To describe what edge AI and edge devices are, it can help to first understand what artificial intelligence (AI) is. AI is the term applied to any tool that simulates and automates complex human intelligence processes. You’ll hear many different terms associated with artificial intelligence – machine learning, deep learning models, neural networks – but essentially, they all are different ways to describe a machine or computer system that’s been taught how to identify and decode patterns.
Some of today’s most common applications of artificial intelligence focus on identifying patterns in text, sound, numbers, or images. However, they can also be used to help us better understand human behavior. In the case of video conferencing, this could mean that an algorithm has been taught how to understand which person is speaking in a meeting and to zoom in on that person, rather than the participants doing it manually.
What is edge AI?
In most cases, AI tools like the ones described above are run on cloud-based systems. In other words, data is collected by a device (i.e., a laptop, mobile phone, or meeting room video camera), sent to a cloud server for processing, and is then delivered back to the hardware device.
However, by enabling processing on the device itself, edge AI removes the need to send and receive data to and from the cloud, essentially limiting reliance on cloud services and cloud computing. With in-built processing capabilities, edge AI-enabled devices can radically streamline the various functions enabled by artificial intelligence algorithms.
According to Fortune Business Insights, the global edge AI market is expected to grow to USD 107.47 billion by 2029. This will be driven largely by its increasing application in a wide range of consumer products and industry solutions, from self-driving cars and virtual assistants to wearable devices and traffic lights.
Benefits of edge AI in video collaboration hardware
For businesses and IT teams grappling with the massive increase in video meetings and the strain it puts on cloud capacity, bandwidth, and security, edge AI can offer major benefits. Let’s take a look at some of these benefits.
Increased Scalability: Edge AI can be used to offload some of the processing required for video collaboration from the cloud to the edge of the network, reducing the need for costly cloud resources. With built-in compute power, edge devices help to increase scalability and make video collaboration more accessible to organizations with limited resources and cloud capabilities.
Enhanced Security: Edge AI provides enhanced security for video collaboration. For example, it can be used to detect and block potential cyber threats, such as malware or unauthorized access to the video collaboration system. Similarly, because data is anonymized before it ever leaves the device, video devices enabled by edge AI minimize the number of transfer points at which potentially sensitive personal data could be intercepted by malicious actors. This allows users to benefit from advanced video analytics functions without the fear of what is happening with their data.