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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 ...
Explainable AI ( XAI) refers to methods and techniques in the application of artificial intelligence technology (AI) such that human experts can understand the results of the solution. It contrasts with the concept of the “black box” in machine learning, where even their designers cannot explain why the AI arrived at a specific decision.
