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Neuromorphic Computing Opportunity Analysis 2020: Leveraging Fabrication Technologies, Embedded Memories, SoCs and FPGAs for Developing Solutions in Neuromorphic Computing

iii. Growth Opportunities Fuel the Growth Pipeline Engine Chapter 1 - Executive Summary 1.2 Research 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

Global Neuromorphic Computing Opportunity Analysis Report 2020: Invasive and Non-invasive Solutions Drive Opportunities

Dublin, Feb. 22, 2021 (GLOBE NEWSWIRE) The "Neuromorphic Computing: Opportunity Analysis" report has been added to ResearchAndMarkets.com's offering. 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 governme

Neuromorphic Computing Opportunity Analysis 2020: Promising Start-Ups Developing Non-Invasive BCI Solutions Gaining Traction from VC Funds and Tier-1 OEMs – ResearchAndMarkets com

ResearchAndMarkets.com’s offering. 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 governme

New Tech Developments We re Actually Excited About in 2021

Smarter Cars: Auto Makers Experiment With Chips That Think Like Humans

Dec. 10, 2020 3:25 pm ET Experimental computer chips that try to mimic the way human brains work could accelerate the use of voice and gesture commands in automobiles, researchers at Intel Corp. and Accenture PLC say. The cutting-edge technique, known as neuromorphic computing, could use significantly less energy than traditional computer- and graphic-processing units that connect wirelessly to a car via the cloud. Today’s cars don’t have the AI capabilities to recognize many speech and gesture commands, in part because of the energy requirements necessary to make those functions work. Car makers are recognizing the need for AI methods that consume less energy, which is one reason why neuromorphic computing can be beneficial, said Tim Shea, technology researcher at Accenture Labs. “They’re already running up against limitations of [current chips] not being scalable enough,” he said.

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