The industrial and consumer applications of AI are advancing so fast that it is often hard to keep track of everything. AI is one of the fastest developing technologies and has now diversified into many different categories, products, and services. This blog is focused on discussing ‘Edge AI’ or ‘AI on Edge.’ We’ll introduce you to what Edge AI is and share the latest trends and developments in the field.
What is Edge AI?
Edge AI refers to the processing of Machine Learning (ML) algorithms locally or ‘on edge.’ Edge AI is an alternative to cloud processing. It offers more security since the devices process the data at the user’s end. It also reduced any delay, latency, or lag which is usually caused due to establishing a connection with the cloud servers.
One example of Edge AI in action is our smartphones. These days, phones are incredibly powerful machines that come with basic ML processing capabilities and AI enhancements like virtual assistants. To enable AI on computers and mobile devices, the primary hardware components required are microchips. Dedicated microchips can work solely on AI-based functions and provide the benefits of Edge AI to users without disrupting the regular performance of our devices.
Why do we need Edge AI?
Edge AI is being developed as an alternative to cloud computing, but usually, we hear that cloud technology is all the rave. While developments and innovation occur in the cloud industry, here we see an alternative being developed at an equally impressive rate. So does that mean cloud technology will become obsolete?
Not quite, as cloud technology is here to stay. The reason for developing Edge A I has to do with service provision requirements. Cloud computing tends to the macro-level and intermediate-level needs of organizations and end-users.
There are some serious concerns in the cloud computing world. Firstly, data breaches are becoming a frequent problem. Millions of users’ data is susceptible to cyber-attacks within seconds if a single server house is not secure. Secondly, cloud computing operates through server houses that are also prone to physical accidents. Power outages, fires, earthquakes, and other such calamities, either natural or artificial, can cause servers to go down and halt entire services. The results can be devastating as apps and websites experience downtime for hours or even days.
Edge AI offers a complementary solution to cloud AI. It performs services at the micro-level to speed up some individual activities. Even if servers worldwide crash or there is a data breach, users can store their most sensitive information locally and continue processing AI functions locally in a relatively secure environment.
Trends and Developments in Edge AI
Now that we’ve told you what Edge AI is and why businesses are interested in developing it, let’s take a look at the latest advancements in the field.
DeepMind has its sights set on creating Artificial General Intelligence (AGI). There is significant debate around how to properly define AGI. However, DeepMind’s own definition is a good way to understand the concept; AGI is the AI system that can be used for almost anything and “sits on a continuum.”
For Edge AI, this would be quite a breakthrough. DeepMind would allow devices to interact with users more holistically, take commands and use the carefully designed intelligence model to perform their tasks. Developers can train AGI in a certain field or subject to perform all the tasks related to it. This is like the edge AI alternative for Digital twins. However, it is important to note that digital twins heavily rely on streaming information from a cloud-based repository. Whereas, DeepMind would be able to perform all activities on the user’s end.
Kria Chips from Xilinx
One of the most important considerations for developing Edge AI is developing the right hardware. Xilinx has created programmable Kria chips and boards that can host AI applications, and AI programs can run smoothly at the user end. Some mainstream applications that Xilinx’s new chips can host are visualization (business intelligence) software, image processing (for intelligent and enhanced cameras), and language processing. Kria chips are also faster to deploy.
Xilinx has attempted to ease the problems of AI and software developers who are not savvy with hardware. The Kria chips and boards increase hardware accessibility significantly. Xilinx has done this by combining hardware and software platforms with production-ready applications.
The company is committed to advancing Edge A I, as they are offering open-source applications.
Facial Recognition from Microsoft and Amazon
Just like CCTV footage, users might not want to share their data on a cloud or public network. If they require AI-based facial recognition for shops and restaurants, they demand trust with the developers and AI developers. Both Microsoft and Amazon offer facial recognition services that businesses can deploy on edge. Microsoft has developed Azure Face API which users can integrate quickly with their existing security setup. Amazon Rekognition is an industry-favorite facial recognition suite which business can purchase and install themselves. These AI-powered software provide ease of use, convenience and cutting-edge AI capabilities to every business.
Blaize AI Studio
This Edge AI Hardware and Solutions company has quickly evolved with the help of strategic and financial investors. Their equity stands at $87 million, which they are employing to create some of the best AI on Edge applications. Blaize AI services are based on real-world data, rather than training models, which makes the AI more sophisticated and powerful.
Their AI Studio is a revolutionary concept. Blaize has chosen to target non-technical people instead of engineers or data scientists. With the AI Studio non-technical users can design AI programs for their intended use without having to write any code. Blaize’s intelligent assistant and other helpful features enable users to freely experiment with AI.
Edge AI provides a strong complementary option to cloud computing. We have also seen some interesting applications of Edge, that allows the secure processing of information and performing unique artificially intelligent tasks. We will soon see many IoT functionalities integrated with AI due to Edge AI development.
Xavor Corporation can help your organization adopt Edge AI technology and incorporate them into your products. Our aim is to help modern-day organizations achieve digital transformation as efficiently as possible. Xavor has a team of AI experts who have over 2 decades of experience and possess a wide range of skills and AI-tool proficiencies. Contact Xavor now to start deploying AI on edge for your organization.