2017新兴技术成熟度曲线(英文版)_68页
报告摘要
2017 Hype Cycle for Emerging Technologies Summary
Core Content
The 2017 Gartner Hype Cycle for Emerging Technologies highlights three major megatrends that are expected to have a profound impact on the future of business and technology:
- AI Everywhere: AI technologies are becoming increasingly disruptive due to their computational power and adaptability. They are expected to enable organizations to harness data for problem-solving and innovation.
- Transparently Immersive Experiences: Technology is evolving to become more human-centric, integrating seamlessly into daily life and work. This includes immersive experiences like Virtual Reality (VR) and Augmented Reality (AR).
- Digital Platforms: The foundation for future business models is being laid by digital platforms that provide the necessary infrastructure for data, computation, and connectivity.
These trends are supported by a range of emerging technologies, each with different maturity levels and potential impact on businesses.
Main Points
- AI Everywhere is at the peak of the Hype Cycle, showing that it is a key enabler for immersive and transparent experiences.
- Digital Platforms are rapidly ascending the Hype Cycle, indicating their growing importance in enabling new business models.
- Transparently Immersive Experiences are also moving up the Hype Cycle, driven by the integration of human-centric technologies.
Key Technologies
On the Rise (Embryonic to Early Adoption)
- Smart Dust: Tiny sensors that can detect various environmental factors, used in building controls, industrial monitoring, and security. Still in the embryonic stage with limited commercial applications.
- 4D Printing: Materials that can change shape after printing, with potential applications in aerospace, medical, and construction. It is still in the embryonic stage and will take over 10 years to mainstream.
- Artificial General Intelligence (AGI): Not yet realized, remains a concept in science fiction and research. AGI is not expected to emerge in the next 10 years.
- Deep Reinforcement Learning: A machine learning technique that uses rewards to guide behavior, with applications in game playing and robotics. It is in the early stages of adoption.
At the Peak (Maturity and High Adoption)
- Blockchain: Gaining traction in transforming industry operating models, especially in finance, manufacturing, healthcare, and education.
- Commercial UAVs (Drones): Used in various industries due to advancements in AI and computing. They are at the peak of the Hype Cycle.
- Software-Defined Security (SDSec): Enables flexible and dynamic security management across different locations and systems.
- Virtual Assistants: Provide unobtrusive and context-aware advisor-based solutions.
- Edge Computing: Enables data processing closer to the source, reducing latency and increasing efficiency.
- Machine Learning: Already providing significant benefits and is a key enabler for AI Everywhere and other trends.
Climbing the Slope (Early Adoption)
- Virtual Reality (VR): Becoming more immersive and integrated with other technologies like Brain-Computer Interface (BCI).
- Augmented Reality (AR): Gaining more visibility and integration with immersive experiences.
- Cognitive Computing: A mix of AI capabilities, hardware, and ICT, used to enhance human cognition.
Priority Matrix
The Priority Matrix categorizes technologies based on their benefit rating and time to mainstream adoption:
| Benefit Rating | Time to Mainstream Adoption |
|---|---|
| Transformational | Less than 2 years |
| High | 2 to 5 years |
| Moderate | 5 to 10 years |
| Low | More than 10 years |
Transformational (Less than 2 years)
- Augmented Data Discovery
- Blockchain
- 4D Printing
High (2 to 5 years)
- Cognitive Expert Advisors
- Cognitive Computing
- Deep Learning
- Conversational User Interfaces
- Autonomous Vehicles
- Artificial General Intelligence
- Brain-Computer Interface
- Smart Dust
- Volumetric Displays
Moderate (5 to 10 years)
- 5G
- Deep Reinforcement Learning
- Digital Twin
- Augmented Reality
- Connected Home
- Enterprise Taxonomy and Ontology Management
- Nanotube Electronics
- Neuromorphic Hardware
- Smart Robots
- Smart Workspace
- Virtual Assistants
Low (More than 10 years)
- Virtual Reality
- Serverless PaaS
- Software-Defined Security
Summary of Key Technologies
| Technology | Status | Key Impact | Vendor Examples |
|---|---|---|---|
| Smart Dust | Embryonic | Transformative for sensing and monitoring | Amphenol Advanced Sensors, Linear Technology |
| 4D Printing | Embryonic | Disruptive in product design and functionality | Autodesk, Stratasys |
| Artificial General Intelligence | Embryonic | Potential for massive disruption in the long term | N/A |
| Deep Reinforcement Learning | Early Adoption | Enabling intelligent decision-making | N/A |
| Blockchain | Peak | Transforming industry models | N/A |
| Commercial UAVs (Drones) | Peak | Changing logistics and delivery | N/A |
| Software-Defined Security | Peak | Enhancing security flexibility | N/A |
| Virtual Assistants | Climbing | Providing context-aware support | N/A |
| Edge Computing | Climbing | Reducing latency and increasing efficiency | N/A |
| Machine Learning | Climbing | Driving AI Everywhere | N/A |
Conclusion
The 2017 Hype Cycle underscores the importance of staying ahead of emerging technologies to maintain competitiveness. While some technologies are at the peak of hype, others are still in the early stages of development. Enterprise architects and technology leaders should focus on evaluating the potential of these technologies to create competitive advantage, generate value, and support transformational business models. The convergence of AI Everywhere, Transparently Immersive Experiences, and Digital Platforms will be pivotal in shaping the future of business and technology.
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