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Microsoft Research AI Ethics Checklist Crafts Principles for Designing AI DevOps Processes

In AI, Technology News by James KobielusLeave a Comment

Microsoft Research AI ethics checklist is a set of published principles for designing ethics checklists that can be readily operationalized in AI DevOps processes. We commend Microsoft Research’s recent effort to catalyze consensus within the practitioner community for the purpose of developing clear principles for designing operationalizable AI ethics checklists.

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Superwise.ai Addresses Growing Enterprise Need for AI Model Assurance

In AI by James KobielusLeave a Comment

Superwise.ai addresses a growing enterprise need for AI model assurance. That said, there are both challenges and opportunities ahead for this AI startup. Model assurance is the ability to determine whether an AI application’s machine learning (ML) models remain predictively fit for their assigned tasks. This is a critical feature of any operational AI DevOps platform, which is one of the reasons Superwise.ai caught my attention. I see both challenges and opportunities ahead for this AI startup.

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NVIDIA Acquisition of SwiftStack Facilitates Cloud-to-Edge Data Management for AI and HPC

In AI, Cloud by James KobielusLeave a Comment

It is apparent that NVIDIA recognizes its current market-leading status in AI chipsets won’t necessary last forever. By focusing on the enterprise stack—the data center, enterprise computing, and all things related to the future of AI in the enterprise, the company plots a path forward that allows it to sustain its impressive growth record. The company’s acquisition of SwiftStack provides NVIDIA with a software-driven data storage and management platform for acceleration of deep learning, analytics, and high-performance computing applications across multiclouds.

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Algorithmia Integrates AI Model Governance with GitOps

In AI by James KobielusLeave a Comment

Algorithmia integrates AI model governance with GitOps, integrating ML and code development into DevOps workflows that use Git as a source-code repository. With this announcement, Algorithmia has made it easier to use GitHub to break down the silos that traditionally have kept ML developers and application coders from integrating tightly within today’s continuous DevOps workflows.