Edge AI chips: New applications, new opportunities
Specialized Edge AI chips are powering the Edge AI revolution
As the demand for intelligent devices and applications grows, Edge AI is emerging as a key technology that promises to bring AI closer to the Edge of the network, where data is generated.
Edge AI relies heavily on specialized chips capable of efficiently processing AI workloads while consuming less power, delivering low latency, and ensuring high accuracy.
These Edge AI chips are designed to be integrated into a wide range of devices, from smartphones and cameras to drones and robots, enabling a host of new use cases.
Recently, we saw the announcement of Perceive's new Ergo2 chip, which claims to be up to four times faster than their first-generation Ergo chip and can handle larger models such as NLP.
This highlights the ongoing innovation and competition in the Edge AI chip market, with many players such as SiMa.ai, Hailo Technologies, AlphaICs, Recogni, and EdgeCortix developing their own solutions.
According to market intelligence firm Global Market Insights, the Edge AI market is projected to top $5 billion in 2023, with a 20% CAGR through the next decade.
This growth is driven by the increasing adoption of Edge AI across various industries, including automotive, healthcare, retail, and manufacturing, as well as the rise of 5G networks (which enable faster, more reliable connectivity for Edge devices).
The sources below closely examine the latest Edge AI chips, their features and benefits, and their applications in various domains, offering insights into how businesses and developers can leverage Edge AI chips to create value.
Chipping away at the future
This article discusses the rapidly growing AI chip market, which is expected to hit a staggering $88.85 billion by 2027.
The article explores various types of chips hitting the market, including GPUs, ASICs, FPGAs, and CPUs, and their applications in Edge AI, natural language processing, robotics, computer vision, and more!
Artificial Intelligence Chip Global Market Report 2023
Game of processors: Consolidation and innovation
According to Manoj Sukumaran, principal analyst at Omdia, demand for specialized AI processors will continue to soar in 2023 as AI deployments surge across all types of enterprises, cloud service providers, and telecom providers.
For example, Nvidia's H100 ‘Hopper’ Tensor Core GPU will be commercially available in 2023, and Intel's GPU, code-named ‘Ponte Vecchio,’ is also expected.
On top of this, consolidation in the AI chip market will occur as startups become acquisition targets.
Revolutionizing Edge AI: Perceive AI's Ergo2 chip
Perceive AI, a company specializing in developing low-power Edge AI chips, has recently announced its highly-anticipated second-generation Ergo2 chip.
This cutting-edge technology promises to deliver a significant performance boost for demanding Edge applications while maintaining impressively low power consumption.
Perceive AI Launches 2nd Edge AI Chip For Low-Power Applications
Some extra resources
4 Trends driving the Edge AI revolution
The following article explores four key Edge AI trends: increasing adoption, improved hardware and software, standardization and interoperability, and a heightened focus on data security.
Monetizing data and enhancing customer engagement
This article explores how businesses can leverage Edge capabilities and integrate AI at the data source to convert data into revenue and improve operational efficiency.
The author argues that the Edge is the front line of customer and operational engagement and a new force for monetization and value creation.
Data Management and AI: Creating Value at the Edge
Edge video analytics powers smart mobility
In light of rapid urbanization and the steadily growing demand for mobility, many nations see public transportation as a sustainable solution to mobility challenges.
According to the article below, Swiss embedded computing provider Elma, Israeli AI chip manufacturer Hailo, and German AI video analytics software vendor Isarsoft have partnered to provide a novel Edge AI video analytics solution.
The new Edge-based video analytics technology finds use in vehicles and train stations, providing operators with accurate, real-time insights from video cameras.
How Edge AI Video Analytics Transforms the Transportation Industry
Xailient’s newest article
Edge computing is a solution that addresses the limitations of the cloud, bringing several benefits to video analytics, including reduced latency, better cost efficiency, and improved security.
To find out more, check out this week’s blog Edge Computing Brings a Diverse Array of Benefits to Video Analytics
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