The 2022 Gartner Hype Cycle for Artificial Intelligence (AI) has revealed a number of game-changing innovations that promise to deliver benefits beyond those of traditional AI applications.
The Hype Cycle divides AI innovations into four main categories: data-centric AI, model-centric AI, applications-centric AI, and human-centric AI. Data-centric AI focuses on enhancing and enriching the data used to train algorithms. This shift from tweaking models to enhancing data could lead to significant improvements in AI performance.
Model-centric AI emphasizes on refining AI models for optimal outputs. This includes techniques such as physics-informed AI, composite AI, causal AI, generative AI, foundation models, and deep learning.
Applications-centric AI includes AI engineering, intelligent applications, and computer vision. Decision intelligence and edge AI are two promising areas of applications-centric AI that are expected to reach mainstream adoption soon. Human-centric AI focuses on the ethical and responsible use of AI. This includes techniques such as AI trust, risk, and security management (TRiSM), responsible AI, digital ethics, and AI maker and teaching kits.
The sources for this piece include an article in Gartner.
