The Analyst Team
Research Director, Cloud and Data Center
Vlad is responsible for the cloud and data center research practice’s expanding roadmap, focused on disruptive trends such as the shift to edge computing, the evolution of compute silicon, and the need for efficiency improvements and sustainability in the data center industry.
Vlad joined Omdia, formerly IHS Markit Technology, in 2016. He developed many of our unique, industry-leading analyses including our flagship open computing equipment research and our three-way server market reconciliation process. He’s held senior positions at Intel and Ciena, where his data-led insights served as a central input into the companies’ strategies. Key market models he developed include an in-depth analysis of telecommunications network operations costs, a PC inventory tracker, and an actionable IOT market forecast. Vlad’s work has even facilitated decision-making in the British Parliament. He holds a Bachelor of Science degree in economics and management from Aston University, UK.
Research Director, AI and Intelligent Automation
Natalia Modjeska leads the AI & IA research team at Omdia. She has 15+ years of experience in developing and deploying analytics and AI. Her diverse career includes R&D, product and program management, sales, consulting, and client advisory. She has worked with organizations of all sizes and levels of maturity across many industries and geographies helping clients to harness the power of data, advanced analytics and AI for transformative change. She has advised 200+ organizations around the globe on topics ranging from AI strategy and use cases, to execution, best practices, governance, ethics, emerging trends, and vendor due diligence.
Natalia is passionate about helping clients to demystify AI/ML and to deploy these technologies responsibly. As part of that effort, she serves as an expert on the ISO/IEC JTC 1/SC 42 - AI Standards working group and she volunteers with several non-profits to develop responsible AI certification; increase AI literacy and improve government through innovative technologies. Natalia holds a PhD in AI (NLP) from the University of Edinburgh in Scotland and an Executive MBA from the Ivey School of Business (Western University).
High Performance Computing for Artificial Intelligence Applications – 2022 Data
Data / 08 Nov 2022 / Neil Dunay
This report forecasts revenue from high performance computing systems used for artificial intelligence workloads, including servers, software, networking, and storage. The forecast is broken down by end-user industry, workload type, and geographic region, from 2020 to 2027.
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