Edge Computing Trends in 2021

Aditya Chakurkar | July 29, 2021 | 480 views

edge computing trends
With significant numbers of cloud vendors implementing edge servers in local markets, market analysts predict an incredible growth in edge computing. Furthermore, the rise in the hottest edge computing trends will be supported by the complimentary 5G network offerings.

The current demand for edge-driven business models is so intense that even the COVID-19 pandemic failed to alter these predictions. A study from IDC’s worldwide IT predictions claims that the impact of this global pandemic will be one of the biggest reasons behind the growth of around 80% of edge computing investments and platform changes across various industries in the coming years.

But firstly, what exactly is this edge computing, and how does it matter to technology trends?

The term ‘edge’ in this points at literal geographic distribution. In layman's terms, edge computing is a kind of computing performed at or near the data source. However, unlike cloud computing, it does not rely on cloud data sources to do all the work.

This doesn't mean that the cloud will disappear with edge computing; instead, it will come to you.

Edge computing, in most cases, uses a variety of functions that need service provisioning closer to users. The most common examples of such functions are telco network functions, machine learning, robotics, AR/VR, and IoT. Using such emerging use cases, edge computing assists in resolving critical challenges in data sovereignty, resiliency, latency, and bandwidth.

Furthermore, migration of data resources, applications, and infra results in:
  • Faster responses to business needs
  • Improved business scaling
  • Long-term resilience
  • Improved flexibility

Businesses rely on edge computing to define new cloud-based services and products that can exploit security, storage, and processing capabilities at the edge of the network.

There will be a need for more distributed compute and data processing power post the COVID-19 pandemic because of new working ways. Moreover, edge devices will be in demand for their ability to fulfill this need without debilitating latency.

Top Edge Computing Trends in 2021

Considering the increasing maturation of edge computing capabilities, market analysts predict the rise in investment in edge computing. As edge computing solutions come up as ever more essential to business operations, here are the top edge computing trends you will want to keep an eye on.

Artificial Intelligence & Machine Learning will Shift to Edge Computing

Although no edge computing strategy can completely substitute the applications of cloud resources, many businesses are trying to put more ML and AI capabilities closer to endpoint devices. In this way, they can achieve the required speed and reliability of such smart processes.

Companies that need to bridge the digital and physical world in real-time will be the primary reason for this new trend in computing. Plus, edge computing has the power to replace machine learning models that are often trained at the data center. Instead, with specialized hardware, learning can occur at the edge.

Considering the general nature of edge technologies, it will improve real-time predictions and, ultimately, operational reliability. Moreover, edge computing and data security are closely associated. Therefore, with more advancements in edge computing strategies, data security will steadily grow.

Pandemic will Push Organizations to the Edge

The current global pandemic has made us realize the actual effectiveness of several modern technologies, and it has changed the way we integrate and deploy them. In addition, the growth in the usage of consumer mobile devices, the increased consumption of virtual content, videos, and the increased demand for IoT devices (Internet of Things) has made the critical edge computing trends continue to flourish.

Here’s what Jason Mann, the vice president of IoT at SAS, has to say, “From social distancing to thermal imaging, safety device assurance and operational changes such as daily cleaning and sanitation activities, computer vision is an essential technology to accelerate solutions that turn raw IoT data (from video/cameras) into actionable insights.”

For example, retailers and shop owners can use edge computing solutions to know when people violate the store’s policies.

Edge will Enhance the Connected Ecosystem Adoption

Apart from enhancing IoT device usage, edge computing will ease the participation of organizations in the connected ecosystem. And, most importantly, there will be relatively lesser bandwidth and network latency issues.

Organizations can quickly expand to several other profitable businesses without incurring hefty infrastructure costs by leveraging the scalability of edge computing. In addition, moving to more fast-streaming and profitable markets will be easy for enterprises because of easy data processing.

IT and Operational Technology will Unite

The COVID-19 pandemic has revealed several weaknesses of most organizations, and ‘resiliency’ is perhaps one of the most common weaknesses of most companies. IoT-driven devices and other connected equipment power the adoption of edge computing solutions where applications and infrastructure are within the facilities. According to the IDC report, the real-time inference with the help of digital twins and AI models can make this approach critical as they can detect the changes in operating conditions and eventually automate the remediation.

