Brain-Inspired Computing — Good or Bad?
All of us remain indebted to John von Neumann for providing the best computing model in the history of computers. The legacy of computer technology of his time is still in use among computers with some variations.
Though this model has been revolutionary in promoting the cause of faster computation in various operations, it is not above downsides. For instance, some tasks lead to performance lag due to the transmission of a massive chunk of data. The actual difficulty lies in channeling it back and forth for performing various tasks.
As a result, the demand for an efficient computing model has been on the rise for decades. Cognitive computers have come to the fore as the best choice to fill the vacuum. Consequently, researchers have started investing their time and effort in determining the scope of this approach. Experts have named it as “brain-inspired computing”.
But What is Brain-inspired Computing? Is it Bane or Boon to People in General?
These questions can start clouding the minds of anyone who thinks about the evolution of new technology, especially the one that relates to the brain. Everything has both positive and negative sides. The case with the cognitive computing model is not an exception to this rule.
In this post, we will expound the topic and find out if it is beneficial for humanity.
What is Brain Inspired Computing?
Brain is central and complex organ of human body. No matter how far one gets to know about it, it does not cease to amaze a learner or researcher.
Comprised of about a billion nerves, it controls a host of body functions on its own. Impressed with the efficiency of the model, researchers of computer science have been striving hard to include it in the architecture of modern computers.
Thus, in layman language, brain-inspired computing can be defined as a cognitive computing concept that revolves around the principle of the processing of information as done by the human brain.
While we are still far away from cracking the code of the computation of the brain, researchers have devised how computers can process information by managing the memory efficiently. For this, they have studied the biological model of the brain and emulated its framework with artificial intelligence (AI).
AI has been in use with the algorithms of conventional computing systems for a long time. Graphical processing units (GPUs) and central processing units (CPUs) make use of it. But due to the element of physical separation, a large chunk of data needs to be moved to and fro. This slows down the computers in terms of performance by creating a bottleneck.
On the other hand, the aspects of processing and memory are connected to one another in the case of the brain. This highly entwined model may look complicated from the outset but it leads to performance efficiency.
Regardless of the fact that we’re on the threshold of taking a baby step in this direction, it has already been surrounded by a pertinent question.
Will it prove to be bane or boon to people in the future? The sure-fire way to answer this question is to examine some characteristic features linked to brain-inspired computing.
Brain Inspired computing: Yay or Nay?
This has been a hot topic for discussion over the last few years. Given the fact that cognitive computing is just at its initial stages, it will be hard to tell anything about its future now. Just as von Neuman’s model has two sides of the story, this model also has its own set of pros and cons. The use of artificial intelligence will play a decisive role in it.
AI is generally associated with improved operational speed. As things stand at present, machines powered by it need human effort in some way or the other for the execution of tasks. But what if it could run machines without manual effort altogether?
The overwhelming capabilities of AI have thrown open the debate on the efficiency of AI in decision making. Experts are split up into two different schools of thought. While some opine that it would be a monumental achievement in the technological evolution of computers, others believe it can open a Pandora’s Box of problems.
Speaking of the positives, by and large, it addresses the problem in the Von-Neumann model of computers that is currently in use. The development of AI hardware as per the suggested model will help reduce the differences in the distance of the components. Also, it will minimize the length of time needed in the processing of information by the efficient management of memory.
In terms of downsides, the model is likely to bring uncertainty with regard to the stability of performance. After carrying out some extensive performance evaluation, most researchers believe it may not provide desirable results or meet the expectations while performing certain tasks.
Another drawback to the theory is that it is likely to bring to the table the element of uncertainty. As a result, it will pose difficulty in determining the effectiveness of the model for a variety of other purposes.
Brain-inspired computing is set to change the landscape of computing technology in a variety of ways. Like the evolution of technology in other areas, the one linked to this one will also lead to a new area of opportunities.
For instance, it will reduce the bottlenecks involved in the movement of data. The elimination of physical barriers of the various computing systems will facilitate the transmission of data at a greater speed. Alongside it, the new model will also lend a helping hand in the efficient management of memory sharing and processing.
Though there are some concerns, the cognitive model is set to bring in some new features that will help alleviate the majority of them. So, after taking all the aspects into consideration, the pros of cognitive computing outweigh its cons.