Holistic generational offsets: Fostering a primitive online abstraction for human vs. machine cognition

TL;DR

This paper introduces a unified, scalable architecture for next-generation mobile internet that shifts computing from data centers to end-user devices, enabling accessible, programmable applications across diverse platforms.

Contribution

It presents a novel architecture that extends current web infrastructure, integrating JVM-based applications for scalable, low-cost, and accessible mobile internet computing.

Findings

Proposes a scalable architecture for mobile internet.

Demonstrates application deployment on diverse platforms.

Highlights the potential for accessible, programmable mobile applications.

Abstract

We propose a unified architecture for next generation cognitive, low cost, mobile internet. The end user platform is able to scale as per the application and network requirements. It takes computing out of the data center and into end user platform. Internet enables open standards, accessible computing and applications programmability on a commodity platform. The architecture is a super-set to present day infrastructure web computing. The Java virtual machine (JVM) derives from the stack architecture. Applications can be developed and deployed on a multitude of host platforms. O(1) <-> O(N). Computing and the internet today are more accessible and available to the larger community. Machine learning has made extensive advances with the availability of modern computing. It is used widely in NLP, Computer Vision, Deep learning and AI. A prototype device for mobile could contain N compute and N MB of memory.