With more convergence of IT and operational technology, the IDC report says that the number of operations deployed on edge computing infrastructure will grow from 20% to more than 90% in 2024. As a result, enterprises will prioritize integrating intelligence into different workflows and processes using edge computing capabilities.

In 2021, mobile edge computing MEC) trends are expected to enable supply chain resilience. With data analytics at the edge, the ecosystem of supply chain enablers can integrate AI and ML to access near, live insights into data consumptions. Furthermore, it will also allow businesses to look into even the most unprocessed elements of highly composite demand and supply chains. Therefore, organizations need something that can enable 24/7 view across the complete supply chain. MEC-based solutions answer this as they can offer end-to-end monitoring from the point of service or manufacture. 

Private 5G Adoption will Increase

As serious applications will begin to materialize, many businesses will take themselves to the edge. Undoubtedly, there's great potential in a private 5G network for fueling the edge computing trends in 2021 and beyond. The private 5G network is dedicated to specific infrastructures like factories and warehouses.

Factory robots and machine tools require low-latency networks and local data processing. Edge computing and 5G can satisfy this need. The general nature of edge technologies and speed, low latency, enhanced coverage, and incredible responsiveness of the 5G network can serve these benefits.

Edge will Improve Data Security

Edge computing reduces data and internet costs and eventually improves data efficiency compared to the cloud. Plus, the edge offers an additional layer of security and enhances the overall user experience.

Unlike the cloud, edge computing does not depend on a single point of storage or application. Instead, it distributes different processes across a variety of devices.

Edge Computing in 2021 and Beyond

The current and future edge computing trends will enable innovation across several industries such as medical, agricultural, worker safety, insurance, industry 4.0, retail, telecommunications, and more.

As more and more companies collaborate to develop an open ecosystem and ultimately make it quick and easy for consumers to integrate as a part of their cloud strategies, edge computing trends will offer more value to organizations in the coming years.

To summarize, edge computing trends will continue to redefine business operations by offering enhanced data security and controls, better connectivity even when disconnected from the network, and quick insights and actions.

If you have any questions related to your upcoming project, we can help! You can go through our success stories here.

Frequently Asked Questions

How new is edge computing?

The origin of edge computing traces back to the 90s, and it lies in content delivery networks. The primary job of these networks was to serve video and web content from edge servers that are deployed within the facility.

What is edge computing used for?

Edge computing is used for a wide variety of applications, services, and products. For example,
  • Medical monitoring devices for real-time responses
  • Self-driving cars for real-time reactions
  • Video conferencing for decreasing lag and latency
  • More efficient caching


Is edge computing the future?

Several researchers estimate that the edge computing trends are proliferating at around 30% of the compound annual growth rate. The edge computing industry is expected to reach more than $7 billion in the next five years. Many businesses have already begun to prepare for the technology change that will take place because of the current and future edge computing trends.

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Aetina Launches New ASIC-Based Edge AI System Powered by Blaize

