Artificial Intelligence Insight Series - Neuromorphic Chipsets Market Size, Application, Analysis, Regional Outlook, Competitive Strategies, and Forecasts, 2018 - 2023
ID : ME_045764 Format : PDF July, 2019 Publisher : Netscribes Pages : 58
The application of Artificial Intelligence (AI) is growing exponentially. This rapid expansion of AI software development, therefore, calls for a focused effort to build new hardware that can process the emerging AI algorithms.
Future of AI hardware will be defined by biologically-inspired neuromorphic chipsets, which provide a real time boost for AI systems. Brain-like chips deliver natural intelligence in major AI applications in the long-term, and have the desirable characteristics of intelligent sensors. The ultimate aim is to develop process technologies, materials, memories, and other building blocks for the integration of the neuron chips into sensors.
Focus is on the impact of neuromorphic hardware across different industries. Current status or limitations, and the future requirements and use cases for each industry have been considered to build the adoption scenario. The advantages offered by neuromorphic chipsets for the different verticals address how the new brain-inspired technology can help bridge the gap in the future.
The different industries included are:
The report includes an overview of the key players and active research projects in the domain. It covers different entities ranging from established semiconductor players and specialized neuromorphic solution providers, to universities and research institutes. The different parameters related to implementation level, market readiness, future focus, etc., are also highlighted. Additionally, the section includes an overview of emerging players and startups in ecosystem that are providing differentiated offerings and defining new frontiers in neuromorphic architecture and design.
A patent study has been conducted to understand the evolution of patent publications and countries of the patent filings. The key assignees and technology domains shaping the neuromorphic IP landscape have also been covered to assess upcoming trends.
A total of 700 patent publications have been identified as specific to neuromorphic hardware, out of which, the top five IP players are IBM, Qualcomm, SK Hynix, Intel, and Brain Corporation. The patent section also covers key technology areas, emerging entities, patent collaborations and geographical distribution of assignees.
Neuromorphic chipsets are laying the foundation for achieving artificial general intelligence (AGI) capabilities
Low power consumption, pattern recognition and stochastic operation are some of the key features that are driving adoption of neuromorphic chipsets across industries
Leading players are offering prototypes and making collaborative efforts with research institutes for applying neuromorphic technology in real-world applications
Startups and organizations focused on ultra-low-power solutions, neuromorphic vision systems, always-on operation and AGI models are gaining traction
The patent study highlights an increased focus towards the development of autonomous systems, including initial investigations on electronic synapses for the implementation of reinforcement learning and other innovative architectures
Neuromorphic chipsets play a critical role in the high-performance architectures envisioned for 2040 for building massive computational infrastructure
Key questions addressed in the report:
What is the state of commercialization for neuromorphic chipsets?
Which are the industries that would will drive the adoption of neuromorphic hardware?
What are the active entities in the domain? At what stage is their product offering?
What are the emerging entities in the neuromorphic chipsets space?
Which startups are attracting significant amount of funding? And what is the outlook for these companies?
How is the patent portfolio of the top assignees aligned in terms of various technology areas of interest including neurons, synapses, interconnects, memory, edge devices, etc.?
1.1. Introduction to the Architecture and Properties
1.2. Implementation of Neural Algorithms on Hardware
1.3. Spiking Neural Networks Driving Neuromorphic Computing
1.4. Neuromorphic Chipsets Transforming the AI Landscape
1.5. Key Features Enabling Industry-wide Adoption
2. Industry Adoption of Neuromorphic Chipsets
2.2. IoT Ecosystem
2.3. Financial Services
2.5. Space Industry
2.6. Medical Systems
3. Competitive Intelligence
3.1. Key Players
3.2. Active Research Projects
3.3. Increased Interest in Emerging Entities
3.4. Overview of the Startup Ecosystem
4. R&D in the Neuromorphic Hardware Domain
4.1. Universities active in the Domain
5. Patent Trend Analysis
5.1. Overview of the Patenting Activities
5.2. Top Technology Domains
5.3. Focus Areas of the Technology Domains
5.4. Assignees Across Geographies
5.5. Overview of Assignees
5.6. Top Assignees
5.7. Emerging Players and Top Universities
5.8. Other Important Activities
6. Key Takeaways
A research methodology is a systematic approach for assessing or conducting a market study. Researchers tend to draw on a variety of both qualitative and quantitative study methods, inclusive of investigations, survey, secondary data and market observation.
Such plans can focus on classifying the products offered by leading market players or simply use statistical models to interpret observations or test hypotheses. While some methods aim for a detailed description of the factors behind an observation, others present the context of the current market scenario.
Now let’s take a closer look at the research methods here.
Secondary Research Model:
Extensive data is obtained and cumulated on a substantial basis during the inception phase of the research process. The data accumulated is consistently filtered through validation from the in-house database, paid sources as well reputable industry magazines. A robust research study requires an understanding of the overall value chain. Annual reports and financials of industry players are studied thoroughly to have a comprehensive idea of the market taxonomy.
Post conglomeration of the data obtained through secondary research; a validation process is initiated to verify the numbers or figures. This process is usually performed by having a detailed discussion with the industry experts.
However, we do not restrict our primary interviews only to the industry leaders. Our team covers the entire value chain while verifying the data. A significant number of raw material suppliers, local manufacturers, distributors, and stakeholders are interviewed to make our findings authentic. The current trends which include the drivers, restraints, and opportunities are also derived through the primary research process.
The market estimation is conducted by analyzing the data collected through both secondary and primary research. This process involves market breakdown, bottom-up and top- down approach.
Moreover, while forecasting the market a comprehensive statistical time series model is designed for each market. Macroeconomic indicators are considered to understand the current trends of the market. Each data point is verified by the process of data triangulation method to arrive at the final market estimates.
The penultimate process results in a holistic research report. The study equips key industry players to undertake significant strategic decisions through the findings. The report encompasses detailed market information. Graphical representations of the current market trends are also made available in order to make the study highly comprehensible for the reader.
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