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This article is part of: Edge Insights
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In light of the fast-evolving climate surrounding edge AI, we take stock of the upside and the downside risks that may move the needle on our recent Edge AI market forecast.
Five key trends that could significantly impact the edge AI market
- Strategic direction of big tech: In this section we analyse the different approaches adopted by Amazon Web Services (AWS), Google Cloud, Microsoft Azure and Nvidia towards edge AI. In addition, we profile key players looking to disrupt the growing market for bespoke AI accelerators designed for deployment in edge environments.
- AI regulation: Here, we look at the impact of regulation governing the nature of AI systems on edge AI deployment, and how this intersects with data residency and sovereignty regulation.
- The GPUaaS ‘goldrush’: In this section we look at how the frenzy to build GPU-equipped infrastructure, that can train AI models, is influencing the edge AI landscape.
- The impact of GenAI at the edge: This section examines the drivers of the deployment of GenAI at the edge, and the obstacles that lie in its way.
- Federated learning: Here, we look at the impact of federated learning, and its ramifications on select industry verticals, and in the hardware deployed on-premise.
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This report accompanies STL Partners’ edge AI forecast
Our recently published Edge AI market forecast models the total addressable market for 12 leading edge AI use cases, segmented by value chain component, industry vertical and AI revenue impact.
Total edge AI addressable revenue (2023–2030)
Table of contents
- Executive summary
- Introduction
- External pressures on the forecast
- Strategic direction of big tech
- Nvidia
- ‘The big three’
- Trends in AI regulation
- Implications of the GPUaaS ‘goldrush’
- Generative AI at the edge
- Federated learning
- Strategic direction of big tech
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