Data Mining
Analytic Solutions to the Formation of Feature-Analysing Cells of a Three-Layer Feedforward Visual Information Processing Neural Net
Analytic solutions to the information-theoretic evolution equation of the connection strength of a three-layer feedforward neural net for visual information processing are presented. The results are (1) the receptive fields of the feature-analysing cells correspond to the eigenvector of the maximum eigenvalue of the Fredholm integral equation of the first kind derived from the evolution equation of the connection strength; (2) a symmetry-breaking mechanism (parity-violation) has been identified to be responsible for the changes of the morphology of the receptive field; (3) the conditions for the formation of different morphologies are explicitly identified.
How big data and product analytics are impacting the fintech industry
The fintech industry is growing at an accelerated pace, driven by new technological innovations and evolving needs. In many cases, the modern enhancements across many IT sectors have had secondary effects across industries – and particularly on fintech products and services. For example, artificial intelligence (AI) now drives a large number of applications and major predictive market models/systems. Of particular note are big data analytics and product analytics. Both industries get a lot of news coverage, though normally in relation to social media or marketing.
How big data Is being utilized by the fleet management industry
Big data, or the data processed on a large scale by analytical tools, is crossing industries to generate new and improved technological processes. In fleet management, this means benefits to maintenance, driver safety, and overall profits. For a bottom line capable of surviving any economic conditions of the present and near-future, big data-powered tech can help fleet management companies thrive. The integration of these data tools have already proved their worth in the industry, and the future only looks brighter. Here, we'll explore just how big data is being utilized by the fleet management industry to produce better solutions in maintenance, safety, and financial outcomes.
Big data and transportation industry: How is it making our roads better
The global autonomous vehicle market is already valued at an estimated 54 billion, and is projected to increase over the coming years. Self-driving cars are one of the more popularized and futuristic endeavors that people are looking forward to, and it's all made possible in part by big data. However, in addition to autonomous vehicles, big data is transforming the transportation industry in a number of other ways as well. From improving traffic efficiency to crash maps made with predictive analysis, here's what you need to know. City traffic can cause a number of issues for commuters -- in fact, it's estimated that Americans lose $160 billion in productivity each year, simply by sitting in traffic.
5 Key Challenges In Today's Era of Big Data
Digital transformation will create trillions of dollars of value. While estimates vary, the World Economic Forum in 2016 estimated an increase in $100 trillion in global business and social value by 2030. Due to AI, PwC has estimated an increase of $15.7 trillion and McKinsey has estimated an increase of $13 trillion in annual global GDP by 2030. We are currently in the middle of an AI renaissance, driven by big data and breakthroughs in machine learning and deep learning. These breakthroughs offer opportunities and challenges to companies depending on the speed at which they adapt to these changes.