Factors driving AI on EDGE leading to a paradigm shift
Digital transformation is something most of the industries are looking for today. The pandemic has further accelerated companies to explore and adopt new technologies. Be it Retail, Manufacturing, Healthcare or Finance industry, technology is being used to improve processes and customer experience. While industries are looking to leverage AI capabilities in their fields, there are some challenges they are facing.
Most of the AI models are cloud native. AI models on cloud need constant connection with cloud for interpreting data which may not be possible always due to network issues. There may be other problems like bandwidth, latency and security which might cause issues in realizing the potential of AI. Especially in the case of applications requiring real-time data processing like self-driving cars, IoT, surveillance there is no scope for any delays. The way to overcome these challenges is by bringing AI to the Edge.
Edge AI is essentially bringing the data processing near to the source. It eliminates the need to communicate with the cloud each time. Edge AI has certain benefits like no latency and bandwidth issues, data privacy as it stays close to the source and lowering the data transfer cost as communication is not required each time. This does not eliminate the need of cloud but reduces complete dependency on it.
Now, all this is being driven by this new tech paradigm that we describe as the intelligent cloud and the intelligent edge. The capacity at the edge, that ubiquity is going to be transformative in how we think about computation in any business process of ours.” — Satya Nadella CEO, Microsoft
Edge AI market has been growing continuously and is expected to increase further. With increasing usage of intelligent devices, Edge AI provides great potential for leveraging AI across various use cases.
According to MarketsandMarkets report, the global edge AI software market size is estimated to grow from $590 million in 2020 to $1835 million by 2026 at a Compound Annual growth of 20.8% during the estimated period.
North America is expected to hold the largest market size in the global edge AI software market whereas APAC region is expected to grow at the highest CAGR during the forecast period. The overall edge hardware market is also expected to reach 1559.3 million units by 2024.
The usage of Edge AI has been on rise across various industries owing to various reasons. Few of the trends driving AI to the edge are:
A. Data Privacy
As said by Tim Berners-Lee, inventor of the world wide web
“Data is a precious thing and will last longer than the systems themselves.”
Importance of data in today’s world is not lost on anyone. With increasing collection and usage of data, every individual, company and nation has become more careful about it. Industries want to prevent any misuse of data and keep it secure. As the data is tremendously increasing, more measures are being taken for secure storage and processing.
Edge AI provides a potential solution for this problem by processing data near to the source. Industries can thus avoid transferring critical or private data to the cloud. Edge AI provides a great opportunity to keep data private. In use cases where industries are hesitant to transfer data to the cloud like in healthcare, facial recognition; Edge AI provides a promising solution.
B. Real time processing
Real time inferencing is critical for some of the AI use cases like self driving cars, industrial IoT and surveillance. The decisions and actions need to happen in real time in these cases and they cannot afford latency. AI at the edge has provided a great opportunity to process data in real time at the source. This will pave a way for many new use cases to shape a better future.
Many industries have found ways to utilize the latest technologies for improving their businesses. Toyota Industries Corporation and Siemens have cooperated on digital transformation for die casting utilizing AI application in Industrial Edge. Dominos and Ford motor company developed a delivery system to deliver pizzas using autonomous vehicles.
In this digital world, it is going to be essential for industries to utilize technology in proper ways to meet the customer’s expectations and survive in a rapidly changing world.
C. 5G
Transition from 4G to 5G will facilitate AI adoption. With more devices being connected to the internet, more will be the data generated which might increase the strain on the network infrastructure. Using edge can be helpful in reducing the amount of data being transferred by processing data locally at the source and only transferring the necessary information to the cloud. One of the interesting examples is that of Verizon teaming up with NFL(National Football League), AWS(Amazon Web Services) to showcase 5G edge. They enabled a mobile game for those in the stadium providing a great augmented reality experience with low latency.
5G and Edge AI provides a great opportunity to explore various use cases that can be beneficial for all.
D. Effects of Pandemic
Pandemic crisis has caused disruption in every industry. Industries had to put new practices in place, adapt to changing situations in various parts of the world, work remotely and many such challenges. New requirements like maintaining social distance, facial recognition with masks, thermal screening came into picture for the industries. Technology has proven to be useful for such use cases requiring minimal user inputs and providing better results. With Edge AI, industries can get real time data to take required action without the need to communicate with the cloud each time. Industries are looking for ways to utilize technology for faster and better results overcoming constraints and circumstances.
E. Better customer experiences
According to ICT research group Omdia’s 2021 IoT Enterprise Survey, more than 90% respondents said IoT was core to digital transformation or was being deployed across multiple areas in their organization
Use of intelligent devices is bound to grow across sectors. Many organizations are trying to leverage IoT for improving performance and operations. Individuals will be connected to the Internet not only through phones, laptops but also with various devices in house and companies. The customer will expect to get faster and better results with all these interconnected devices. It will thus be necessary to provide a great user experience.
One of the examples is Marriott International partnering with Samsung and Legrand to use IoT and edge AI to create the world’s first IoT-enabled hotel room. It will facilitate providing personalized services to its customers.
“The combination of edge computing and AI provides significant opportunities to survive in an increasingly disruptive world,” says Michelle Duerst, Senior Director Analyst, Gartner. “Many executives do not understand how edge computing and AI can raise innovation capabilities, operational excellence and customer engagement.” Edge AI is paving new opportunities to leverage AI in different use cases. It will be exciting to see how industries will make use of Edge AI. Though implementing Edge AI can be challenging, implementation for proper use cases will benefit the companies.
Do let us know what are your thoughts on Edge AI by commenting below or reaching out to us at connect@edgeneural.ai.
Previous article we covered Unleash the power of AI on EDGE and in our next article we will explore some of the Major challenges while implementing Edge AI.
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