In this podcast, hosted by Data Science Central’s Sean Welch, speaker Carl Flygare from PNY sheds light on how NVIDIA’s recent revolutionary innovation in AI is transforming Data Science along with Big Data Analytics.
Data Science only started becoming more widely used as an independent discipline in the early 2000’s with the launch of the Data Science Journal in 2002. The GPU was just invented a few years prior in 1999, and we as a society were nowhere near where we are now in terms of technology and computation. With the continuous development and innovation of smartphones, social media and other devices that connect us to the internet, more data is being created than ever before. Just to put this in perspective, according to The Next Tech, the 3.7 billion of us who access the internet are collectively creating 2.5 not billion, not trillion, but 2.5 quintillion bytes of data every day. Incredibly, 90% of the world's data has been created in the last two years.
From speeding up drug discovery, improving health outcomes in Healthcare, detecting fraud via Online banking apps and more, Data Science and Big Data analytics have become everyday business tools to analyze, identify, and apply actionable insights. Using CPUs, the process of dataset collection and data prep is invariably a time-consuming task however GPUs enable revolutionary degrees of productivity. With functionality only available on NVIDIA’s GPU-accelerated hardware and advanced AI software development, Data Scientists and other AI/ML/DL/MV professionals can automate their data analysis and execute GPU accelerated end-to-end data science and analytics pipelines. These tools will save you days, weeks, months or more off your development efforts, and ultimately help you create a better tomorrow, today. Learn more on which products from NVIDIA are transforming Data Science and Big Data analytics for the better in this podcast.
