A lot of folks know about Chesterton's fence these days, but not enough know about Chesterton's lamp-post. A similar parable, but that one comes with lessons on importance of concise and effective communication regarding the lamp-post's utility.
Most orgs where search is important have this dysfunctional organizational process where people are siloed into ML and search separately.
Where the search infra team owns infra, and the candidate retrieval process under strict latency constraints.
Then, the ML people can write their single threaded Python pandas reranking routines copied from a notebook that Fred wrote in 2019.
This ML โranking layerโ usually also involves a custom container image built on the tensorflow 1.14rc2 image to rerank 100 items with a DNN
@rakyll The thing is that GCP made a huge Vertex marketing push, and Vertex docs never send you to aistudio - in fact, Vertex has its own different thing also called ai studio. Product decisions around all this are bewildering.
Big news: I'm helping with @martinkl with a second edition of Designing Data-Intensive Applications! An early release of the first 3 chapters is now available (O'Reilly Learning subscribers only at this point) and we're hoping to finish it next year.
https://t.co/SpDUBCLdLi