In this contributed article, editorial consultant Jelani Harper offers his perspectives around 2023 trends for the boundless potential of generative Artificial Intelligence—the variety of predominantly advanced machine learning that analyzes content to produce strikingly similar new content.
Search Results for: machine learning
2023 Trends in Artificial Intelligence and Machine Learning: Generative AI Unfolds
November 28, 2022 by Leave a Comment
Machine Learning Career Path: Exploring Opportunities in 2022 and Beyond
November 18, 2022 by Leave a Comment
In this special guest feature, George Tsagas, Owner of eMathZone, discusses how machine learning professionals can work as data scientists, computer engineers, robotics engineers, or managers. But if you want to make a career, the first step in finding opportunities in the field of machine learning is to understand the different types of jobs and skills needed.
Comet Introduces Kangas, An Open Source Smart Data Exploration, Analysis and Model Debugging Tool for Machine Learning
November 16, 2022 by Leave a Comment
Comet, provider of a leading MLOps platform for machine learning (ML) teams from startup to enterprise, announced a bold new product: Kangas. Open sourced to democratize large scale visual dataset exploration and analysis for the computer vision and machine learning community, Kangas helps users understand and debug their data in a new and highly intuitive way.
How Conversation Design is Using Machine Learning to Make Robots More Helpful
November 9, 2022 by Leave a Comment
In this special guest feature, Dmitry Gritsenko, CEO of the Master of Code Global, suggests that as interest in the commercial use of conversation design continues to rise, it’s a great time to look at the technologies that are making all of this possible as well as its impact on users today and in the future.
The Move Toward Green Machine Learning
November 6, 2022 by Leave a Comment
A new study suggests tactics for machine learning engineers to cut their carbon emissions. Led by David Patterson, researchers at Google and UC Berkeley found that AI developers can shrink a model’s carbon footprint a thousand-fold by streamlining architecture, upgrading hardware, and using efficient data centers.
ClearML and Genesis Cloud Announce New MLOps Partnership Delivering 100% Green Energy Compute Solution for Machine Learning
October 25, 2022 by Leave a Comment
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 […]
Seagate Launches Lyve Cloud Analytics Platform to Optimize Machine Learning Operations and Accelerate Innovation
October 12, 2022 by Leave a Comment
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 Leave a Comment
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 Leave a Comment
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 Leave a Comment
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.
