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 | Jobs Reply


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Specialized Edge AI hardware, commonly known as AI accelerators, augments data-intensive deep learning inference on Edge devices, making them an attractive choice for many compute-intensive jobs.

New York, Dec. 22, 2022 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Global Edge AI Hardware Market Size, Share & Industry Trend Analysis Report By Application, By Device Type, By Component, By By Vertical, By Regional Preview and Forecast, 2022 – 2028” – https://www.reportlinker.com/p06374119/?utm_source=GNW
With the growing demand for real-time deep learning workloads, specialized Edge AI hardware that enables fast deep learning on the device has become more and more essential.

In addition, the current standard (cloud-based) AI solution is insufficient to cover bandwidth, ensure data privacy, and provide low latency. Therefore, AI tasks must be relocated to the Edge. Edge AI can run on a variety of hardware platforms, 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 collect and evaluate device data using embedded algorithms. The devices will make judgments, resolve issues automatically, and predict future performance. All this is done without human intervention. In addition to smartphones, laptops, Smart Drive cars, and Raspberry Pis, other examples of Edge AI devices are smartphones, laptops, Smart Drive cars, and Raspberry Pis.

Edge artificial intelligence (AI edge) is a paradigm for designing artificial intelligence (AI) workflows that includes centralized data centers (the cloud) and devices outside the cloud that are closer to people and physical objects (the edge). This is in contrast to the common practice of developing and running AI applications entirely in the cloud, which has come to be known as cloud AI. It also varies from traditional techniques to AI development, where AI algorithms were created on desktop computers and then deployed on desktop computers 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 anxiety. The outbreak of COVID-19 has had a significant impact on the operations of the production and manufacturing industries, hampering the expansion of the AI ​​edge hardware market. In addition, the COVID-19 pandemic has affected the electronics industry, as production facilities have been shut down, leading to an increase in demand for electronics and semiconductor products among the industries. It has a significant impact on European manufacturing and Chinese exports, which may hamper market growth.

Market Growth Factors

Mission-Critical Applications That Require Minimum Latency and Real-Time Data Transmission

In the AI ​​edge, machine learning algorithms handle IoT-generated data on near-end devices to solve issues of over-latency and insufficient security. A huge amount of data collected by an IoT device is sent to the cloud, where machine learning (ML) models are built and the processed data is transferred back to the device, which can delay response. However, AI in the widget reduces data exchange, allowing for a faster response.

The Emergence of 5G Networks That Integrate It And Telecom

IT and telecommunications are collaborating to provide new capabilities for advanced apps and reduce network latency with the introduction of 5G networks. The 5G network enables data centers to develop edge modules and implement industry-specific networks in a single environment using virtualization and software-defined networking principles. Critical AI applications such as autonomous vehicles, industrial automation, surgery and robotics require ultra-low latency.

Market Restraining Factors

Limitations of AI Edge Devices

Currently, pre-trained ML models are used for inference in edge AI. These models automatically adjust based on user data and needs. Training a model requires a significant amount of computing power, and because edge AI has limited access to training data, it is more susceptible to uncertainty and unpredictability. Furthermore, edge AI can perform small transfer learning tasks but cannot perform deep learning tasks. Concerns with cloud computing include latency issues, privacy concerns, and bandwidth limitations.

Outlook Device Type

By Device Type, the Edge AI Hardware Market is segmented into Smartphones, Surveillance Cameras, Robots, Wearables, Edge Servers, Smart Speakers, Automotive, and Smart Mirrors. ​​​​The smartphone segment received the highest revenue share in the edge AI hardware market in 2021. The increasing demand for smartphones is expected to contribute to the growth of the edge AI hardware market. Edge AI provides improved imaging and photography skills, power efficiency and security for smartphones.

Outlook function

Based on Application, the Edge AI Hardware Market is segmented into Training and Inference. ​​​​​​The segment received the largest revenue share in the edge AI hardware market in 2021. The development of low-power and high-performance CPUs and the growing need for IoT applications are increasing interest in edge artificial intelligence. Reduced latency resulting from the elimination of cloud data transmission is a key driver driving the edge AI market.

Outlook Vertical

On the basis of Vertical, Edge AI Hardware Market is fragmented into Consumer Electronics, Smart Home, Automotive & Transportation, Government, Healthcare, Industrial, Aerospace & Defense, Construction, and others. The healthcare segment registered a significant revenue share in the edge AI hardware market in 2021. As new initiatives to improve clinical, operational and financial value across the care continuum are implemented, the importance of edge computing and analytics will increase .

Outlook Component

By Component, Edge AI Hardware Market is segmented into Processor, Memory, and Sensors and others. The memory segment saw a significant revenue share in the AI ​​edge hardware market in 2021. In addition to new and existing memory growth, including flash storage technologies, several other technological advances are allowing AI/ML jobs on the edge.

Regional Perspective

From a regional perspective, the Edge AI Hardware Market is analyzed across North America, Europe, Asia Pacific, and LAMEA. ​​​​The Asia Pacific segment received the highest revenue share in the AI ​​edge hardware market in 2021. China is the largest artificial intelligence market in the Asia Pacific region, followed by Japan; this makes a promising market for edge AI hardware applications in the region. The presence of a high number of manufacturing firms in China and Japan, along with the strong presence of the automobile, electronics, and semiconductor industries, drive the growth of the AI ​​edge hardware market in Asia-Pacific.

The main strategies followed by market participants are Product Launches. Based on the Analysis presented in the Cardinal Matrix; Apple, Inc. are and Microsoft Corporation are the forerunners in the Edge AI Hardware Market. Companies such as Samsung Electronics Co., Ltd., Intel Corporation and Huawei Technologies Co., Ltd are some of the key innovators in the Edge AI Hardware Market.

The market research report covers analysis of key market stakeholders. Key companies profiled in the report include Apple, Inc., MediaTek, Inc., Qualcomm, Inc., Huawei Technologies Co., Ltd., Samsung Electronics Co., Ltd. (Samsung Group), Intel Corporation, Nvidia Corporation, IBM Corporation, Google LLC, and Microsoft Corporation.

Scope of the Study

Market Segments Covered in the Report:

By Function

• Conclusion

• Training

By Device Type

• Smart phones

• Surveillance Cameras

• Consumables

• Robots

• Smart Speakers & Smart Mirrors

• Automotive

• Edge Servers

By Component

• Processor

• Memory

• Sensor & Others

By Vertical

• Consumer Electronics

• Smart Home

• Automotive & Transportation

• Government

• Health care

• Industrial

• Aerospace & Defense

• Construction

• Other people

By Geography

• North America

from USA

from Canada

from Mexico

o The rest of North America

• Europe

o Germany

from UK

o France

from Russia

o Spain

from Italy

o The rest of Europe

• Asia Pacific

o China

o Japan

from India

o South Korea

from Singapore

from Malaysia

o Rest of Asia and the Pacific

• LAMEA

o Brazil

o Argentina

from UAE

o Saudi Arabia

o South Africa

o Nigeria

o The rest of the LAMEA

Profiled Companies

• 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

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Read the full report: https://www.reportlinker.com/p06374119/?utm_source=GNW

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