How Edge AI is addressing the key challenges of Cloud Computing

How Edge AI is addressing the key challenges  of Cloud Computing

Over the past few years, the internet has been through a massive transformation and cloud computing has taken leaps and bounds to meet the customer demand while offering the most optimal advancement in technology to run applications, programs and operations. Most of the applications and devices today run on cloud or have cloud enabled features that makes the processes, operations easy and convenient.

According to Statistica, the global cloud computing market size is estimated to reach 482 billion U.S. dollars in 2022. While the manner in which data is processed at the cloud has evolved over the years to achieve greater efficiency, increased storage, and faster processing, there are challenges that have been constantly brought up by the end users, companies and organizations that rethink the adoption of cloud. 

What is Cloud Computing?

Cloud computing is a generic term used for anything that involves delivering hosted services over the internet. It enables users to access their data, information and applications across different devices from anywhere in the world. This revolutionizes the world of computing and powers developers, companies & manufacturers to build more inclusive, personalized and easily accessible applications for their end-users.

A cloud can be private or public. Public cloud caters to anyone on the internet. A private cloud is a proprietary network or a data center that supplies hosted services to a limited number of people, with certain access and permissions settings. 

What is Edge Computing?

Edge Computing is a fairly new concept of computing where the processing of data is done at the network’s edge. Edge computing reduces the need for large amounts of data to travel among servers, the cloud and devices or edge locations to get processed. This is particularly important for modern applications such as data science and AI. ​​It carries storage and computational power nearer to the computer where it is really essential for the information sources. 

So, in a nutshell, Edge Computing & Edge AI enables abilities in devices to run data processing and data analytics locally on the device using data that they create so that they can make decisions in the form of output without the need to take the data to the cloud each time.

Benefits of Cloud Computing

Some of the prominent benefits of cloud computing include:

  • Lower upfront cost – Cloud computing eliminates the expenses involved in buying hardware, software, IT management and maintenance costs. Cloud computing allows companies and organizations to get applications to market quickly, with a low financial barrier to entry.
  • Flexible pricing – In many cases, the pricing of a cloud infrastructure is structured in such a way that the organizations or companies only pay for the resources used, allowing for more control over costs.
  • Limitless compute on demand – Cloud services can react and adapt to changing demands instantly by automatically provisioning and deprovisioning resources.
  • Simplified IT management – Cloud providers provide their customers with access to IT management experts, allowing businesses to focus on their goals rather than IT management.
  • Easy updates – The latest hardware, software and services can be accessed with one click and upgrades are easily possible considering the security, performance and organizational needs.
  • Reliability – Data backup, disaster recovery and business continuity are easier and less expensive.
  • Save time – Companies & organizations can easily deploy applications in a fraction of the time and get to market sooner.

Challenges of Cloud Computing

While cloud computing brings a lot of power in data processing, it also introduces some concernable challenges, namely:

  • Data Security & Privacy – User or organizational data stored in the cloud is critical and private. Since the cloud storage is public and even if the cloud service provider assures data integrity, there is always risk involved with user authentication and authorization, identity management, data encryption, and access control.
  • Cost Management – Although most of the cloud providers have ‘pay as you go’ models, there will unused and unoptimized resources that will incur huge costs on the users or companies.
  • Performance Trade-Off – In many cases where the models are not optimized or the data keeps exponentially growing, the cloud performance deteriorates and considerable amount of performance lay-offs can be evidently seen.
  • High Dependence On Network – Cloud computing is completely dependent on the availability of network/internet to function. This makes the whole system or applications crippled if there is no connection.

Many businesses, users and developers are realising these challenges to be hurdles in day-to-day functioning of technologies that can hamper the user experiences. This gave birth to Edge Computing and Edge AI as a solution to challenges possessed by the Cloud Computing.

Benefits of Edge AI over Cloud Computing

  • Speed – Speed is an quintessential part of any user experience and companies and manufacturers today understand this and are in the race for delivering this. With Edge AI, the data can be processed locally in the device to avoid latency involved in sending the data to the cloud and bringing the output after it is processed.
  • Security – With the data stored locally, manufacturers and companies can save sensitive and important data locally instead of taking it to the public cloud where it is more vulnerable thereby decreasing the security risks involved.
  • Increased Performance – Edge AI overcomes the challenge where devices and applications had to transmit large volumes of data in real-time in a cost-effective manner by bringing the power right to the devices.
  • Reduced Operational Costs  – By eliminating the need for the data to be processed at the cloud every time and increasing the computational requirements, Edge AI enables devices to connect or communicate with cloud only when it is absolutely necessary.
  • Scalability – With Edge AI, companies and developers can easily deploy to scale new features, bandwidth and support the growth as required. This provides an upper hand over cloud which still has challenges to upscale as and when needed.
  • Reliability – Since there is less risk of a network issue in a faraway place impacting local customers. Even in the case of a data center failure, Edge AI will permit critical processing capabilities without hampering the experience.
  • Versatility – Edge AI is extremely flexible and provides an uninterrupted experience across different functions. The ability to use Edge AI to operate under different scenarios like Computer Vision, Video Analytics, Smart Systems, etc. makes it a viable and versatile solution for many developers and companies.

Cloud computing has been a viable option for many companies to address the challenges faced by IT vendors and organizations. While this has been a powerhouse for almost a decade now, there is also a need for better and more sophisticated system to fill the loopholes and challenges drawn by cloud computing.

But, with more and more companies realising the advantages of Edge AI and how they can solve the challenges cloud computing possess while powering the applications and systems to be more flexible, cost-effective, secure and scalable, it is only imperative that Edge AI will be the frontier of technologies moving ahead.

If you are not already in the race of Edge AI adoption, it’s time to power up. Get started today with ENAP Studio. It is a one-stop Edge AI Solution that can help you train, optimize & deploy AI Models on all major Edge Hardware.

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