Aetina | December 08, 2022

Aetina, an edge AI solution provider that offers embedded computing hardware and software for AI and IoT, has launched a new ASIC-based edge AI system powered by the programmable Blaize® Pathfinder P1600 Embedded System on Module (SoM). The Aetina AI inference system—AIE-CP1A-A1—is a small-sized embedded computer designed for different computer vision applications, including object detection, human motion detection, and automated inspection. The AIE-CP1A-A1 model features the small form factor Blaize® Pathfinder P1600 Embedded SoM, ideal for rugged and challenging environments and embedded systems that need extended temperature ranges. It features Dual ARM Cortex A53 processors, 16 GSP cores providing 16 TOPS AI performance, and the benefits of low memory bandwidth and low latency, making it capable of accelerating neural network (NN) deployment and deep learning (DL) process. Based on the Blaize Graph Streaming Processor (GSP®) architecture, the Pathfinder enables energy-efficient processing power ideal for AI inferencing workloads at the edge, easily plugs into a custom carrier board, and runs autonomously or integrated within a larger system. Due to its compact, fanless design and multiple I/O ports, the AIE-CP1A-A1 can fit both commercial and industrial-grade AI-powered systems that involve vision AI-related inference. The Blaize Pathfinder also supports H.264/H.265 video encoder and decoder, making it compatible with different sensors to run quick image recognition and video analytics tasks. Aetina offers customized carrier boards and computer cases for sophisticated system integration and chip-down design service to provide other kinds of embedded computing models, such as single-board computer (SBC) with the Blaize Pathfinder in addition to regular box PCs. Moreover, Aetina helps developers convert their AI inference models to a format that can run and function normally on edge devices built with ASIC chips. “We are now expanding our edge computing product line to bring more GPU and ASIC-based solutions to help developers build their AI systems in various verticals and industries. “The AIE-CP1A-A1 model, powered by Blaize Pathfinder P1600 SoM, is our first ASIC-based system. In the future, by integrating different types of chips and modules, we can offer heterogeneous computing devices that are suitable for different AI models.” Jackal Chen, Senior Product Manager at Aetina Keeping AI processing and inferencing workloads at the edge, rather than sending data to the cloud, is critical for cost-effective and almost latency-free AI applications," said Dinakar Munagala, CEO and Co-founder of Blaize. "The Pathfinder SoM and our GSP architecture enable this key business objective for the demands of computer vision applications, including object detection, autonomous optical inspection, robotics, and more." Additionally, Aetina is now developing more ASIC-based AI accelerators with M.2 and EDSFF specification for developers, speeding up the inference processes of their AI models at the edge. About Blaize Blaize is a leading provider of a proprietary purpose-built, full-stack hardware architecture and low-code/no-code software platform that enables edge AI processing solutions at the network’s edge for computing in multiple large and rapidly-growing markets — automotive, mobility, retail, security, industrial automation, medical devices, and many others. Blaize’s novel solution solves the technical problem that edge AI processing requires across those verticals — very low latency and high thermal and power efficiency — which previously relied on retrofitting sub-optimized AI solutions designed more for data centers and the cloud. Blaize has previously raised over $180MM from strategic investors such as DENSO, Daimler, Magna, and Samsung, and financial investors such as Franklin Templeton, Temasek, GGV, and others. With headquarters in El Dorado Hills (CA), Blaize has teams in San Jose (CA) and subsidiaries in Hyderabad (India), Manila (Philippines), and Leeds and Kings Langley (UK), with 300+ employees worldwide. About Aetina Aetina Corporation, founded in 2012 in Taipei, Taiwan, is a leading provider of state-of-the-art AI solutions involving high-performance edge computing hardware and low-code/no-code software to help developers build different AI verticals quickly. With a focus on the global AI market, Aetina is committed in delivering professional longevity services to solve the developers’ pain points and speed up their AI adoption processes.

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GENERAL AI, AI APPLICATIONS, SOFTWARE

Silex Technology to provide Wi-Fi 6E Embedded Modules for High-Performance Applications Powered by the NVIDIA Jetson Edge AI Platform

Silex Technology, Inc. | October 28, 2022

Silex Technology, a global leader in wireless technology, has introduced its new Wi-Fi 6E module, the SX-PCEAX series based on the NVIDIA Jetson edge AI platform, along with the latest Linux drivers for the NVIDIA JetPack SDK 5.0.x release supporting Linux kernel 5.10. The latest Wi-Fi 6E standard expands Wi-Fi into the 6 GHz spectrum for unprecedented Wi-Fi communications performance, stability, and efficiency. Designed for improved communications in highly congested environments, the new Wi-Fi 6E module delivers the critical reliability, efficiency, and performance needed to expand IoT devices in factories, warehouses, and medical facilities. Silex Technology has created the SX-PCEAX-M2, a tri-band IEEE 802.11 abgn/ac/ax WLAN module plus Bluetooth combo module based on Qualcomm's QCA2066 SoC, specifically for the NVIDIA® Jetson Orin™ platform. The M.2 card form factor inserts directly into the developer kit for a plug-and-play experience using evaluation software from Silex. No engineering development is required to get started with a wireless evaluation on the Jetson Orin platform. "Silex is proud to be a preferred Wi-Fi solutions provider in the NVIDIA Partner Network. "Our radio hardware modules are ready to go into mass production and are ideal for original equipment manufacturers who seek to reduce RF design costs and improve time to market." Keith Sugawara, President of Silex Technology America An essential requirement for AI is access to a large amount of high-quality data for it to learn from, and Wi-Fi will become increasingly crucial for AI-powered applications to access data wirelessly. Silex delivers outstanding wireless technology engineered to help developers and customers leverage the NVIDIA Jetson edge AI and robotics platform to transfer data at high speeds via reliable, secure, and robust Wi-Fi. The SX-PCEAX is not only ideal for evaluation with the Jetson family of developer kits and modules but is also ready for equipment manufacturers to take to mass production. Modules have obtained certifications for North America, Europe, and Japan, enabling quick time to market and cost saving for customers. Silex can help customers port the driver to their specific platforms. Its reference platform for driver evaluation and development is the NVIDIA Jetson AGX Orin™ developer kit. To further expedite the product development process, Silex also provides additional engineering services, including custom driver development, certification services, and hardware schematic design reviews. Since SX-PCEAX offers a standard M.2 form factor, it can be used to add Wi-Fi connectivity to any Jetson platform (including the Jetson Orin series) with an M.2 card slot.. Silex is currently working with e-con Systems and VVDN in the NVIDIA partner ecosystem to provide Wi-Fi connectivity for NVIDIA customers. Backed by 40+ years of OEM integration experience, Silex can help bring reliable and secure wireless connectivity to AI at the edge applications. About Silex Technology, Inc. Silex Technology builds on more than 40 years of hardware and software connectivity know-how and IP, custom design development experience, and in-house manufacturing capabilities, bringing value to customers with a foundation of technical expertise. With relentless attention to quality and strategic partnerships with leading semiconductor providers, Silex Technology is the global leader in reliable Wi-Fi connectivity for products ranging from medical devices to document imaging products to a video or digital displays. With Silex Technology, customers get a single vendor that provides hardware and software support from design through manufacturing for a successful product after a successful product.

