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Explainable machine learning (xml) or explainable ai (xai)
| Глоссарий терминов искусственного интеллекта |
Researchers have developed a set of processes and methods that allow humans to better understand the results and outputs of machine learning algorithms. this helps developers of ai-mediated tools understand how the systems they design work and can help them ensure that they work correctly and are meeting requirements and regulatory standards.
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Understand, английский
Algorithms, английский
Complex mathematical formulae or rules used to solve complex problems in cctv they are used to achieve digital compression of a video picture.
Requirements, английский
Нормативы
Requirement, английский
- Требование
- Something which is necessary one of the requirements of the position is a qualification in pharmacy. res abbr reticuloendothelial system
- Требование; спрос; потребность; условие ~ of continuity требование (обеспече- 469 requirement ния) неразрывности [неразрезность сплошности] ~s of structural safety требования техники безопасности в строительстве
- A desired feature, property, or behavior of a system.
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Foundation models, английский
Foundation models represent a large amount of data that can be used as a foundation for developing other models. for example, generative ai systems use large language foundation models. they can be a way to speed up the development of new systems, but there is controversy about using foundation models since depending on where their data comes from, there are different issues of trustworthiness and bias. jitendra malik, professor of computer science at uc berkeley once said the following about foundation models
Critical ai, английский
Critical ai is an approach to examining ai from a perspective that focuses on reflective assessment and critique as a way of understanding and challenging existing and historical structures within ai. read more about critical ai.
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