At IBM Think, Watson Expands "Anywhere"

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At IBM Think in February, IBM made several announcements around the expansion of Watson's availability and capabilities, framing these announcements as the launch of "Watson Anywhere." This piece is intended to provide guidance to data analysts, data scientists, and analytic professionals seeking to implement machine learning and artificial intelligence capabilities and evaluating the capabilities of IBM Watson's AI and machine learning services for their data. IBM declared that Watson is now available "anywhere" – both on-prem and in any cloud configuration, whether private, public, singular, multi-cloud, or a hybrid cloud environment. Data that needs to remain in place for privacy and security reasons can now have Watson microservices act on it where it resides. The obstacle of cloud vendor lock-in can be avoided by simply bringing the code to the data instead of vice versa.


Trust and transparency for your machine learning models with Watson OpenScale

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This tutorial is part of the Getting started with Watson OpenScale learning path. In this tutorial, you'll see how IBM Watson OpenScale can be used to monitor your artificial intelligence (AI) models for fairness and accuracy. You'll get a hands-on look at how Watson OpenScale will automatically generate a debiased model endpoint to mitigate your fairness issues and provides an explainability view to help you understand how your model makes its predictions. In addition, you'll see how Watson OpenScale uses drift detection. Drift detection will tell you when runtime data is inconsistent with your training data or if there is an increase the data that is likely to lead to lower accuracy.


IBM Wants To Make Artificial Intelligence Fair And Transparent With AI OpenScale

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IBM has announced AI OpenScale, a service that aims to bring visibility and explainability of AI models for enterprises. When it comes to adopting AI for business use, there are multiple concerns among enterprise customers. Lack of visibility of the model, unwanted bias, interoperability among tools and frameworks, compliance in building and consuming AI models are some of the critical issues with AI. IBM AI OpenScale provides explanations into how AI models are making decisions, and automatically detect and mitigate bias to produce fair, trusted outcomes. It attempts to bring confidence to enterprises by addressing the challenges involved in adopting artificial intelligence.


IBM Wants To Make Artificial Intelligence Fair And Transparent With AI OpenScale

#artificialintelligence

IBM has announced AI OpenScale, a service that aims to bring visibility and explainability of AI models for enterprises. When it comes to adopting AI for business use, there are multiple concerns among enterprise customers. Lack of visibility of the model, unwanted bias, interoperability among tools and frameworks, compliance in building and consuming AI models are some of the critical issues with AI. IBM AI OpenScale provides explanations into how AI models are making decisions, and automatically detects and mitigates bias to produce fair, trusted outcomes. It attempts to bring confidence to enterprises by addressing the challenges involved in adopting artificial intelligence.


IBM Wants To Make Artificial Intelligence Fair And Transparent With AI OpenScale

#artificialintelligence

IBM has announced AI OpenScale, a service that aims to bring visibility and explainability of AI models for enterprises. When it comes to adopting AI for business use, there are multiple concerns among enterprise customers. Lack of visibility of the model, unwanted bias, interoperability among tools and frameworks, compliance in building and consuming AI models are some of the critical issues with AI. IBM AI OpenScale provides explanations into how AI models are making decisions, and automatically detects and mitigates bias to produce fair, trusted outcomes. It attempts to bring confidence to enterprises by addressing the challenges involved in adopting artificial intelligence.