As we approach the physical limits of further miniaturisation of computing devices and transmission speeds of data, there has been a rise in alternative means of processing. As conventional computing is linear in nature, many of the problems the world faces today are challenging to solve due to the sheer data size and complexities involved. For example, scenarios such as complex encryption or simulations of complex systems or searching large data sets test the limits of classical computing. Some of these limitations start to impact the digital experience of customers and response times — this is where quantum computing comes in.
Rather than taking a linear approach, quantum computing solves problems by carrying out multiple calculations simultaneously, thus increasing the processing power exponentially. Quantum algorithms cause the multiplier effect more than quantum computers themselves, lowering the order of complexity of several common algorithms significantly, thereby making them super-efficient.
However, in addition to this increased processing power, companies must also ensure that insights through computing are available in a timely and readily accessible manner. So, in addition to processing data faster, there is also the need to handle the challenge of transmitting large volumes of data over computer networks. Edge computing comes to the rescue here by enabling data analysis closer to source. This reduces the requirement of network bandwidth and accelerates the delivery of computation and insights.
Quantum Computing and Its Applications
Leveraging its tremendous processing power, quantum computing helps to solve modern business problems. Today, drug companies can run hundreds of millions of comparisons and simulations involving complex interactions between large molecules using quantum computing. It is also useful for any problem which requires optimisation. It does so by parallelly analysing many scenarios and finding the most suitable one which meets the users’ requirements. Various problems such as portfolio optimization, transportation route optimisation, etc. can be solved by using this approach.
However, due to its fair share of problems such as need for large number of error-correcting quantum bits (qubits) or extreme operating conditions, it is still a challenge to obtain the most optimum solutions using quantum computing. Hence most of the solutions emanating are of a hybrid kind, i.e. a mix of classical Machine Learning (ML) and quantum computing.
This approach leads to better results in business issues such as logistics, requiring quick scale-up or wherever there is a lack of data availability. These types of problems are difficult to solve solely using classical computers, and, hence, they are invaluable as the starting point for quantum computers — both, as a way of exploring various methods of computing as well as interesting alternative answers.
Faster computing through Edge devices
Companies all over the world are responding to the change in the data usage paradigm. Over the next few years, as Internet of Things (IoT) applications boom along with the demand for data-driven insights, there will be two consequences. One, use cases which require a response within say 15 milliseconds to give an output for a seamless customer experience. Two, the generation of huge amounts of data which can be processed closer to the source.
While industries at the forefront of technical innovation have adopted this new computational technology, traditional businesses too are now starting to do the same for supporting various data analytics in their offices, stores and manufacturing plants. Several telecom companies are exploring if they can have edge computing infrastructure in the towers that they currently own so that the latency may be substantially reduced, allowing edge algorithms on telco networks.
For example, high-value retail companies that have central data locations but want to improve their surveillance. However, recording hours of video across the store network and transmitting it to a central / cloud location would involve huge costs in terms of bandwidth as well as latency. Similarly, loan approval decisions can be made in principle in milliseconds based on algorithms running inside the end user devices such as smartphones, and, therefore, making the experience one of delight for the customer.
In The Future
While quantum computing is in its infancy, edge computing is already here and is helping corporations step up their analytics. However, as these technologies ramp up and become more commonplace, use cases will expand into the realm of possibility. Along with vast amounts of content-heavy data such as video and voice which are better served without transmission to cloud/data centre, they will represent the next frontier of technology making a difference in our everyday experiences.