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The Secret to Automating Machine Learning Life Cycles

In this contributed article, Lucas Bonatto, CEO & Founder of Elemeno, suggests that the constant use, upgrade, and acceleration of AI and machine learning will create countless opportunities for enabling innovation in organizations outside IT, as well as adapting to changes in the IT Operations Model. The secret to automating ML lifecycles is to increase the adoption of AI around the world. The first step to achieve this goal is by providing an end-to-end ML-Ops platform with an AI Marketplace where users can obtain models, making the use of AI as seamless as possible.

MLOps | Is the Enterprise Repeating the Same DIY Mistakes?

In this contributed article, Aaron Friedman, VP of Operations at Wallaroo.ai, discusses why hiring data scientists isn’t the answer to unlocking ML value (especially at a time when finding qualified candidates is harder than ever).

Run:ai Releases Advanced Model Serving Functionality to Help Organizations Simplify AI Deployment 

Run:ai, a leader in compute orchestration for AI workloads, announced new features of its Atlas Platform, including two-step model deployment — which makes it easier and faster to get machine learning models into production. The company also announced a new integration with NVIDIA Triton Inference Server. These capabilities are particularly focused on supporting organizations in […]

Datatron Simplifies Platform for Operationalization of ML Models 

Datatron announced the latest version of its enterprise-grade MLOps platform. Updates include increased flexibility, a new interface that simplifies data scientists’ workflow, and ease-of-use enhancements for the operational teams, resulting in an additional productivity gain of up to 68%. 

Domino Data Lab Announces Hybrid MLOps Architecture to Future-Proof Model-Driven Business at Scale

Domino Data Lab, a leading Enterprise MLOps platform trusted by over 20 percent of the Fortune 100, announced its new Nexus hybrid Enterprise MLOps architecture that will allow companies to rapidly scale, control and orchestrate data science work across different compute clusters — in different geographic regions, on premises, and even across multiple clouds.

VIANAI Systems Introduces First Human-Centered AI Platform for the Enterprise

Vianai Systems (“Vian”), the human-centered AI platform and products company, launched the Vian H+AITM Platform for reliable, optimized enterprise-wide deployment, management, and governance of machine learning (ML) models at scale. The Vian H+AI Platform brings a human-centric approach, combined with advanced AI techniques to address and remove barriers that currently prevent widespread AI adoption into production environments.

XOps: The Rise of Smarter Tech Operations

In this contributed article, Arvind Prabhakar, CTO of StreamSets, discusses how XOps has become a growing data analytics trend in 2021 for good reason. Evolved from the DevOps movement to better support and enable AI and ML automation workflows, XOps enables organizations to operationalize data and analytics to drive greater business value and establish a solid yet flexible foundation for future technology development.

Case Study: Balancing MLOps Innovation with Tough Security Standards

As AI adoption has grown, so too have concerns about data protection and infrastructure security across the MLOps lifecycle. At GTS Data Processing, a rapidly growing German IT company, security is top of mind as they deliver Infrastructure-as-a-Service and Software-as-a-Service platforms to companies across Europe. GTS’ DSready Cloud offering, powered by Domino® and hosted in Germany, brings together the tools, technologies, compute, and collaboration capabilities its clients need to deliver and manage data science capabilities at scale—all within a GDPR-compliant environment that supports Germany’s stringent security standards.

Balancing MLOps Innovation with Tough Security Standards

As AI adoption has grown, so too have concerns about data protection and infrastructure security across the MLOps lifecycle. At GTS Data Processing, a rapidly growing German IT company, security is top of mind as they deliver Infrastructure-as-a-Service and Software-as-a-Service platforms to companies across Europe. GTS’ DSready Cloud offering, powered by Domino® and hosted in Germany, brings together the tools, technologies, compute, and
collaboration capabilities its clients need to deliver and manage data science capabilities at scale—all within a GDPR-compliant environment that supports Germany’s stringent security
standards.

The Missing Role your Organization Needs for the Success of your AI Initiatives

In this contributed article, Alankrita Priya, AI/ML Product Manager at Hypergiant, discusses how MLOps platforms can operationalize new technologies and fully bridge the gap between data scientists and end business users. There is a crucial role that AI PMs will play moving forward in both facilitating this deployment process and ensuring that companies practice responsible AI.