Row 13460

Row ID: 13460 | Dataset Entry | Axioma AXP Content Repository

Content Data

This page contains data entry 13460 from the Axioma AXP content repository. The structured data below represents the complete record for this entry.

Beginning to feel like this thread is product market research lmao

But...

Monitoring every LLM call is invaluable. We can see an entire chat session in the UI, deep dive into Agentic & Rag traces to see how their interim steps go. Good for debugging. See any manual human feedback or automated evaluations on each response. Great for downstream fine-tuning or even generally evaluating our systems. We can directly see the cost impacts of a new prompt, and the cost of specific APIs and sub components.

We can A/B test prompts, deploy to stage/prod when ready. And generally we get through so many variations it's great to have a git-esque permanent log.

FieldValue
text Beginning to feel like this thread is product market research lmao But... Monitoring every LLM call is invaluable. We can see an entire chat session in the UI, deep dive into Agentic & Rag traces to see how their interim steps go. Good for debugging. See any manual human feedback or automated evaluations on each response. Great for downstream fine-tuning or even generally evaluating our systems. We can directly see the cost impacts of a new prompt, and the cost of specific APIs and sub compone…
label r/machinelearning
dataType comment
communityName r/MachineLearning
datetime 2024-05-20
username_encoded Z0FBQUFBQm5Lakw3eUJsamw5T2NhS0VFcDNEeC1OWkV2bjM5bERWbDZUNHpDTnVUZWNCV2MwYVJTMHd2Y2gtRTMxUVB5eXpRNng4d1NsSnFVOUU4Z3lmaVRNNUpPMGpUQkE9PQ==
url_encoded Z0FBQUFBQm5Lak9LU2YtS0NFMWV2Q2U3THpRV3A2U296V015MU1ySmFaa1N5NGllUWdVNnVETGMwTjZnTy1fcURJVVFDWkxqMTVhdng5emRBODBxaFpzVFdQNjFLYW9vLWEyWUI3TndBRkZjVm83dGhOZkFfZ1VmS2hnTUI5U3JheVo3c1dheEpVcE5kWHo4c0h2aU02UGxlS3NYazBjVnhfTmJmUUliZ3UwNTNUWTVFa1BsdGlIRUY2YXp2WUFnNzlmMjVUR2FOYnZwcUNnZDN1bmZaTFlCb0wteWtKZEZLUT09

Raw Record

{
  "text": "Beginning to feel like this thread is product market research lmao\n\nBut...\n\nMonitoring every LLM call is invaluable. We can see an entire chat session in the UI, deep dive into Agentic & Rag traces to see how their interim steps go. Good for debugging. See any manual human feedback or automated evaluations on each response. Great for downstream fine-tuning or even generally evaluating our systems.\nWe can directly see the cost impacts of a new prompt, and the cost of specific APIs and sub components.\n\nWe can A/B test prompts, deploy to stage/prod when ready. And generally we get through so many variations it's great to have a git-esque permanent log.",
  "label": "r/machinelearning",
  "dataType": "comment",
  "communityName": "r/MachineLearning",
  "datetime": "2024-05-20",
  "username_encoded": "Z0FBQUFBQm5Lakw3eUJsamw5T2NhS0VFcDNEeC1OWkV2bjM5bERWbDZUNHpDTnVUZWNCV2MwYVJTMHd2Y2gtRTMxUVB5eXpRNng4d1NsSnFVOUU4Z3lmaVRNNUpPMGpUQkE9PQ==",
  "url_encoded": "Z0FBQUFBQm5Lak9LU2YtS0NFMWV2Q2U3THpRV3A2U296V015MU1ySmFaa1N5NGllUWdVNnVETGMwTjZnTy1fcURJVVFDWkxqMTVhdng5emRBODBxaFpzVFdQNjFLYW9vLWEyWUI3TndBRkZjVm83dGhOZkFfZ1VmS2hnTUI5U3JheVo3c1dheEpVcE5kWHo4c0h2aU02UGxlS3NYazBjVnhfTmJmUUliZ3UwNTNUWTVFa1BsdGlIRUY2YXp2WUFnNzlmMjVUR2FOYnZwcUNnZDN1bmZaTFlCb0wteWtKZEZLUT09"
}
Explore Dataset Explore Row

Entry Information