Gartner today highlighted top trends impacting the future of DataScience and MachineLearning to meet the increasing significance of data in AI. Read more: GartnerDA GartnerIT DataAnalytics
Gartner recommends organizations evaluate
based on their ability to resolve distributed data challenges, as well as to access and integrate with data sources outside of their immediate environment.is growing to enable the processing of data at the point of creation at the edge, helping organizations to gain real-time insights, detect new patterns and meet stringent data privacy requirements. Edge AI also helps organizations improve the development, orchestration, integration and deployment of AI.
Gartner predicts that more than 55% of all data analysis by deep neural networks will occur at the point of capture in an edge system by 2025, up from less than 10% in 2021. Organizations should identify the applications, AI training and inferencing required to move to edge environments near IoT endpoints.makes AI a positive force, rather than a threat to society and to itself.
, as well as by industries looking to grow through AI technologies and AI-based businesses. By the end of 2026, Gartner predicts that more than $10 billion will have been invested in AI startups that rely on foundation models – large AI models trained on huge amounts of data.of more than 2,500 executive leaders found that 45% reported that recent hype around ChatGPT prompted them to increase AI investments.
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