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Fintech Asia News Feed

Discover more about the world of artificial intelligence, machine learning, and blockchain through our carefully curated news feed.

28Jul 25
Ai-nutrition-labels-–-a-food-inspired-approach-to-trust-–-i-by-imd

AI Nutrition Labels – A Food-Inspired Approach To Trust – I by IMD

Artificial Intelligence To build trust, companies should be as transparent with their algorithms as they are with their ingredients. How well do your employees or customers understand the AI systems your company is building? If you’re like most business leaders, the honest answer is not well enough. And that’s a growing problem. As AI becomes
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28Jul 25
New-ai-automation-platform-learns-like-a-human–infofla’s-selto-v2-now-available

New AI Automation Platform Learns Like a Human–Infofla’s Selto V2 Now Available

Infofla, a fast-growing AI startup specializing in workflow automation, has launched Version 2 of its flagship product ‘Selto’, delivering major upgrades that dramatically improve precision, flexibility, and user control. Also Read: AiThority Interview with Dr. Petar Tsankov, CEO and Co-Founder at LatticeFlow AI Powered by Infofla’s proprietary ‘VLAgent’ engine—an AI system that combines large language models
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28Jul 25
Meta-names-chatgpt-co-creator-as-chief-scientist-of-superintelligence-lab

Meta names ChatGPT co-creator as chief scientist of Superintelligence Lab

Reuters Published On Jul 28, 2025 at 06:31 AM IST Shengjia Zhao By Echo Wang NEW YORK: Meta Platforms has appointed Shengjia Zhao, co-creator of ChatGPT, as chief scientist of its Superintelligence Lab, CEO Mark Zuckerberg said on Friday, as the company accelerates its push into advanced AI. "In this role, Shengjia will set the
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28Jul 25
These-ai-models-might-help-spot-space-solar-panel-damage-–-orbital-today

These AI Models Might Help Spot Space Solar Panel Damage – Orbital Today

Researchers in Egypt have developed artificial intelligence (AI) models to detect damage on solar panels used in space. The study analysed images of solar arrays affected by arcing, a phenomenon where electrical discharges occur when high-voltage solar panels interact with plasma in space. According to the authors, “Arcs can lead to severe damage to cell
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28Jul 25
Statistical-mechanics-explains-heavy-tailed-self-regularization-in-neural-networks

Statistical Mechanics Explains Heavy-Tailed Self-Regularization In Neural Networks

The enduring mystery of why deep neural networks learn so effectively has taken a step closer to resolution with a new theoretical framework, unveiled by Charles H. Martin of Calculation Consulting and Christopher Hinrichs of Onyx Point Systems, and colleagues. Their work introduces a Semi-Empirical Theory of Learning, or SETOL, which provides a formal explanation
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27Jul 25
From-big-brother-to-brave-new-algorithm:-the-rise-of-sovereign-ai-and-the-new-age-of-censorship

From Big Brother to Brave New Algorithm: The Rise of Sovereign AI and the New Age of Censorship

Contrary to Orwellian dystopia, the world is heading towards a brave new algorithmic order; rather than through brute force and surveillance, rebellions are crushed, narratives are re-encoded through digital history distortion, and pacification is achieved with enlightened algorithms, all while offering comfort, deceiving the user into a state of euphoria while stripping away their liberties.
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27Jul 25
Postoperative-outcome-analysis-of-chronic-rhinosinusitis-using-transfer-learning-with-pre-…

Postoperative outcome analysis of chronic rhinosinusitis using transfer learning with pre …

Research Open access Published: 27 July 2025 Wentao Gong1,2  na1, Keguang Chen3  na1, Xiao Chen2, Xueli Liu2, Zhen Li2, Li Wang2, Yuxuan Shi2, Quan Liu2, Xicai Sun2,4, Xinsheng Huang3, Xu Luo5 & … Hongmeng Yu1,2,4  BioMedical Engineering OnLine volume 24, Article number: 95 (2025) Cite this article Abstract Background This study developed a foundation model-based analytical framework for
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27Jul 25
Genseg:-generative-ai-transforms-medical-image-segmentation-in-ultra-low-data-regimes

GenSeg: Generative AI Transforms Medical Image Segmentation in Ultra Low-Data Regimes

Medical image segmentation is at the heart of modern healthcare AI, enabling crucial tasks such as disease detection, progression monitoring, and personalized treatment planning. In disciplines like dermatology, radiology, and cardiology, the need for precise segmentation—assigning a class to every pixel in a medical image—is acute. Yet, the main obstacle remains: the scarcity of large, expertly
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