- What is explainable AI? - IBM
Explainable AI is used to describe an AI model, its expected impact and potential biases It helps characterize model accuracy, fairness, transparency and outcomes in AI-powered decision making Explainable AI is crucial for an organization in building trust and confidence when putting AI models into production
- Apa yang dimaksud dengan Explainable AI? - IBM
² ” Explainable Artificial Intelligence ”, Jaime Zornoza, 15 April 2020 ³ ” Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI ”, ScienceDirect, Juni 2020 ⁴ ” Understanding Explainable AI ”, Ron Schmelzer, Forbes contributor, 23 Juli 2019
- 설명 가능한 AI(XAI)란 무엇인가요? - IBM
² ” Explainable Artificial Intelligence ”, Jaime Zornoza, 2020년 4월 15일 ³ ” Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI ”, ScienceDirect, 2020년 6월 ⁴ ” Understanding Explainable AI ”, Ron Schmelzer, Forbes contributor, 2019년 7월 23일
- 什么是可解释 AI？ - IBM
² ” Explainable Artificial Intelligence ”, Jaime Zornoza, 2020 年 4 月 15 日。 ³ “ 可解释人工智能 (XAI)：负责任 AI 的概念、分类法、机遇与挑战 ”，ScienceDirect，2020 年 6 月。 ⁴ “ Understanding Explainable AI ”，《福布斯》撰稿人 Ron Schmelzer，2019 年 7 月 23 日。
- What Is Black Box AI and How Does It Work? | IBM
White box AI, also called explainable AI (XAI) or glass box AI, is the opposite of black box AI It is an AI system with transparent inner workings Users understand how the AI takes in data, processes it and arrives at a conclusion
- ¿Qué es la IA explicable? - IBM
¹ ” Explainable AI ” The Royal Society 28 de noviembre de 2019 ² ” Explainable Artificial Intelligence ” Jaime Zornoza 15 de abril de 2020 ³ ” Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI ” ScienceDirect Junio de 2020 ⁴ ” Understanding Explainable
- What Is AI Interpretability? - IBM
Explainable AI (XAI) is used to identify the factors that led to the results Various explainability methods can be used to present the models in ways that make their complex processes and underlying data science clear to a human being using natural language
- Agentic AI vs. Generative AI | IBM
Diving into the differences between agentic AI and generative AI means first defining both Generative AI is artificial intelligence that can create original content—such as text, images, video, audio or software code—in response to a user’s prompt or request
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