you get per use (on your specific unusual distribution of queries) without employing the expensive ML / stats e…
> I’ve always had a hard time understanding the value proposition in the same way I don’t understand the value proposition of e.g. AWS Rekognition. I signed up for AWS specifically to use Rekognition. I use it to screen alerts from my security cameras. In short, Blue Iris detects motion, a Node-RED flow grabs an image and uses Rekognition to see what's in it, if there's a person detected the Node-RED flow notifies me…
But you’re just proving my point. It wouldn’t make sense to use Rekognition unless you had someone with skills to assess the classifier accuracy in the context of your specific problem. For example, it seems like your loss function places an asymmetrically higher cost on false negatives. (Incidentally, it’s interesting you claim it hasn’t produced a false negative ... did you watch every frame of video and make sure?)
If you replace your simple one man operation with a simple loss function on an amount of data you can manually evaluate with instead a complex computer vision workflow, say where face or person detection has legal consequences for a company that sells or licenses stock photography, or an image or video search tool trying to avoid surfacing porn or pirated content, etc. then Rekognition becomes no longer useful, because you’ll need not just one person doing cursory evaluation of false negatives, but a team of people building out a benchmark-like battery of automated evaluations with probably IoU metrics in addition to classifier metrics and will need to figure out how many errors they can tolerate in some cost budget combined with the normal cost budget of usage to Rekognition.
Basically, for some tiny hobbyist use case, I guess it’s fine (though really you could literally just load some Keras model pre-trained on imagenet or some off the shelf version of yolo and save yourself $5/mo) but the value proposition falls apart as soon as the cost function becomes a complicated business one.
Re: Algolia raises $110M for its search-as-a-service
#106Earlier quoted context omitted.
I’m saying in my experience there is no such thing as one singular “decent solution” for search. It varies enormously from use case to use case, customer cohort to customer cohort, etc. To even know if you’re buying a decent solution from Algolia or not, you’d already have to hire pretty much all the same staff you’d have to hire to more cost-effectively build it in-house. I think the fundamental myth, just like with…
I do both search and ML solutions in the area that Rekognition targets. In both cases they are great 80/20 solutions (actually Algoria is more like a 95/5 solution in most cases).
Re: Algolia raises $110M for its search-as-a-service
#107Earlier quoted context omitted.
Simply sorting by date doesn't really seem to be that useful either. For example, the poster below showed the following link for the "ml" query: https://hn.algolia.com/?dateRange=all&page=0&prefix=true&que... . If you look at the results, the first 2 results only matched part of the poster's username and many of the top results here are empty threads which are not that useful since HN is mostly for discussions. To be…
️ oops, a typo in the query, but why they have query correction for popularity based, not date based?
Re: Algolia raises $110M for its search-as-a-service
#108Earlier quoted context omitted.
It's only as good as the HN team have configured the ranking and other algolia settings. Be nice for them to expose these.
Pretty sure HN's search is implemented by Algolia themselves. It's served from algolia.com.
Re: Algolia raises $110M for its search-as-a-service
#109Side question: how interesting and flexible is algolia as a replacement of a custom solr setup? I don't like the HN search and never heard that it is in use for larger data sets.
Re: Algolia raises $110M for its search-as-a-service
#110Incase someone doesn't know already: they have a HN search too! https://hn.algolia.com/
search for e.g 'microsoft' -> ~120k results change sort by popularity to sort by date -> ~30k results I don't really understand how sorting can affect the number of results. Btw youtube search does this too.