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Mar 17, 2024 · We are releasing the base model weights and network architecture of Grok-1, our large language model. Grok-1 is a 314 billion parameter Mixture-of-Experts model trained from scratch by xAI. This is the raw base model checkpoint from the Grok-1 pre-training phase, which concluded in October 2023.
Explainable artificial intelligence (XAI) is a set of processes and methods that allows human users to comprehend and trust the results and output created by machine learning algorithms. Explainable AI is used to describe an AI model, its expected impact and potential biases.
23 hours ago · Listen. 1:40. Elon Musk ’s artificial intelligence startup xAI has raised $6 billion to accelerate its challenge to his former allies at OpenAI. The Series B round, announced in a blog post on ...
XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contains various tools that enable for analysis and evaluation of data and models. The XAI library is maintained by The Institute for Ethical AI & ML, and it was developed based on the 8 principles for Responsible Machine Learning.
Jul 12, 2021 · [Submitted on 12 Jul 2021] Explainable AI: current status and future directions. Prashant Gohel, Priyanka Singh, Manoranjan Mohanty. Explainable Artificial Intelligence (XAI) is an emerging area of research in the field of Artificial Intelligence (AI).
Features. Understand AI output with groundbreaking XAI tools, developed by Google Research and used to power AI at Google. Feature attributions. A managed service for generating feature...
Explainable AI (XAI) refers to the ability of an artificial intelligence (AI) system or model to provide clear and understandable explanations for its actions or decisions. In other words, XAI is about making AI transparent and interpretable to humans.
