Dublin, March 21, 2023 (GLOBE NEWSWIRE) -- The "Global Edge AI Hardware Market Size, Share & Industry Trends Analysis Report By Function (Inference and Training), By Device Type, By Component (Processor, Memory and Sensor & Others), By Vertical, By Regional Outlook and Forecast, 2022 - 2028" report has been added to ResearchAndMarkets.com's offering.
The Global Edge AI Hardware Market size is expected to reach $21.4 billion by 2028, rising at a market growth of 17.4% CAGR during the forecast period.
Specialized Edge AI hardware, commonly referred to as AI accelerators, increases data-intensive deep learning inference on Edge devices, making them an attractive choice for many compute-intensive jobs. With the increasing demand for real-time deep learning workloads, specialized Edge AI hardware that enables rapid deep learning on the device has become more and more essential.
In addition, the current standard (cloud-based) AI solution is inadequate for covering bandwidth, ensuring data privacy, and providing low latency. Therefore, AI tasks must be relocated to the Edge. Edge AI may operate on a variety of hardware platforms, ranging from standard MCUs to powerful neural processing processors. Edge AI hardware devices include IoT devices and machines.
Edge AI-connected devices monitor device behavior and gather and evaluate device data using embedded algorithms. The devices will make judgments, automatically resolve issues, and anticipate future performance. All of this is performed without human intervention. In addition to smartphones, laptops, Smart Driven cars, and Raspberry PIs, other examples of Edge AI devices are smartphones, laptops, Smart Driven cars, and Raspberry PIs.
Edge artificial intelligence (edge AI) is a paradigm for designing artificial intelligence (AI) workflows that span centralized data centers (the cloud) and devices outside the cloud that are closer to humans and physical things (the edge).
This is in contrast to the common practice of developing and running AI applications wholly in the cloud, which has come to be known as cloud AI. It also varies from traditional techniques to AI development, in which AI algorithms were created on desktops and then deployed on desktops or specialized hardware for tasks such as reading check numbers.
COVID-19 Impact Analysis
The crisis is causing uncertainty in the stock market, a decline in corporate confidence, a major slowdown in the supply chain, and an increase in customer concern.
The breakout of COVID-19 has had a significant influence on the operations of production and manufacturing industries, which in turn has hindered the expansion of the edge AI hardware market.
In addition, the COVID-19 pandemic has affected the electronics industry, as production facilities have been halted, which has led to an increase in demand for electronics and semiconductor products among industries. It significantly impacts manufacturing in Europe and Chinese exports, which may impede the market's growth.
Market Growth Factors
Mission-Critical Applications Necessitating Minimal Latency And Real-Time Data Transmission
In edge AI, machine learning algorithms handle IoT-generated data on near-end devices to solve the issues of excessive latency and insufficient security.
A vast amount of data collected by an IoT device is sent to the cloud, where machine learning (ML) models are executed and the processed data is transferred back to the device, which may cause a delay in response. However, AI in the gadget reduces data exchange, allowing for a quicker response.
The Emergence Of 5G Networks That Integrate It And Telecom
IT and telecoms are collaborating to deliver new capabilities for high-end apps and reduce network latency with the introduction of 5G networks.
The 5G network enables the development of data centers at edge modules and the implementation of industry-specific networks in a single environment using virtualization and software-defined networking principles. Critical AI applications like autonomous vehicles, industrial automation, surgery, and robotics require ultra-low latency.
Market Restraining Factors
Limitations Associated With AI Edge Devices
Currently, pre-trained ML models are employed for inference in edge AI. These models automatically adjust based on user data and requirements.
Training a model requires a significant amount of computer power, and because edge AI has limited access to training data, it is more susceptible to uncertainty and unpredictability. In addition, edge AI can perform small transfer learning tasks but cannot perform deep learning tasks. Concerns that cloud computing encounters include latency issues, privacy worries, and bandwidth limitations.
Key Market Players
List of Companies Profiled in the Report:
- Apple, Inc.
- MediaTek, Inc.
- Qualcomm, Inc.
- Huawei Technologies Co., Ltd.
- Samsung Electronics Co., Ltd. (Samsung Group)
- Intel Corporation
- Nvidia Corporation
- IBM Corporation
- Google LLC
- Microsoft Corporation
Key Topics Covered:
Chapter 1. Market Scope & Methodology
Chapter 2. Market Overview
2.1 Introduction
2.1.1 Overview
2.1.1.1 Market Composition & Scenarios
2.2 Key Factors Impacting the Market
2.2.1 Market Drivers
2.2.2 Market Restraints
Chapter 3. Competition Analysis - Global
3.1 The Cardinal Matrix
3.2 Recent Industry Wide Strategic Developments
3.2.1 Partnerships, Collaborations and Agreements
3.2.2 Product Launches and Product Expansions
3.2.3 Acquisition and Mergers
3.3 Top Winning Strategies
3.3.1 Key Leading Strategies: Percentage Distribution (2018-2022)
3.3.2 Key Strategic Move: (Product Launches and Product Expansions: 2019, May - 2022, Sep) Leading Players
3.3.3 Key Strategic Move: (Partnerships, Collaborations & Agreements: 2020, Apr - 2022, Aug) Leading Players
Chapter 4. Global Edge AI Hardware Market by Function
4.1 Global Inference Market by Region
4.2 Global Training Market by Region
Chapter 5. Global Edge AI Hardware Market by Device Type
5.1 Global Smartphones Market by Region
5.2 Global Surveillance Cameras Market by Region
5.3 Global Wearables Market by Region
5.4 Global Robots Market by Region
5.5 Global Smart Speakers & Smart Mirrors Market by Region
5.6 Global Automotive Market by Region
5.7 Global Edge Servers Market by Region
Chapter 6. Global Edge AI Hardware Market by Component
6.1 Global Processor Market by Region
6.2 Global Memory Market by Region
6.3 Global Sensor & Others Market by Region
Chapter 7. Global Edge AI Hardware Market by Vertical
7.1 Global Consumer Electronics Market by Region
7.2 Global Smart Home Market by Region
7.3 Global Automotive & Transportation Market by Region
7.4 Global Government Market by Region
7.5 Global Healthcare Market by Region
7.6 Global Industrial Market by Region
7.7 Global Aerospace & Defense Market by Region
7.8 Global Construction Market by Region
7.9 Global Others Market by Region
Chapter 8. Global Edge AI Hardware Market by Region
Chapter 9. Company Profiles
For more information about this report visit https://www.researchandmarkets.com/r/77gryw
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