Artificial intelligence (AI) can be a highly transformative technology and is becoming an essential part of the technology industry impacting everything from our personal lives to the way we conduct business. But as AI computing becomes standard practice, enterprises are looking to differentiate themselves by utilizing tools that will allow them to get the most value and insight from their AI. One such tool is IBM Cloud Pak® for Data and in this blog I will explain how it provides organizations with an end-to-end enterprise insights platform for their data and AI needs and how IBM Z® can also play a vital role.
IBM Cloud Pak for Data, Watson® Machine Learning for z/OS® and open-source technologies are a part of a comprehensive software and hardware strategy that solidifies IBM Z as a first-class AI platform. IBM recently publicly discussed the new Telum processor which features on-chip acceleration specifically for AI deep learning processing.
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To get the most value from their AI efforts, organizations need to establish an information architecture. At many large enterprises, data resides in different formats across multiple platforms. Because of this complex data landscape, many organizations have found it difficult to collect and structure data in a form useful for AI. The lack of an information architecture within these complex environments can be a primary factor in impeding AI implementation. To help establish an information architecture that can unlock the value of data and accelerate the journey to AI, IBM has developed a prescribed approach we call the “AI Ladder.” It features four sequential steps; collect, organize and analyze data so that AI models can be infused within business processes.
IBM Cloud Pak for Data
IBM Cloud Pak for Data addresses the challenges of delivering analytics and AI using a single, open platform to infuse AI into business applications. Cloud native by design, the platform unifies market-leading services spanning the entire analytics lifecycle. It helps eliminate the need for costly, and often competing, point solutions while providing the information architecture you need to successfully implement AI. Core to an enterprise insights platform is the ability to store and manage data in support of analytics and AI. Modernizing your data infrastructure via a cloud native, containerized approach, such as with IBM Cloud Pak for Data, can significantly simplify your data management efforts. And leveraging existing IBM Z infrastructure and skills can help you reduce implementation risk, complexity, and cost.
IBM Cloud Pak for Data on IBM Z and IBM Watson Studio
IBM Cloud Pak for Data on IBM Z debuted in November 2020 with a focus on modernizing data infrastructure in support of analytics and AI. It brings the capabilities of IBM Cloud Pak for Data including the Red Hat® OpenShift® Container Platform and pre-integrated, certified software to your existing IBM Z infrastructure. The initial release included IBM Cloud Pak foundational services, IBM Db2® Management Console and IBM Db2 Warehouse. Also available are IBM Db2 Advanced Enterprise Server Edition and IBM Db2 for z/OS® Data Gate.
IBM is now incorporating IBM Watson® Studio within IBM Cloud Pak for Data 4.0.2 on IBM Z so that organizations can build AI models where data often originates. IBM Watson Studio is designed to empower data scientists, developers, and analysts to build, run and manage AI models, and optimize decisions anywhere IBM Cloud Pak® for Data runs.
These recent enhancements help organizations to confidently leverage their IBM Z platform and enterprise data to build and deploy ML/AI models on Linux® on IBM Z and LinuxONE. Organizations can also build AI models on IBM Cloud Pak for Data on IBM Z and deploy those models within the z/OS environment through Watson Machine Learning for z/OS. By unlocking the value of their IBM Z data in new ways, organizations can drive additional revenue, control costs, help reduce fraud, and improve customer satisfaction while making minimal changes to their core business applications.
Source: ibm.com
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