In the final episode of our 7 mini-series on the The Challenges of AI, we chat with Clarinda Mascarenhas about an item that isn't part of the AI Ladder, but is still needed by enterprises - Modernize. The average enterprise has 5-6, in addition to a wealth of data scattered across on-premises and legacy systems. That data must be integrated, governed, and leveraged across the full AI lifecycle. With Modernize, customers can make their data ready for an AI and hybrid cloud world by
automating the end-to-end data and AI lifecycle management integrating and govern data across hybrid cloud and data settings virtualizing all data, regardless of where it livesDon't forget to subscribe to get updates when a new episode launches
Situation Under Control - IBM Cloud Framework for Financial Services
What is DevSecOps and Software Supply Chain Security ?
IT Economics and Cloud - it depends
9 ways to fail at cloud native
IBM Cloud Databases and Their Intersection with Distributed Cloud
The Rise of Industry Clouds
Cloud Skills to Pay the Bills - Closing the Cloud Skills Gap
Distributed Cloud - Consume public cloud in your data center, edge, or other clouds
Get developers out of the infrastructure business with IBM Cloud Code Engine
Confidential Computing - Protect your data at rest, in transit and in use.
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Managed OpenShift has a Posse (the Developer Voice)
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Disaster Recovery and Backup in a Software Defined DC
The Makeup of a Software-Defined Data Centre
The Software-Defined Data Centre
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The Challenge of AI: Operationalize AI throughout the business
The Challenge of AI: Build and scale AI with trust and transparency
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