Global Edge AI Accelerators Emerging Opportunity Analysis Report 2023: Emerging Grow in Developing Workload-specific AI Accelerators, AI Chips in Smaller Devices, & Development of Faster Interconnects

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Oct 16, 2023, 13:15 ET

DUBLIN, Oct. 16, 2023 /PRNewswire/ -- The "Edge AI Accelerators - Emerging Opportunity Analysis" report has been added to ResearchAndMarkets.com's offering.

The report offers comprehensive insights on the edge AI accelerator market, including a comparative analysis of key edge AI processors, emerging use cases, and an overview of pivotal AI accelerator technologies.

Furthermore, it enlightens on technology trends, business trade models, and the key strategies adopted by industry players. A regional analysis of this rapidly evolving market is also included. By developing an understanding of these critical aspects, businesses can stay ahead of the curve in their understanding and utilization of the edge AI accelerator space.

Specialized edge AI hardware that enables quick deep learning on-device has become essential due to the rising need for real-time deep learning workloads. Additionally, a cloud-based AI method cannot ensure data privacy, low latency, or offer high bandwidth. As a result, many AI workloads are shifting to the edge, increasing the demand for specialized AI hardware for on-device machine learning inference.

The growth of IoT, smart technology adoption by consumer electronics and the automotive industry, and intelligent industrial automation are propelling the edge AI accelerator market. AI accelerators in consumer-oriented applications, such as smartphones, wearables, and smart appliances, need to have a high processing-to-cost ratio as well as a smaller size. On the other hand, for most of the AI accelerators used in industrial/enterprise applications, the requirement for high processing speed and power efficiency are of prime significance.

The majority of chip manufacturers are struggling to improve processing speed while reducing power consumption. To overcome this, organizations are investing in developing application-specific chips, efficient chip architectures, new algorithms, advanced memories, and alternative materials. To leverage these technological advancements, major corporations are embracing technology strategies such as partnerships and acquisitions.

The market for edge AI accelerators is projected to grow significantly in the United States, South Korea, China, Japan, Germany, and Israel. This is due to the high amount of manufacturing activity pertaining to consumer electronics, automotive, industrial equipment, and defense. Apart from having a strong manufacturing base, these countries have also developed a strong ecosystem for chip manufacturing, which is crucial to maintaining a dominant position in the market.

The emergence of deep learning, neural networks, computer vision, generative artificial intelligence, and neuromorphic computing has created new opportunities for edge inferencing applications. While enterprises are quickly moving towards a decentralized computer architecture, they are also learning new methods to apply this technology to boost productivity and cut costs.

Therefore, AI chip developers should focus more on developing solutions that are designed to fulfill these requirements specific to use cases.

This research report covers the following topics:

Overview and significance of key AI accelerator technologies
Comparative analysis of key edge AI processors
Emerging use cases
Technology trends and key developmental strategies used by players in the industry
Business models in the AI accelerator chip industry
Regional analysis of the edge AI accelerator space
AI accelerators roadmap
Growth opportunities

Key Topics Covered:

1. Strategic Imperatives

Why Is It Increasingly Difficult to Grow?
The Strategic Imperative
The Impact of the Top 3 Strategic Imperatives of Edge AI Accelerators Industry
Growth Opportunities Fuel the Growth Pipeline EngineT
Research Methodology

2. Growth Opportunity Analysis

Scope of Analysis
Segmentation of Edge AI Accelerators Used In Different Industries
Growth Drivers
Growth Restraints

3. Emerging Opportunity Analysis - Edge AI Accelerators

Executive Summary
Key Hardware Technologies - CPU Overview
Key Hardware Technologies - GPU Overview
Key Hardware Technologies - ASIC Overview
Comparative Analysis of Key Edge AI CPUs, GPUs, and ASICs
Analysis of Key Performance Factors for Different Applications
Emerging Use Cases of Edge AI Accelerators
Convergence Scenario: Enhancing Employee Safety in Industrial Environments
Strategic Partnerships
Mergers and Acquisitions
Key Innovation Themes
Key Players and New Product Development Initiatives
Start-ups and New Product Development Initiatives
Business Models in the AI Accelerator Chip Industry
Ecosystem of Edge AI Accelerators
Regional Analysis of Edge AI Accelerator - APAC
Regional Analysis of Edge AI Accelerator - Europe and Israel
Regional Analysis of Edge AI Accelerator - North America
AI Accelerators Roadmap

4. Growth Opportunity Universe

Growth Opportunity 1: Developing Workload-specific AI accelerators
Growth Opportunity 2: Including AI Chips in Smaller Devices
Growth Opportunity 3: Development of Faster Interconnects

5. Appendix

For more information about this report visit https://www.researchandmarkets.com/r/hknwyu

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