By Krishna Rangasayee, CEO and Founder, SiMa.ai
Most discussions about technological transformation have been dominated by the cloud.
Transformation, until recently, meant moving to a decentralised platform to process the
large quantities of data the business generated. Computing needs, however, are evolving
beyond the cloud. The next quantum leap in software innovation is towards the world of
edge computing. A study by the Linux Foundation shows that a majority of companies will
be using edge computing by 2028, while Gartner says that over 50% of enterprises will
process their data outside of traditional platforms by 2025. Hyperscalers have already
reported a decline in their cloud business during the first half of 2023. In other words, the
change is here – and it is a fast gathering pace.
Why edge computing matters
Industry 4.0 has been all about automation, connectivity, and robotics. These technologies are exponentially expanding possibilities across sectors – including traditional ones like
manufacturing – and bringing about huge advancements in daily quality of life. The thing that gets talked about less, however, is the massive amount of power that goes into running the processing units behind those technologies. With environmental damage
reaching critical levels, there is an immediate need to shift to sustainable industry practices and the power centres we currently use are not efficient enough to process the kind of data Industry 4.0 calls for. Estimates show that up to 20% of the world’s power could go towards computing by the end of the decade unless more efficient solutions are found, which is where edge computing comes in. In fact, the market for setting up AI and ML to be compatible with edge computing will be worth $76 billion by 2031.
The business case for edge computing
There are four main reasons why companies are investing in edge computing.
● Instantaneous data processing – To succeed in today’s hyper-competitive space, acting on real-time data insights is critical, and cloud-based data processing is no longer fast enough. There is a growing need to bring the compute to the data at the exact point of the latter’s creation, which is what edge computing does. Even a few seconds can make a difference when it comes to the results that AI/ML algorithms give us.
● Cost efficiency – Moving data to cloud hosting centres can be a significant operational cost, and the more data that gets produced, the higher these costs soar. Edge computing eliminates the need for data movement, and it uses much less power and network resources than the cloud does. After the initial setup cost, therefore, it makes for a much more affordable computing option.
● Enhanced security and control – Edge computing marks a return to “on-machine” computing rather than the decentralisation of the cloud. While this might seem surprising to some, companies are increasingly seeing the benefits of retaining full control over their data and setting up their own security systems. As cyber-attacks continue to proliferate, having to move data to the cloud creates points of vulnerability, and edge computing removes that risk.
● Unlocking the potential of remote devices – Edge computing enables devices and computers to process data at the “edge” of the network. The load on the network is thus reduced, and as a consequence, edge computing can work even in remote locations where connectivity may not be that good. Businesses can thus access timely insights from their devices regardless of where they physically are, enabling more informed decision-making.
The manufacturing sector, in particular, can benefit immensely from edge computing.
The modernisation of the sector has been long overdue, and while AI and robotics are key to
the solution, edge computing provides the foundation for it all to happen. With edge computing, manufacturers can set up smart factories where they receive data insights on the factory floor rather than having to wait for an external facility to get back to them.
As a result, AI and ML can be deployed securely and promptly to supplement human labor and decision-making. In car manufacturing, for instance, robots can be trained to spot and respond to issues in real-time rather than awaiting commands. This, naturally, will speed up manufacturing timelines and ensure accuracy at every step, and thus enable manufacturers to meet growing customer demands.
Technology is progressing faster than ever. The volume of data being generated is already exceeding the capacity of current business networks, and edge computing will become a necessity sooner than anyone can imagine. Companies of all sizes would do well to invest in edge computing facilities now and start enjoying the benefits of faster processing times, lower costs, and greater data security and autonomy. It’s an exciting time to be in the industry, and the next few years will likely change the face of how things work – for the better of all.