Operations | Monitoring | ITSM | DevOps | Cloud

civo

How to overcome common challenges in machine learning deployments

Apr 2, 2024 By Josh Mesout In Civo
🚨 To read the full findings from this research, visit The Machine Learning State of Play 2024 white paper. Are the challenges of deploying machine learning (ML) overshadowing its true potential in the modern workplace? Through our recent white paper , we spoke to 500+ developers who have experience working with ML systems to gain an understanding of the pain points faced by developers when using ML solutions.
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circleci

From MLOps to LLMOps: The evolution of automation for AI-powered applications

Mar 25, 2024 By Jacob Schmitt In CircleCI
Machine learning operations (MLOps) has become the backbone of efficient artificial intelligence (AI) development. Blending ML with development and operations best practices, MLOps streamlines deploying ML models via continuous testing, updating, and monitoring. But as ML and AI use cases continue to expand, a need arises for specialized tools and best practices to handle the particular conditions of complex AI apps — like those using large language models (LLMs).
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influxdata

Machine Learning and Infrastructure Monitoring: Tools and Justification

Mar 20, 2024 By Charles Mahler In InfluxData
In the rapidly changing world of technology, effective monitoring is critical for maintaining your infrastructure and ensuring it performs effectively. While traditional monitoring methods are effective, they can fall short as systems scale and become more dynamic and complex. This article aims to bridge the gap by introducing software engineers to the power of machine learning (ML) in infrastructure monitoring, outlining not just the ‘how’ but the ‘why’ of its application.
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elastic

Machine learning vs. AI: Understanding the differences

Mar 7, 2024 By Aditya Tripathi, In Elastic
For a long time, AI was almost exclusively the plaything of science fiction writers, where humans push technology too far, to the point it comes alive and — as Hollywood would have us believe — starts to wreak havoc. Cheery stuff! However, in recent years, we’ve seen an explosion of AI and machine learning technology that, so far, has shown us a fun side with people using AI for creating, planning, and ideating in a big way.
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jfrog

Advancing MLOps with JFrog and Qwak

Feb 28, 2024 By Yonatan Arbel In JFrog
Modern AI applications are having a dramatic impact on our industry, but there are still certain hurdles when it comes to bringing ML models to production. The process of building ML models is so complex and time-intensive that many data scientists still struggle to turn concepts into production-ready models. Bridging the gap between MLOps and DevSecOps workflows is key to streamlining this process.
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jfrog

Four Key Lessons for ML Model Security & Management

Feb 21, 2024 By Zohar Sacks In JFrog
With Gartner estimating that over 90% of newly created business software applications will contain ML models or services by 2027, it is evident that the open source ML revolution is well underway. By adopting the right MLOps processes and leveraging the lessons learned from the DevOps revolution, organizations can navigate the open source and proprietary ML landscape with confidence.
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opsmatters

How Machine Learning is Reshaping Your Business

Feb 18, 2024 By OpsMatters In OpsMatters
Machine learning, a subset of artificial intelligence (AI), has emerged as a powerful tool for reshaping the landscape of business operations. By leveraging algorithms and statistical models, machine learning enables computers to learn from data and make predictions or decisions without explicit programming. In this blog, we'll delve into the transformative impact of machine learning on various aspects of business, from enhancing customer experience to driving innovation and ensuring data security.
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AI vs. ML: What's the Difference? + What is #aiops in 60 Seconds | #backtobasics | LogicMonitor

Feb 6, 2024 By LogicMonitor In LogicMonitor
Ever wonder what #machinelearning (#ml) really means? Or how it's different from #ai? What even is #aiops? This #BackToBasics short explains it ALL in plain English! #shorts Follow us...
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