Claude

Due to the nature of the most modern ANN vector search algorithms, incrementally updating a vector index is a massive challenge. This is a well known “hard problem”. The issue here is that these indexes are carefully organized for fast lookups and any attempt to incrementally update them with new vectors will rapidly deteriorate the fast lookup pro... See more

You’ve got a vector database that has all the right database fundamentals you require, has the right incremental indexing strategy for your use case, has a good story around your metadata filtering needs, and will keep its index up-to-date with latencies you can tolerate. Awesome.

Your ML team (or maybe OpenAI) comes out with a new version of their... See more

1. Synthetic Data for Baseline Metrics¶

Synthetic data can be used to establish baseline precision and recall metrics for your reverse search. The simplest kind of synthetic data is to take existing text chunks, generate synthetic questions, and verify that when we query our synthetic questions, the sourced text chunk is retrieved correctly.

Benefi... See more

Eventually their database became a ticking time bomb ready to explode at any moment. The first instinct might be to beef up their Postgres instance, like me trying to get big at the gym. But there are physical limits to how much you can scale a single machine before costs increase exponentially. Moreover, query performance and maintenance processes

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7 must-know strategies to scale your database

Indexing:

Check the query patterns of your application and create the right indexes.

Materialized Views:

Pre-compute complex query results and store them for faster access.

Denormalization:

Reduce complex joins to improve query performance.

Vertical Scaling

Boost your database server by adding more CPU, RAM, or... See more

Livingston: Who did you learn things from at Google? Did you have mentors? Buchheit: I didn't know anything about building these large systems before working at Google. So I'd look at how different parts of Google work and sort of say, "Does that apply to us? Can we reuse that technique?"—since there was already a successful model of how

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