Lady Luck is a western expression of the Roman goddess of luck, Fortuna. Fortuna’s decisions on whether to provide good or bad luck have been debated for centuries. Some of the best innovations we have today have been a result of an error, exaptation, and serendipity. However, when we think about the future, it is a visioning game of what could happen, not necessarily knowing what will happen.
The x-ray, which was invented by a physics professor at 50 years old, was the result of an error. He was working on the cathode-ray-tube and noticed when he held a thick paper in front of it that there was light was produced by the material near the tube which ultimately led to the discovery of the x-ray. Today it is common to use x-rays to look at broken bones, detect pneumonia and detect cancer.
Scientific breakthroughs have also happened from a result of exaptation. An example is a current work at a company called GroundProbe. GroundProbe is a technology radar equipment that is very precise over a short distance. At first, the founders thought that this technology would be used to find underground pipes and power cables. But, when they tested it with consumers, there was not much demand. After additional market testing, they discovered it had more valuable use to monitor the stability of rock walls in mines to preempt dangerous emergency evacuations.
At the Imperial Festival in April 2018, the Department of Electrical and Electronic Engineering student, Sharlyn Doshi seeks to explain better the optimum psychological and environmental conditions for serendipitous discovery. Her study of the Human-Computer Interaction is one of many studies happening across the world that examines serendipity and approaches in the field of computer science. Her research interest is not surprising given that many other scientific discoveries have also been made by luck including the microwave oven, penicillin, Velcro, and even chocolate chip cookies!
While good fortune has a role in scientific discovery, Doshi’s research work and others will continue to link the steps leading to Lady Luck. Error, exaptation, and serendipity seem to favor the prepared mind. While the story of the apple falling on physicist Isaac’s Newton’s head is a myth, there is some evidence that the falling of the apples from the tree may have contributed to him thinking about gravity. However, the reality is that there are several likely factors involved in helping us see the world in a new way from favorable timing, having the right tools and creative thinking. Lady Luck may favor those that dance near curiosity and opportunity. In the meantime, don’t lean too hard on luck for your next technological breakthrough or it may evaporate.
Today over 2 million people across the globe are using R programming to analyze large data sets with ease. After decades of using SAS, Matlab, and ACL, this programmer recently converted to using R for data analysis, mainly because when running a small business, it is essential to find ways to save money, especially in Information Technology. One of the most compelling things about R is that it is free and has a library of scientific algorithms to support big data analysis and visualization. The Spectrum Survey by IEEE described the R programming language the “king of statistical computing languages for analyzing and visualizing big data.” With R being an open source language with code that can be used on all platforms including Windows, Mac, and Linux, it helps level the playing field regarding access to big data analytic tools.
The R Suite is available online and can be downloaded rather quickly. R has standard data management tools built-in for accessing a variety of data from performing basic summaries and joins, but also more complicated statistical analyses like Tree models and ANOVA. Also, there is an active community of R users online and free videos to help the new professional quickly get up to speed. When the Excel spreadsheet does not work anymore because there are over 2 million rows of data to be analyzed, R can provide a timely solution.
According to a recent Gartner report, artificial intelligence (AI) is estimated to create 2.3 million jobs by 2020. The job search site Indeed found that employers demand for AI skills has more than doubled over the past three years. Companies are searching for candidates that know how to use big data analytics tools like R to support their business and artificial intelligence growth goals. While artificial intelligence has undoubtedly taken away jobs, some of the jobs that are added back into the economy include the need for those with R programming skills. The average pay for data scientists with R skills is $115,531 per year.
R programming is a vital tool for many big data scientists in some of America’s largest companies. For example, Twitter’s Data Science toolbox uses R to help define their customer service interactions. Facebook uses R to analyze status and profile pictures to identify key relationships. Microsoft and Nordstrom, and many others are using the R language to identify data patterns and develop targeted solutions to fundamental business problems. Google uses R to determine the effectiveness of its advertisements. And, The New York Times and The Economist have used the visualization tools found in R in their publications. Also, a recent study found that 80% of Airbnb data scientists use R, and 64% of them use it as their primary analysis tool.
While programming has changed over the years, the fundamentals have stayed the same. A problem is defined, a solution is identified, a program is selected to use, a debugging process happens, and there is development and testing of the program. Big data programming is an essential piece of evolving technologies like voice-recognition and artificial intelligence. R is a widely used tool in the big data industry with free access across the globe that supports everything from big data analytics to artificial intelligence modeling. To get started in downloading R, click here: https://www.r-project.org/
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