Resultado de búsqueda
18 de dic. de 2019 · The purpose of an explainable AI (XAI) system is to make its behavior more intelligible to humans by providing explanations. There are some general principles to help create effective, more human-understandable AI systems: The XAI system should be able to explain its capabilities and understandings; explain what it has done, what it is doing now, and what will happen next; and disclose the ...
12 de jul. de 2021 · Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI). XAI can explain how AI obtained a particular solution (e.g., classification or object detection) and can also answer other "wh" questions. This explainability is not possible in traditional AI. Explainability is essential for critical applications, such as defense, health ...
Model Specifications. Grok-1 is currently designed with the following specifications: Parameters: 314B. Architecture: Mixture of 8 Experts (MoE) Experts Utilization: 2 experts used per token. Layers: 64. Attention Heads: 48 for queries, 8 for keys/values. Embedding Size: 6,144. Tokenization: SentencePiece tokenizer with 131,072 tokens.
ocultar. La inteligencia artificial explicable (en inglés: explainable artificial intelligence, habitualmente abreviado XAI) se refiere a métodos y técnicas en la aplicación de tecnología de inteligencia artificial (IA) por los que el ser humano es capaz de comprender las decisiones y predicciones realizadas por la inteligencia artificial.
24 de may. de 2021 · Why XAI Explains Individual Decisions Best The best understood area of XAI is individual decision-making: why a person didn’t get approved for a loan, for instance. Techniques with names like LIME and SHAP offer very literal mathematical answers to this question — and the results of that math can be presented to data scientists, managers, regulators and consumers.
3 de nov. de 2023 · Read about the latest announcements from xAI including Grok, Grok-1, and the PromptIDE. Blog About Careers. Menu. Blog. Read about our latest product and research announcements. May 26, 2024. Series B Funding Round. May 26, 2024. xAI is pleased to announce our series B funding round of $6 billion.
1 de jun. de 2020 · Grounded on a first elaboration of concepts and terms used in XAI-related research, we propose a novel definition of explainability that places audience (Fig. 2) as a key aspect to be considered when explaining a ML model.We also elaborate on the diverse purposes sought when using XAI techniques, from trustworthiness to privacy awareness, which round up the claimed importance of purpose and ...
