2017新兴技术成熟度曲线_68页

2017 Hype Cycle for Emerging Technologies Summary

Core Content

The 2017 Hype Cycle for Emerging Technologies outlines key trends and technologies that are expected to shape the future of business and technology over the next five to ten years. It emphasizes the importance of understanding and adapting to these emerging technologies to maintain competitiveness in the digital economy.

Main Trends

The report identifies three main megatrends:

1. AI Everywhere

   • AI technologies are set to be the most disruptive due to their computational power and data capabilities.
   • Key technologies include: Deep Learning, Deep Reinforcement Learning, Artificial General Intelligence (AGI), Autonomous Vehicles, Cognitive Computing, Commercial UAVs (Drones), Conversational User Interfaces, Enterprise Taxonomy and Ontology Management, Machine Learning, Smart Dust, Smart Robots, and Smart Workspace.

2. Transparently Immersive Experiences

   • Technologies are becoming more human-centric, enhancing interactions between people, businesses, and things.
   • Key technologies include: 4D Printing, Augmented Reality, Brain-Computer Interface, Connected Home, Human Augmentation, Nanotube Electronics, Virtual Reality, and Volumetric Displays.

3. Digital Platforms

   • These technologies are foundational to enabling new business models and transforming how organizations operate.
   • Key technologies include: 5G, Digital Twin, Edge Computing, Blockchain, IoT Platform, Neuromorphic Hardware, Quantum Computing, Serverless PaaS, and Software-Defined Security.

Major Hype Cycle Changes

The 2017 Hype Cycle highlights several new and emerging technologies that are likely to be strategic in the coming years:

• New Technologies Introduced:

  • 5G
  • Artificial General Intelligence
  • Deep Learning
  • Deep Reinforcement Learning
  • Digital Twin
  • Cognitive Computing
  • Blockchain
  • Smart Dust
  • 4D Printing

• Technologies That Have Moved Significantly:

  • Blockchain
  • Commercial UAVs (Drones)
  • Software-Defined Security
  • Brain-Computer Interface

Priority Matrix

The report categorizes technologies based on their time to mainstream adoption and strategic importance:

Key Technologies by Stage

On the Rise (2–5 years to mainstream adoption):

• Augmented Data Discovery
• Cognitive Expert Advisors
• Deep Learning
• Edge Computing
• Commercial UAVs (Drones)
• IoT Platform
• Machine Learning
• Serverless PaaS
• Software-Defined Security
• Virtual Reality

At the Peak (5–10 years to mainstream adoption):

• 5G
• Deep Reinforcement Learning
• Digital Twin
• Augmented Reality
• Blockchain
• Cognitive Computing
• Connected Home
• Conversational User Interfaces
• Enterprise Taxonomy and Ontology Management
• Nanotube Electronics
• Neuromorphic Hardware
• Smart Robots
• Smart Workspace
• Virtual Assistants

Sliding Into the Trough (More than 10 years to mainstream adoption):

• 4D Printing
• Artificial General Intelligence
• Autonomous Vehicles
• Brain-Computer Interface
• Human Augmentation
• Quantum Computing
• Smart Dust
• Volumetric Displays

Off the Hype Cycle

Some technologies that were featured in the 2016 Hype Cycle are no longer included in the 2017 report, as they are now more mature or less emerging. These include:

• 802.11ax
• Affective Computing
• Context Brokering
• Gesture Control Devices
• Data Broker PaaS (dbrPaaS)
• Micro Data Centers
• Natural-Language Question Answering
• Personal Analytics
• Smart Data Discovery
• Virtual Personal Assistants

Technology Insights

• Smart Dust: Tiny wireless sensors that can detect environmental conditions, currently in the embryonic stage with limited commercial applications. It has transformational potential but remains in early development.
• 4D Printing: An emerging technology that allows printed objects to change shape or properties after printing. It is still in the embryonic stage but shows promise in various industries like healthcare and aerospace.
• Artificial General Intelligence (AGI): Remains in the realm of science fiction and theoretical discussions. While current AI is "weak AI," AGI is not expected to emerge in the next decade.
• Deep Reinforcement Learning: A machine learning technique that is gaining traction due to its success in areas like game playing and robotics. It is still in early stages and requires extensive training.

Conclusion

The 2017 Hype Cycle underscores the transformative potential of emerging technologies across various domains. It encourages enterprise architects and technology leaders to evaluate these technologies for strategic advantage, innovation, and long-term business impact. The report emphasizes the need for proactive investment and collaboration to stay ahead in the rapidly evolving digital landscape.