Gartner Research

Hype Cycle for Artificial Intelligence, 2018

Summary

AI is almost a definition of hype. Yet, it is still early: New ideas will surface and some current ideas will not live up to expectations. This Hype Cycle will help CIOs and IT leaders trace essential trends and innovations to determine scope, state, value and risk in their AI plans.

Published: 24 July 2018

ID: G00357478

Analyst(s): Svetlana Sicular ,  Kenneth Brant

Table Of Contents

Analysis

  • What You Need to Know
  • The Hype Cycle
  • The Priority Matrix
  • Off the Hype Cycle
  • On the Rise
    • AI Governance
    • Artificial General Intelligence
    • AI Developer Toolkits
    • Knowledge Graphs
    • Neuromorphic Hardware
    • AI-Related C&SI Services
    • Human-in-the-Loop Crowdsourcing
    • Natural-Language Generation
    • Chatbots
  • At the Peak
    • AI PaaS
    • Deep Neural Network ASICs
    • Smart Robots
    • Conversational User Interfaces
    • Intelligent Applications
    • Digital Ethics
    • Graph Analytics
    • Prescriptive Analytics
    • Deep Neural Nets (Deep Learning)
    • VPA-Enabled Wireless Speakers
    • Machine Learning
    • NLP
    • Robotic Process Automation Software
    • Virtual Assistants
    • Cognitive Computing
  • Sliding Into the Trough
    • FPGA Accelerators
    • Computer Vision
    • Predictive Analytics
    • Autonomous Vehicles
    • Commercial UAVs (Drones)
    • Augmented Reality
    • Knowledge Management Tools
  • Climbing the Slope
    • Virtual Reality
  • Entering the Plateau
    • GPU Accelerators
    • Ensemble Learning
    • Speech Recognition
  • Appendixes
    • Hype Cycle Phases, Benefit Ratings and Maturity Levels

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