| viXra.org > Economics and Finance > 2511 |
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| viXra.org > Economics and Finance > 2511 |
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[2] viXra:2511.0128 [pdf] submitted on 2025-11-26 01:04:51
Authors: Samuel Forbes
Comments: 12 Pages. (Note by viXra Admin: Please submit article written with AI assistance to ai.viXra.org)
This paper examines smooth, progressive income tax functions as an alternative to the current piecewise UK tax function. The piecewise function applies constant rates within income brackets leading to a discontinuous first derivative or marginal tax rate which can create incentives for individuals to limit their earnings. Building on Odland’s work on the Norwegian income tax function, we derive and analyse a general class of smooth tax functions that maintain progressivity while ensuring continuity in marginal rates. We find that the function Odland proposed as a replacement for the Norwegian piecewise tax function also provides a good fit for the UK piecewise tax function. Despite theoretical advantages of a smooth tax function, the implementation of such a system in the UK and elsewhere is likely to be constrained for several reasons including administrative complexity and political considerations.
Category: Economics and Finance
[1] viXra:2511.0127 [pdf] submitted on 2025-11-24 22:45:34
Authors: Satyadhar Joshi
Comments: 15 Pages. (Note by viXra Admin: Please submit article written with AI assistance to ai.viXra.org)
This paper presents a comprehensive review of Artificial General Intelligence (AGI) and Agentic AI, examining their definitions, evolution, technological foundations, current capabilities, and future trajectories. We analyze AGI’s theoretical underpinnings, contrasting it with narrow AI and artificial superintelligence (ASI), and highlight three critical dimensions of AGI development: (1) technical architectures bridging narrow AI to general intelligence, (2) transformative applications across sectors such as finance, business, and research, and (3) emerging ethical and workforce challenges. Agentic AI is also explored in depth, with a focus on its architectural requirements, computational demands, and learning mechanisms.We review specialized frameworks like OpenAI’s AGI classification and Agentic AI platforms such as Vectara-agentic and CrewAI, along with enabling infrastructure including NVIDIA’s AI hardware and large-scale cloud systems like OpenAI’s proposed "Stargate." Our comparative analysis reveals that Agentic AI is already being deployed in areas such as legal services, DevOps, and enterprise automation, whereas AGI remains in the research stage with ongoing debates about feasibility and timelines.Market data shows accelerating AGI growth (36.9% CAGR through 2031) and strong adoption in financial services (38% of AI investments projected by 2028). Despite this momentum, significant gaps persist in areas such as evaluation metrics, environmental impact, and governance. We propose a framework for responsible AGI development that balances innovation with ethical standards, emphasizing standardized benchmarks and workforce transition strategies.This is a pure review paper; all findings are derived from cited literature. It contributes to ongoing discourse by synthesizing fragmented research into actionable insights for practitioners and policymakers navigating the AGI and Agentic AI landscape.
Category: Economics and Finance
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