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by Thaxll 562 days ago
It feels like everyone re-implement the same application, searching text in language x.y.z has been done a million times, search speed in not a problem so what differenciate this solution with the dozen+ mature ones.

The speed looks great but isn't everything else already fast enough?
2 comments
wolfgarbe 562 days ago
Its not just about speed. Speed reflects efficiency. Efficiency is needed to serve more queries in parallel, to search within exponentially growing data, with less expensive hardware, and fewer servers, consuming less energy. Therefore the pursuit for efficiency never gets outdated and has no limit.
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sdesol 562 days ago
In addition to what you said, faster searches can also provide different search options. For example, if you can execute five similar searches in the same time that it would take to execute one. You now have the option to ask "Can I leverage five similar searches to produce better results" and if the answer is yes, you can now provide better answers and still keep the same user experience.

Where I really think faster searches will come into play is with AI. There is nothing energy efficient about how LLM work and I really think Enterprise will focus on using LLM to generate as many Q and A pairs during off peak energy hours and using a hybrid search that can bridge semantic (vector) and text. I think for Enterprise the risk of hallucinations (even with RAG) will be too great and fall back to traditional search, but with a better user experience.

Based on the README, it looks like vector search is not supported or planned, but it would be interesting to see if SeekStorm can do this more efficiently than Lucene/OpenSearch and others. I only dabbled in the search space, so I don't know how complex this would be, but I think SeekStorm can become a killer search solution if it can support both.

Edit: My bad, it looks like vector search is PoC.

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jamil7 562 days ago
Software is currently extremely inefficient, driven by years of increasingly powerful cheap hardware. Once that starts to slow it makes sense that we start squeezing efficiency out of software again. We’ve also seen in the last 20 years the rise of languages that make writing performant, higher-level software a lot easier.

We’re also at a point where cloud compute is consuming a significant amount of energy globally.

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