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Author Archives: George Leopold
George Leopold
George Leopold has written about science and technology for more than 30 years, focusing on electronics and aerospace technology. He previously served as executive editor of Electronic Engineering Times. Leopold is the author of "Calculated Risk: The Supersonic Life and Times of Gus Grissom" (Purdue University Press, 2016).AutoML Platform Kepler Targets Domain Experts
July 15th, 2020 Comments Off on AutoML Platform Kepler Targets Domain Experts
As more companies roll out digital infrastructure, they are ingesting greater volumes of data that can be used by business analysts to gauge customer intent and boost transactions. Complexity and lack of data scientists have made that transition harder ...
App Tracing Startup Emerges from Stealth
July 14th, 2020 Comments Off on App Tracing Startup Emerges from Stealth
As enterprise software architectures evolve beyond monolithic applications to delivering micro-services, debugging tools like distributed tracing are emerging to detect cyberattacks against one of the foundations of cloud-native deployments: APIs. With attacks proliferating on the hundreds of APIs used ...
Paige, AI for Pathology Startup, Attracts New Funding
July 13th, 2020 Comments Off on Paige, AI for Pathology Startup, Attracts New Funding
Medical applications for AI and machine learning have so far yielded mixed results. While proving useful in areas like medical imaging, where tools can help reduce confirmation bias, the technology has fallen short in other applications like drug discovery. ...
Nascent HCI Market Bestrides ‘Multi-Modal’ IT
July 10th, 2020 Comments Off on Nascent HCI Market Bestrides ‘Multi-Modal’ IT
Software-defined storage and virtualized servers have become key building blocks of hyperconverged IT infrastructure running on commodity equipment. VMware (NYSE: VMW) and its majority shareholder, Dell Technologies (NYSE: DELL), are among the leaders in the emerging HCI sector, with ...
PCIe Tools Aim to Speed Data Fabric Apps
July 9th, 2020 Comments Off on PCIe Tools Aim to Speed Data Fabric Apps
A design kit tailored to PCI Express 4.0 data fabrics combines orchestration software from infrastructure platform vendor Liqid and silicon switch giant Broadcom. The goal is accelerating application prototyping, testing and development that would expand enterprise adoption of higher-bandwidth ...
Suse Ups Kubernetes Game with Rancher Labs Deal
July 8th, 2020 (2)
The innovation engine that is Kubernetes is prompting infrastructure vendors to open their wallets to acquire developers whose platforms are based on the open source cluster orchestrator. Suse, the open source cloud infrastructure specialist, is the latest, moving to ...
Kubernetes Gets a Traffic Manager
July 8th, 2020 Comments Off on Kubernetes Gets a Traffic Manager
The Kubernetes ecosystem continues to expand with the adoption of a traffic manager for easing access to the orchestrator’s application services. The control plane called Contour was contributed to the Cloud Native Computing Foundation by VMware, which acquired the ...
AutoML Startup dotData Supports Container-Based Models
July 7th, 2020 Comments Off on AutoML Startup dotData Supports Container-Based Models
As data science platforms expand across enterprise applications like predictive analytics, automated machine learning vendors are steadily integrating AI models with emerging infrastructure to ease deployment and orchestration. For example, data science automation specialist dotData this week released a ...
Cyber Security is Recovery Focus as 5G Enthusiasm Wanes
July 2nd, 2020 Comments Off on Cyber Security is Recovery Focus as 5G Enthusiasm Wanes
The urgency of 5G wireless rollouts has diminished among executives in a monthly survey of global business conditions as enterprises shift their pandemic recovery focus to more pressing matters like securing virtual workforces and ensuring data privacy. The Economist ...
Machine Learning Is Living in the Past
July 1st, 2020 Comments Off on Machine Learning Is Living in the Past
Machine learning algorithms trained on large data sets have proven useful for spotting past patterns. Examples include stable environments like image databases or board games. When it comes to messy, real-world data, however, those same ML algorithms often fall ...