Human-in-the-Loop (HITL): Integrating human judgment with AI decision-making, ensuring optimal outcomes and alignment with human values.
Labelling in AI: Assigning descriptive tags or categories to data to train AI models in recognizing and interpreting similar data. (Thanks John Stieger)
Labelling in AI: Assigning descriptive tags or categories to data to train AI models in recognizing and interpreting similar data. (Thanks John Stieger)
Large Language Models (LLMs): AI systems trained on vast text datasets, capable of high-quality text generation and translation.
Large Language Models (LLMs): AI systems trained on vast text datasets, capable of high-quality text generation and translation.
Machine Learning: A subfield of AI where algorithms learn and improve from data over time, without explicit programming for each task.
Multi-modal AI: AI systems capable of processing and generating diverse data types — like text, images, voice, and video — often simultaneously, to provide a more comprehensive output or interaction. (Thanks Jeremiah Owyang).
Multi-modal AI: AI systems capable of processing and generating diverse data types — like text, images, voice, and video — often simultaneously, to provide a more comprehensive output or interaction. (Thanks Jeremiah Owyang).
Natural Language Processing (NLP): AI's ability to understand and process human language, encompassing tasks like translation, sentiment analysis, and text generation.
Neural Networks: Models composed of interconnected nodes that process data, inspired by the human brain's neurons. They're essential for modern AI.