IBM Watson OpenScale
IBM Watson OpenScale
About IBM Watson OpenScale
IBM Watson OpenScale is an open, enterprise-grade platform that enables businesses to build, operate, and manage production AI. Features include measurement and tracking of AI outcomes, continuous feedback loops, intelligent bias detection and correction, actionable metrics, and more.
With the IBM Watson OpenScale operations console, users can track and measure AI outcomes allowing alignment with business outcomes and organizational KPI's, enabling users to adjust and respond to business changes. The platform provides out-of-the-box metrics as well as the option of custom metrics for tracking model performance. Outcomes are tracked and measured from AI across its lifecycle, while adapting to changing business needs. It detects and mitigates risk and harmful bias, providing business with actionable insights for business development and change plans.
IBM Watson OpenScale can be integrated into existing business applications and model development environments including IBM Watson Machine Learning, IBM Watson Studio, AWS SageMaker, TensorFlow, and AzureML, enabling users to further accelerate the AI capabilities. AI models can be deployed on a variety of cloud platforms including IBM Cloud, IBM Cloud Private, and more.
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- Industry: Oil & Energy
- Company size: 10,000+ Employees
- Used Weekly for 2+ years
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- Likelihood to recommend 9.0 /10
IBM Watson OpenScale: a must-have machine learning management solution for enterprises
Reviewed on 29/03/2023
Pros
One of the most important benefits of IBM Watson OpenScale is its ability to manage and monitor machine learning models at scale. Companies can use this tool to track the performance of their machine learning models and understand how they are changing over time.In addition, IBM Watson OpenScale enables companies to quickly detect problems with their machine learning models. The tool provides real-time alerts when a model begins to behave abnormally, allowing companies to react quickly and resolve issues before they become critical.In addition, IBM Watson OpenScale provides increased transparency into how machine learning models make decisions. Companies can track the decisions made by machine learning models and understand how those decisions are made. This can help companies feel more confident in the decisions their machine learning models make and improve their accuracy over time.
Cons
Limited integration: IBM Watson OpenScale was designed to work in tandem with other IBM products, which may make it more difficult to integrate with other third-party tools.Resource requirements: IBM Watson OpenScale requires a number of computing resources, such as memory and storage, to operate effectively. Organizations must ensure they have these resources before deploying the tool.Complexity: Due to its advanced nature, IBM Watson OpenScale can be complex to use for beginners or inexperienced users.
IBM Watson OpenScale FAQs
Below are some frequently asked questions for IBM Watson OpenScale.Q. Who are the typical users of IBM Watson OpenScale?
IBM Watson OpenScale has the following typical customers:
2–10, 11–50, 51–200, 201–500, 501–1,000, 1,001–5,000
Related categories
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Artificial Intelligence (AI) Software