touche_bag

29 ms·

1. 1.▲
   by touche_bag 2y ago

   100? I had a customer with 10k upserts incl merge logic for the upserts while serving 100k concurrent reads. Good luck doing that with a SQL database trying to check constraints across 10 tables. This is what Nosql databases are optimized f
2. 2.▲
   by touche_bag 2y ago

   Huh? Rerank is always a boost on top of retrieval. So regardless of the chunking method or model you use, reranking with a good model will always result in higher MRR. And improvements in embedding models also will never solve the probl
3. 3.▲
   by touche_bag 2y ago

   Consistent reads also mean additional checks. I think the WT cache is also very double edged. Completely cripples the database when resource constrained and not sized correctly, while giving a huge boost when the environment is "right
4. 4.▲
   by touche_bag 2y ago

   I think 8 was a release purely focused on performance, with some big improvements. Comparing 3.4 is kinda unfair.. You were fast with the tradeoff of half your data missing half the time
5. 5.▲
   by touche_bag 2y ago

   Interesting take. Have you benchmarked models on your own data? Cause at this point everything is contaminated so I find it impossible to tell what proper sota is. Also - most folks still just use openai. Last time I checked, reranking alw