Google’s PageRank Algorithm Surpassed by ResNet Paper

Google has been a household name for years, and its search engine is one of the most popular in the world. But did you know that the algorithm powering it all was published back in 1998? The original PageRank paper, as it’s known, has been cited 17,139 times to date. However, this number pales in comparison to the latest paper from 2016 - ResNet - which has been cited 146,746 times. This staggering difference is causing some people to scratch their heads and wonder what could possibly be behind such an enormous discrepancy. Could it be that ResNet is just a much more useful tool than PageRank? Or could there be something else at play here? The answer may lie in how these two algorithms are used. While PageRank was designed specifically for search engines like Google’s own, ResNet is used for a variety of applications including image recognition and natural language processing. This means that while PageRank might have had a limited scope when it was first released, ResNet can be applied to almost any situation where machine learning is needed. This versatility makes ResNet much more attractive to researchers and developers who need powerful tools for their projects. As such, it’s no surprise that the paper has seen such success since its release four years ago. It also explains why so many people are citing it; after all, if you need an algorithm that can do something specific then why not use one of the best out there? Of course, this doesn’t mean that PageRank should be discounted entirely either; its influence on modern search engines cannot be overstated and its importance should not be forgotten either. After all, without it we wouldn’t have Google as we know it today! It may seem strange at first glance but upon closer inspection the success of ResNet compared to PageRank makes perfect sense. With its versatile applications and powerful capabilities, it's no wonder why so many people are turning to this algorithm over others - even those with impressive track records like Google's own PageRank paper!