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Ankur Saxena on Muck Rack

Ankur Saxena

United States
As seen in: Medium, Nature, Oracle Magazine, Taylor & Francis Online, Stem Cell Reports, Canadian Journal of Infectious Diseases & Medical Microbiology, Data Center Knowledge, International Railway Journal Magazine, WriteUp Cafe, Bobsguide and

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Articles

What Is Satta Matka? History & Basic Structure Explained

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By Ankur Saxena
| WriteUp Cafe
Satta Matka is a number-based system that originated in India and later evolved into multiple market formats. Over time, it became known for its structured result system involving open, close, jodi, patti and panel numbers. This guide explains the concept in a simple and educational manner. Origin and History of Satta Matka The origins of Satta Matka trace back several decades when early number-based systems replaced commodity-linked practices.
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Design and analysis of a cantilever-based MEMS switch with dielectric thin film material coatings for enhanced electrostatic actuation

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By Ankur Saxena, Raghvendra Singh, G. Ezhilarasan, Mahesh Kumar, Shubham Verma Verified, Shantharam Patil, Chandrmani Yadav, Pratikkumar S. Shata
| Nature Verified
Abstract The selection of an appropriate dielectric material for a microelectromechanical systems (MEMS)-based radio-frequency cantilever switch is essential for achieving reliable operation, improved actuation performance, rapid response, and stable thermal behavior. In this work, a rectangular cantilever structure is designed at a micro scale. It optimized the influence of dielectric materials on response time, operating capacitance between the beam and electrodes, and thermal performance.
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The Token Factory: Why AI's Next Winners Will Master Inference Economics

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By Ankur Saxena
| Investors Hangout
AI Is Leaving the Lab. It Is Entering the Factory. AI is no longer a research project. It is becoming a production infrastructure. Enterprise AI budgets have grown from approximately $1.2M per year in 2024 to more than $7M by mid-2026. Spending is rapidly shifting from training models to inference, the continuous execution of AI models in production. Some Fortune 500 companies are already spending tens of millions of dollars every month on inference.
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