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AI TECH, GENERAL AI

Deloitte Acquires SFL Scientific's Business to Enhance Cutting Edge AI and Science-based Capabilities

Deloitte | October 03, 2022

Deloitte announced today that it has acquired the business of SFL Scientific, a leading, award-winning artificial intelligence (AI) strategy and data science consulting firm. This acquisition underscores Deloitte's commitment to investing in the capabilities that public and private sector clients need to transform their businesses for future success. Combining SFL Scientific's deep science and analytics knowledge with Deloitte's breadth of AI capabilities and industry depth and experience further positions Deloitte as an AI leader, advances its ability to deliver AI-fueled transformations for clients, and accelerates the growth of its AI market share. "As our clients advance their enterprise AI journeys, they require the comprehensive and sophisticated experience that SFL Scientific delivers. "The acquisition builds on an already strong relationship between our two organizations serving both commercial and public sector clients. Additionally, it will help us advise clients with the best approach to how AI can help transform their business, implement scalable capabilities to drive that transformation, and provide ongoing support to continually improve investments with AI-infused tech." Dan Helfrich, chairman and CEO, Deloitte Consulting LLP SFL Scientific has a proven track record serving large, market-leading organizations in the private and public sectors, successfully delivering high-quality, novel and complex projects, and offering deep domain and scientific capabilities. SFL Scientific's team of experienced AI strategists, data scientists, and AI engineers serve as trusted advisors to executives, helping them understand and evaluate new and essential areas for AI investment and identify unique opportunities to transform their businesses. "Combining SFL Scientific's specialized AI strategy knowledge with Deloitte's breadth of AI technological capabilities and industry depth will advance our AI leadership, accelerate our AI market share, and position Deloitte as a trusted advisor helping our enterprise clients transform their businesses through the power of AI," said Nitin Mittal, AI co-leader, and principal, Deloitte Consulting LLP. Acquiring SFL Scientific's business reinforces Deloitte as the destination for a rich career in AI, and fortifies our commitment to fostering an environment to advance technical excellence and technology development and growing leading teams of data scientists, strategists, and technologists, all in support of delivering AI-fueled transformations for clients. "We are excited to join forces with Deloitte. Combining our high caliber AI talent with Deloitte's broad domain knowledge and implementation capabilities is the catalyst to accelerate solving scientific and operational challenges with AI," said Michael Segala, Ph.D., CEO, SFL Scientific. About Deloitte Deloitte provides industry-leading audit, consulting, tax, and advisory services to many of the world's most admired brands, including nearly 90% of the Fortune 500® and more than 7,000 private companies. Our people come together for the greater good and work across the industry sectors that drive and shape today's marketplace — delivering measurable and lasting results that help reinforce public trust in our capital markets, inspire clients to see challenges as opportunities to transform and thrive, and help lead the way toward a stronger economy and a healthier society. Deloitte is proud to be part of the largest global professional services network serving our clients in the markets that are most important to them. Building on more than 175 years of service, our network of member firms spans more than 150 countries and territories.

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