RLHF
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models.
Reinforcement Learning from Human Feedback (RLHF) is a machine learning technique that uses human input to guide the training of AI models.
The degree to which a product satisfies strong market demand, often considered a key indicator of a product's potential for success.
The study of the relationships between people, practices, values, and technologies within an information environment.
Guidelines and principles designed to ensure that AI systems are developed and used in a manner that is ethical and responsible.
The use of statistical techniques and algorithms to analyze historical data and make predictions about future outcomes.
Culture, Automation, Lean, Measurement, and Sharing (CALMS) is a framework for guiding the implementation of DevOps practices.
A mathematical framework used to analyze strategic interactions where the outcomes depend on the actions of multiple decision-makers.
The process of optimizing content and website structure to improve visibility and ranking in voice search results.
Internet of Things (IoT) refers to a network of interconnected physical devices embedded with electronics, software, sensors, and network connectivity, enabling them to collect and exchange data.