Topic: ml
At its summit, Red Hat advances OpenShift AI
Red Hat today announced advances in Red Hat OpenShift AI, an artificial intelligence (AI) and machine learning (ML) platform that enables enterprises to create and deliver AI-enabled applications at scale across hybrid clouds. OpenShift AI was designed to help organizations struggling with bringing AI models into production, the company said in its announcement. Among those … continue reading
ITOps Times Open-Source Project of the Week: Power Grid Model
Power Grid Model is a high-performance Python/C++ library for steady-state distribution of power system analysis that offers optimized algorithms for the characteristics of the distribution grid. The project also offers full support of three-phase asymmetric calculation and efficient C++ implementation with native parallel computing support. This technology can be used for Monte-Carlo low voltage grid … continue reading
Civo launches Kubeflow as a Service
Cloud provider Civo launched a Kubeflow as a Service offering to reduce the time and resources it takes for developers to gain insights from ML algorithms. Only 53% of AI projects make it from prototype to production, according to Gartner research, and this is likely due to the vast and complex infrastructure required to support … continue reading
Zscaler announces new Zero Trust capabilities
Zscaler announced newly advanced AI/ML innovations for better user protection and digital experience monitoring in Zscaler’s Zero Trust Exchange security platform. This comes as organizations are facing a 314% increase in cyberattacks on encrypted internet traffic and an 80% increase in ransomware with nearly a 120% increase in double extortion attacks, the company found in … continue reading
Enhancing observability with AI in HCL Workload Automation
Organizations now are looking towards AI intelligence to help operators avoid manual operations, whether it’s due to the sheer number of alerts that they’re getting that are contributing to “alert fatigue” or the lack of observability of how the organization is working. HCL has introduced a new set of features to its HCL Workload Automation … continue reading
Report: Cloud application monitoring remains the biggest challenge for SREs
Just over half of SREs (53%) said that the number one cloud application monitoring challenge is unified visibility across the stack. Organizations are looking toward AI and machine learning to solve these problems, but adoption of AIOps is slow. This is according to the 2021 SRE Report that was conducted by the digital experience monitoring … continue reading
Splice Machine’s Livewire brings operational AI to industrial IoT
Splice Machine announced a new open-source AI platform, Livewire, designed to combine data and AI, and alert plant operators of likely outages or performance degradation soon enough for them to take remedial action. According to the company, the platform enables teams of data engineers, operators, and data scientists to work together with unprecedented speed and … continue reading
Report: Most SOCs are using AI and machine learning tools to detect advanced threats
The 2020 State of Security Operations report found that SecOps teams are more often turning to next-generation automation tools to address gaps in security with 93% of respondents saying that they employ AI and ML technologies with the leading goal of improving advanced threat detection. The report was conducted by Micro Focus and CyberEdge Group, … continue reading
premium 3 reasons enterprises need to implement AIOps
Competitive organizations don’t simply react to their environments or competitors. Rather, they are proactively and predictively anticipating how to deliver better business outcomes. These autonomous digital enterprises know how to pull all the relevant information, capabilities, and people into the same place to quickly and efficiently make the right decisions. This requires flexible and dynamic … continue reading
Deploying AIOps in ITOM should not require writing and maintaining manual rules
There is a lot of interest around AIOps, with multiple studies finding that organizations are adopting AI at an increasing rate. In a recent Forrester report 68% of companies surveyed have plans to invest in AIOps-enabled monitoring solutions over the next 12 months. Gartner forecasts that by 2022, 40% of all large enterprises will combine … continue reading
NVIDIA launches data center inference platform for AI-powered services
NVIDIA announced two advances to its GPU technology this week at GTC Japan, both aimed at AI-powered voice, video, image and recommendation inference acceleration. The first is NVIDIA TensorRT Hyperscale Inference Platform, an inference software solution which runs on the second component of the announcement, the NVIDIA Tesla T4 GPU, based on the NVIDIA Turing … continue reading
Robin Systems brings Kubernetes to Big Data, database and AI/ML apps
Robin Systems wants to extend Kubernetes to data-heavy apps with the release of its hyper-converged Kubernetes platform ROBIN. The new platform is designed to bring the benefits of Kubernetes to Big Data, databases, and artificial intelligence/machine learning solutions. “Kubernetes is the de-facto standard for container orchestration for microservices and applications. However, enterprise adoption of big … continue reading
