Row 27086

Row ID: 27086 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 27086 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Twitter gets a lot of hate but it’s easily the best place for AI Engineering resources and networking. Here’s a [recent post from LlamaIndex themselves](https://x.com/llama_index/status/1792354714648211648?s=46&t=Sfyn0fYB_7h9jFWWL6MHiw) + the article they link to covering some similar:

[How to Optimize Chunk Size for RAG in Production (Medium)](https://pub.towardsai.net/how-to-optimize-chunk-sizes-for-rag-in-production-fae9019796b6)

FieldValue
text Twitter gets a lot of hate but it’s easily the best place for AI Engineering resources and networking. Here’s a [recent post from LlamaIndex themselves](https://x.com/llama_index/status/1792354714648211648?s=46&t=Sfyn0fYB_7h9jFWWL6MHiw) + the article they link to covering some similar: [How to Optimize Chunk Size for RAG in Production (Medium)](https://pub.towardsai.net/how-to-optimize-chunk-sizes-for-rag-in-production-fae9019796b6)
label r/datascience
dataType comment
communityName r/datascience
datetime 2024-05-21
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Raw Record

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  "text": "Twitter gets a lot of hate but it’s easily the best place for AI Engineering resources and networking. Here’s a [recent post from LlamaIndex themselves](https://x.com/llama_index/status/1792354714648211648?s=46&t=Sfyn0fYB_7h9jFWWL6MHiw) + the article they link to covering some similar:\n\n[How to Optimize Chunk Size for RAG in Production (Medium)](https://pub.towardsai.net/how-to-optimize-chunk-sizes-for-rag-in-production-fae9019796b6)",
  "label": "r/datascience",
  "dataType": "comment",
  "communityName": "r/datascience",
  "datetime": "2024-05-21",
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Entry Information