Category: Machine Learning

June 24, 2020

HPE Turns to Containers With Its Ezmeral Software

At its virtual Discover event this week, HPE announced the launch of its kubernetes-based container software, HPE Ezmeral. This announcement shows HPE’s continued dedication to its goal of everything-as-a-service by 2022 and heats up the container wars with competitors like IBM RedHat and VMWare.

AI, Cloud, Hybrid Cloud, Infrastructure, and Operations, Machine Learning

June 1, 2020

Daniel Newman

Futurum Tech Webcast

Understanding the Ideal Human-Machine Relationship – Futurum Tech Podcast Interview Series

On this special episode of the Futurum Tech Podcast - Interview Series, host Daniel Newman is joined by Logan Wilt, AI data scientist and Applied AI Center of Excellence Garage Leader at DXC Technology to talk about using AI to approach problem solving and the human-machine relationship we are now encountering.

AI, Digital Home, Machine Learning

March 13, 2020

James Kobielus

Research Note

Superwise.ai Addresses Growing Enterprise Need for AI Model Assurance

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.

AI, Machine Learning

March 12, 2020

James Kobielus

Research Note

Google’s TensorFlow Quantum Is a Key Industry Milestone in Machine Learning Acceleration

Google’s latest announcement lands in a fast-moving, but still immature, quantum computing marketplace. By extending the most popular open-source ML development framework, Google will almost certainly catalyze use of TensorFlow Quantum in a wide range of ML-related initiatives. The Google-developed quantum ML framework will find its way into a wide range of other solution providers’ quantum computing environments. So what will Google’s likely next move be in the Quantum ML space? Read on to see what I think.

Emerging Technologies, Machine Learning, Quantum Computing

March 9, 2020

James Kobielus

Research Note

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

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.

AI, Cloud, Hybrid Cloud, Infrastructure, and Operations, Machine Learning

February 27, 2020

James Kobielus

Research Note

Algorithmia Integrates AI Model Governance with GitOps

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.