Conventional artificial intelligence (AI)-enabled processors are based on rule-based algorithms and are optimized for applications, such as real-time monitoring and reporting. However, with increasing demand for fully autonomous solutions, there is a need for perceptive solutions capable of making probabilistic decisions, replicating the human brain.
With technology advancements in chipset architecture and algorithms, neuromorphic chipsets are processing powerhouses that are logically analogous to neurons that exist in biological human brains and efficiently perform complicated decision-making tasks. Neuromorphic computing holds the potential to emerge as a vital breakthrough in applications across the healthcare, manufacturing, and aerospace & defense sectors. With increased funding and related support from government bodies and Tier-1 OEMs, neuromorphic solutions are poised to witness exponential traction from venture capitalists and government bodies in the years to come.
Key Questions Answered in the Technology and Innovation Study
- What is the significance of neuromorphic computing technology and its impact?
- What are the current trends and developments that are driving the opportunities for neuromorphic computing technologies in the global market?
- What are the technology capabilities of various emerging technologies in invasive and non-invasive segment boosting the neuromorphic computing?
- Key innovations and their application impact.
- IP and Funding scenario.
- Growth opportunities and critical success factors.
- What sort of strategies do OEMs need to embrace to gain entry and sustain in the competitive marketplace?
i. Strategic Imperatives
ii. About the Growth Pipeline Engine™
iii. Growth Opportunities Fuel the Growth Pipeline Engine™
Chapter 1 - Executive Summary
1.1 Scope of the Technology and Innovation Research
1.2 Research Methodology
1.3 Research Process and Methodology
1.4 Summary of the Key Findings
1.5 Impact of Enabling Technologies in Neuromorphic Computing Based Applications
Chapter 2 - Technology Landscape of Neuromorphic Computing
2.1 Neuromorphic Computing Technology Landscape - An Overview
2.2 R&D Trends: Key R&D Areas Strengthening Commercialization Potential of Invasive BCI Solutions
2.3 Key Technology Attributes to Focus on for Future Product Development
2.4 R&D Drivers: Government Supporting R&D Initiatives is a Major Driving Force for Advancements in Neuromorphic Computing
2.5 Market Drivers Accelerating the Growth of Neuromorphic Computing
2.6 Distributing Large Amount of Synapses on a Single Compact Chipset is a Major Bottleneck Hindering Wide-Scale Advancements in Neuromorphic Computing Space
2.7 Commercialization Pace and High Manufacturing Cost are Major Bottlenecks for Neuromorphic Computing
2.8 Patent Analysis: China Emerging as an Innovation Hub in Neurocomputing Industry
2.9 Patent Analysis: Semiconductor Giants Developing Breakthrough Neuro-Technologies
2.10 Regional Analysis: Government-Backed Organizations Across the Globe Supporting Research Initiatives in Neuromorphic Computing Domain
Chapter 3 - Stakeholder Ecosystem Analysis in Neuromorphic Computing
3.1 Value Chain Diagram of Neuromorphic Computing Industry
3.2 Extended Ecosystem of Neuromorphic Computing Industry
3.3 Competition Overview: Implanted Solutions Capable to Transfer Data at High Speed Holds the Future
3.4 Analysis of Value Chain - Role of Universities and Research Institutes
3.5 Analysis of Value Chain - Europe and China are Actively Involved in Development of Neuromorphic Solutions
3.6 Analysis of Value Chain - Role of Major Global Companies
3.7 Analysis of Value Chain - Innovations in Neuromorphic Chips Globally
3.8 Analysis of Value Chain - Supportive Pillars Propelling the Advancements in Neuromorphic Computing
3.9 Funding Analysis: BCI and Machine Learning are Major Supported Areas in the Field of Neuromorphic Computing
3.10 Funding Analysis: Governmental Support With Interest from Venture Capitalists is Key to Development of Neurocomputing Solutions
3.11 Analysis of Value Chain - Role of Hardware Manufacturers
3.12 Analysis of Value Chain - Leveraging Fabrication Technologies, Embedded Memories, SoCs and FPGAs for Developing Solutions in Neuromorphic Computing
3.13 Start-Up Analysis: Promising Start-Ups Developing Non-Invasive BCI Solutions Gaining Traction from VC Funds and Tier-1 OEMs
3.14 Emerging BCI-based Medical Applications
3.15 Emerging Neuro-Tech Start-Ups to Watch-Out
3.16 Emerging Start-Ups in Neurocomputing Domain
Chapter 4 - Application Diversity of Neuromorphic Computing
4.1 Application Segmentation Based on Industry Impact and Time to Market
4.2 Analysis of Applications Impacted by Neuromorphic Computing - Healthcare
4.3 Analysis of Applications Impacted by Neuromorphic Computing - Robotics, Manufacturing, Security and Surveillance
4.4 Analysis of Applications Impacted by Neuromorphic Computing - Home Automation, Retail, Banking and Finance
4.5 Analysis of Applications Impacted by Neuromorphic Computing - Automotive, Energy, Aerospace and Defence
Chapter 5 - Growth Opportunities and Strategic Insights
5.1 Growth Opportunities for Invasive and Non-Invasive Solutions
5.2 Growth Roadmap for Neuromorphic Solutions Will Depend on the Strength of IP Portfolio in Near Term
5.3 Impact of COVID-19 in Neuromorphic Computing Applications
Chapter 6 - Key Contacts
Chapter 7 - Next Steps
7.1 Your Next Steps