Difference between revisions of "Humanloop"

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** [https://docs.humanloop.com/docs/quickstart Playground documentation]
 
** [https://docs.humanloop.com/docs/quickstart Playground documentation]
 
* [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ... [[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]]
 
* [[Large Language Model (LLM)]] ... [[Natural Language Processing (NLP)]] ... [[Natural Language Generation (NLG)|Generation]] ... [[Natural Language Classification (NLC)|Classification]] ... [[Natural Language Processing (NLP)#Natural Language Understanding (NLU)|Understanding]] ... [[Language Translation|Translation]] ... [[Natural Language Tools & Services|Tools & Services]]
* [[Large Language Model (LLM)#Multimodal|Multimodal Language Model]]s ... [[GPT-4]] ... [[GPT-5]]
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* [[Risk, Compliance and Regulation]] ... [[Ethics]] ... [[Privacy]] ... [[Law]] ... [[AI Governance]] ... [[AI Verification and Validation]]
 
* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ... [[Algorithm Administration#Automated Learning|Automated Learning]]
 
* [[Singularity]] ... [[Artificial Consciousness / Sentience|Sentience]] ... [[Artificial General Intelligence (AGI)| AGI]] ... [[Inside Out - Curious Optimistic Reasoning| Curious Reasoning]] ... [[Emergence]] ... [[Moonshots]] ... [[Explainable / Interpretable AI|Explainable AI]] ... [[Algorithm Administration#Automated Learning|Automated Learning]]
  

Revision as of 10:07, 27 June 2023

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Humanloop helps developers build high-performing applications on top of large language models like GPT-3. You can use it to experiment with new prompts, collect model generated data and user feedback, and finetune models for better performance while optimizing costs.