Recently, Google boasted possession of the world’s first stable quantum computer. This feat, operating at more than 100-million times the speed of the standard digital computer, opens up doors to a new wave in computational gymnastics. To many optimists, this advancement speaks to the ongoing endeavor to finally tame the problems of artificial intelligence and Big Data analysis. While some imagine this might give rise to the need for new and innovative additions to the kafka tutorial, others are skeptical as to how far this new leap in technology will inevitably take us into these realms of data processing. Making significant headway in artificial intelligence and Big Data is a tall order no matter who is making the claims. This has many asking what is realistic and what is wishful thinking when it comes to how quantum computing is affecting these areas of technology.
Quantum Computing and Artificial Intelligence
While it is desirable to have an artificial intelligence engine that runs as fast as q-bits allow inside a quantum computer, more speed will not necessarily lead to increased competence with artificial intelligence. For starters, while automation and optimization are certainly interesting aspects of primitive artificial intelligent systems, solving problems in neither category introduces evidence that computers are engaged in any sort of legitimate machine learning. Learning in an artificial intelligence sense is more a measure of a machine’s ability to adapt its own approach to solving a problem, not simply follow an algorithmic path faster than a last generation computer. For this reason, quantum computers may offer up little in the area of improvements in artificial intelligence despite all the hype surrounding Google’s new quantum computer giving rise to some type of artificial intelligence arms race. On the other hand, research points to the positive aspects of quantum effects potentially improving areas of machine learning. One way this is believed to occur is by providing the speed and ability to carry out different steps of a problem simultaneously.
Quantum Computing and Big Data
When it comes to manipulating extremely large sets of data, such as Big Data sets, a quantum computer might just be the technology for which data analysts have been waiting. The problem with such large datasets is that typical digital computing methods and processors lack the speed to utilize the information of such large sets of data in real time. With a computer that can run 100-million times faster than the average digital computer, sifting through such datasets becomes a far easier task being carried out in a far shorter amount of time by comparison. The sheer raw power and speed of a quantum computer makes it a far better candidate for the commercial realm, and will undoubtedly help data analysts obtain closer to real-time solutions to Big Data problems. Now that Google has made quantum computing possible, it hopes to be able to soon bring quantum computers to the commercial market. This would inevitably provide businesses and private individuals the raw processing power they need to obtain more use from Big Data repositories.
The New Method
Interest in the use of quantum computing methods has caused researchers to find a new way to approach the problem with Big Data. While a problem involving a massive number of data points may not be practical to wrestle with using conventional digital computing methods, even a small quantum computer employing analytical methods from algebraic topology have proven to be both practical and efficient ways of looking for logical holes and studying internal systemic connectivity of the Big Data set being analyzed.
Conclusion
Quantum computers provide researchers with more speed and raw computational power than they ever had with conventional computers. By augmenting the ability of a quantum computer with an approach like algebraic topology, both Big Data analysis and aspects of machine learning inside the realm of artificial intelligence can enter the next phase of scientific advancement. While sheer processing power and speed may not solve all the issues surrounding these two areas of interest, quantum computing, nevertheless, provides researchers with the means to probe deeper into the subject than ever before.