ClearML, the frictionless, unified, end-to-end MLOps platform, and Genesis Cloud, a leader in green GPU cloud computing, announced a new partnership. The agreement will make Genesis Cloud’s 100% green energy Compute Instance available as part of ClearML’s powerful MLOps platform. With computing accounting for nearly 4% of global emissions in 2021 – and with that number likely set […]
Search Results for: machine learning
ClearML and Genesis Cloud Announce New MLOps Partnership Delivering 100% Green Energy Compute Solution for Machine Learning
October 25, 2022 by
Seagate Launches Lyve Cloud Analytics Platform to Optimize Machine Learning Operations and Accelerate Innovation
October 12, 2022 by
Seagate® Technology Holdings plc (NASDAQ: STX), a world leader in mass-data storage infrastructure solutions, announced the launch of Lyve™ Cloud Analytics platform, a complete cloud-based analytics solution that includes storage, compute, and analytics, to help Lyve Cloud customers lower the total cost of ownership (TCO) and accelerate time to value with their DataOps and MLOps (machine learning operations).
Research Highlights: Pen and Paper Exercises in Machine Learning
October 8, 2022 by
In this regular column we take a look at highlights for breaking research topics of the day in the areas of big data, data science, machine learning, AI and deep learning. For data scientists, it’s important to keep connected with the research arm of the field in order to understand where the technology is headed. Enjoy!
Enabling Federated Querying & Analytics While Accelerating Machine Learning Projects
September 26, 2022 by
In this special guest feature, Brendan Newlon, Solutions Architect at Stardog, indicates that for an increasing number of organizations, a semantic data layer powered by an enterprise knowledge graph provides the solution that enables them to connect relevant data elements in their true context and provide greater meaning to their data.
AI Under the Hood: Mixing Things Up – Optimizing Fluid Mixing with Machine Learning
September 9, 2022 by
Fluid mixing is an important part of several industrial processes and chemical reactions. However, the process often relies on trial-and-error-based experiments instead of mathematical optimization. While turbulent mixing is effective, it cannot always be sustained and can damage the materials involved. To address this issue, researchers from Japan (Tokyo University of Science) have now proposed an optimization approach to fluid mixing for laminar flows using machine learning, which can be extended to turbulent mixing as well.
The Secret to Automating Machine Learning Life Cycles
September 7, 2022 by
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.
SiMa.ai Ships Purpose-built Machine Learning SoC Platform to Customers for Embedded Edge Applications
August 30, 2022 by
SiMa.ai, the machine learning company enabling effortless deployment and scaling at the embedded edge, announced that it has begun shipping the industry’s first purpose-built software-centric Machine Learning System-on-Chip platform for the embedded edge – the MLSoC.
Federated Machine Learning and Its Impact on Financial Crime Data
August 25, 2022 by
In this special guest feature, Gary M. Shiffman, PhD, Co-founder and CEO, Consilient, takes a look at Federated Machine Learning, the branch of machine learning that’s sure to be a revolution for FCC professionals by enabling collaboration while preserving privacy. After all, money launderers are humans and therefore display consistent patterns of behavior. Machine learning (ML) technology, at its core, detects patterns across big data.
Machine Learning Model Management: Ensemble Modeling
August 23, 2022 by
In this contributed article, editorial consultant Jelani Harper highlights how the machine learning approach called ensemble modeling enables organizations to utilize an assortment of models and combine them, and their predictive accuracies, to get the best result.
A “Glass Box” Approach to Responsible Machine Learning
July 26, 2022 by
In this contributed article, editorial consultant Jelani Harper suggests that machine learning doesn’t always have to be an abstruse technology. The multi-parameter and hyper-parameter methodology of complex deep neural networks, for example, is only one type of this cognitive computing manifestation. There are other machine learning varieties (and even some involving deep neural networks) in which the results of models, how they were determined, and which intricacies influenced them, are much more transparent.
