Human-in-the-loop: Difference between revisions
From ACT Wiki
Jump to navigationJump to search
imported>Doug Williamson (Create page. Sources: Linked pages.) |
(Add link.) |
||
| Line 19: | Line 19: | ||
* [[Deep learning]] | * [[Deep learning]] | ||
* [[Generative pre-trained transformer]] (GPT) | * [[Generative pre-trained transformer]] (GPT) | ||
* [[Google Gemini]] | |||
* [[GPT-4]] | * [[GPT-4]] | ||
* [[Information technology]] | * [[Information technology]] | ||
| Line 34: | Line 35: | ||
*[[Unsupervised learning]] | *[[Unsupervised learning]] | ||
[[Category:Identify_and_assess_risks]] | [[Category:Identify_and_assess_risks]] | ||
[[Category:Manage_risks]] | [[Category:Manage_risks]] | ||
[[Category:Risk_reporting]] | |||
[[Category:Risk_frameworks]] | [[Category:Risk_frameworks]] | ||
[[Category: | [[Category:The_business_context]] | ||
Latest revision as of 22:21, 11 May 2024
Information technology - software - machine learning - natural language processing.
(HITL).
In the context of machine learning, human-in-the-loop refers to one or both of the following roles undertaken by a human:
- Manual labelling of training data.
- Validating or feeding back to the model on the quality of its outputs.
See also
- Artificial intelligence (AI)
- Artificial super-intelligence (ASI)
- Bot
- Chatbot
- ChatGPT
- Data
- Data labelling
- Deep learning
- Generative pre-trained transformer (GPT)
- Google Gemini
- GPT-4
- Information technology
- Language model
- Large language model (LLM)
- Machine learning
- Natural language
- Natural language processing
- Neural network
- Reinforcement Learning from Human Feedback (RLHF)
- Robotics
- Software
- Software robot
- Supervised learning
- Unsupervised learning
