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I built an AI content engine that turns one piece of content into posts for 9 platforms — fully automated with n8n

What it does: You give it any input — a blog URL, a YouTube video, raw text, or just a topic — and it generates optimized posts for 9 pla...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

mining hardware doing AI training - is the output actually useful

there's this network that launched recently routing crypto mining hardware toward AI training workloads. miners seem happy with the econo...

Reddit - Artificial Intelligence · 1 min ·
[2604.01989] Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation
Llms

[2604.01989] Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation

Abstract page for arXiv paper 2604.01989: Attention at Rest Stays at Rest: Breaking Visual Inertia for Cognitive Hallucination Mitigation

arXiv - AI · 4 min ·

All Content

[2602.19718] Carbon-Aware Governance Gates: An Architecture for Sustainable GenAI Development
Generative Ai

[2602.19718] Carbon-Aware Governance Gates: An Architecture for Sustainable GenAI Development

The paper proposes Carbon-Aware Governance Gates (CAGG) to integrate sustainability into Generative AI development, addressing the increa...

arXiv - AI · 3 min ·
[2602.19698] Iconographic Classification and Content-Based Recommendation for Digitized Artworks
Machine Learning

[2602.19698] Iconographic Classification and Content-Based Recommendation for Digitized Artworks

This article presents a proof-of-concept system for automating iconographic classification and content-based recommendations for digitize...

arXiv - AI · 3 min ·
[2602.19578] Goal-Oriented Influence-Maximizing Data Acquisition for Learning and Optimization
Machine Learning

[2602.19578] Goal-Oriented Influence-Maximizing Data Acquisition for Learning and Optimization

The paper presents Goal-Oriented Influence-Maximizing Data Acquisition (GOIMDA), a novel algorithm for active data acquisition in machine...

arXiv - Machine Learning · 3 min ·
[2602.19629] Cooperation After the Algorithm: Designing Human-AI Coexistence Beyond the Illusion of Collaboration
Ai Safety

[2602.19629] Cooperation After the Algorithm: Designing Human-AI Coexistence Beyond the Illusion of Collaboration

The paper discusses the design of human-AI coexistence, emphasizing the need for governance frameworks to ensure responsible collaboratio...

arXiv - AI · 4 min ·
[2602.19506] Relational Feature Caching for Accelerating Diffusion Transformers
Machine Learning

[2602.19506] Relational Feature Caching for Accelerating Diffusion Transformers

This paper introduces Relational Feature Caching (RFC) to enhance the efficiency of diffusion transformers by improving feature predictio...

arXiv - Machine Learning · 4 min ·
[2602.19555] Agentic AI as a Cybersecurity Attack Surface: Threats, Exploits, and Defenses in Runtime Supply Chains
Llms

[2602.19555] Agentic AI as a Cybersecurity Attack Surface: Threats, Exploits, and Defenses in Runtime Supply Chains

This article discusses the cybersecurity implications of agentic AI systems, focusing on threats and defenses in runtime supply chains, h...

arXiv - AI · 3 min ·
[2602.19509] Pyramid MoA: A Probabilistic Framework for Cost-Optimized Anytime Inference
Llms

[2602.19509] Pyramid MoA: A Probabilistic Framework for Cost-Optimized Anytime Inference

The article presents Pyramid MoA, a probabilistic framework designed to optimize inference costs in large language models (LLMs) while ma...

arXiv - Machine Learning · 3 min ·
[2602.19491] Botson: An Accessible and Low-Cost Platform for Social Robotics Research
Llms

[2602.19491] Botson: An Accessible and Low-Cost Platform for Social Robotics Research

The paper presents Botson, a low-cost, accessible platform for social robotics research, designed to enhance trust in AI through anthropo...

arXiv - AI · 3 min ·
[2602.19312] Metasurfaces-Integrated Wireless Neural Networks for Lightweight Over-The-Air Edge Inference
Machine Learning

[2602.19312] Metasurfaces-Integrated Wireless Neural Networks for Lightweight Over-The-Air Edge Inference

This article presents Metasurfaces-Integrated Neural Networks (MINNs) as a novel framework for efficient edge inference in 6G wireless ne...

arXiv - Machine Learning · 4 min ·
[2602.19475] Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction
Machine Learning

[2602.19475] Scale-PINN: Learning Efficient Physics-Informed Neural Networks Through Sequential Correction

The paper presents Scale-PINN, a novel approach to enhance Physics-Informed Neural Networks (PINNs) by integrating a Sequential Correctio...

arXiv - Machine Learning · 4 min ·
[2602.19450] Red-Teaming Claude Opus and ChatGPT-based Security Advisors for Trusted Execution Environments
Llms

[2602.19450] Red-Teaming Claude Opus and ChatGPT-based Security Advisors for Trusted Execution Environments

This article presents a red-teaming study of Claude Opus and ChatGPT as security advisors for Trusted Execution Environments (TEEs), high...

arXiv - AI · 4 min ·
[2602.19116] Event-Triggered Gossip for Distributed Learning
Robotics

[2602.19116] Event-Triggered Gossip for Distributed Learning

The paper presents an event-triggered gossip framework for distributed learning, enhancing communication efficiency among nodes while mai...

arXiv - Machine Learning · 3 min ·
[2602.19049] IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning
Llms

[2602.19049] IAPO: Information-Aware Policy Optimization for Token-Efficient Reasoning

The paper presents IAPO, a novel framework for token-efficient reasoning in large language models, enhancing accuracy while reducing infe...

arXiv - Machine Learning · 3 min ·
[2602.18895] Could Large Language Models work as Post-hoc Explainability Tools in Credit Risk Models?
Llms

[2602.18895] Could Large Language Models work as Post-hoc Explainability Tools in Credit Risk Models?

This paper explores the potential of large language models (LLMs) as post-hoc explainability tools in credit risk models, evaluating thei...

arXiv - Machine Learning · 4 min ·
[2602.19315] Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders
Robotics

[2602.19315] Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders

This article presents a novel approach to online navigation planning for underwater gliders, utilizing a stochastic shortest-path Markov ...

arXiv - AI · 4 min ·
[2602.18813] Habilis-$β$: A Fast-Motion and Long-Lasting On-Device Vision-Language-Action Model
Machine Learning

[2602.18813] Habilis-$β$: A Fast-Motion and Long-Lasting On-Device Vision-Language-Action Model

Habilis-$β$ is a new on-device vision-language-action model that excels in fast-motion tasks, demonstrating superior performance in real-...

arXiv - Machine Learning · 4 min ·
[2602.19268] CORVET: A CORDIC-Powered, Resource-Frugal Mixed-Precision Vector Processing Engine for High-Throughput AIoT applications
Ai Infrastructure

[2602.19268] CORVET: A CORDIC-Powered, Resource-Frugal Mixed-Precision Vector Processing Engine for High-Throughput AIoT applications

The article presents CORVET, a resource-efficient vector processing engine utilizing CORDIC for high-throughput AIoT applications, achiev...

arXiv - AI · 4 min ·
[2602.18762] Bounds and Identification of Joint Probabilities of Potential Outcomes and Observed Variables under Monotonicity Assumptions
Machine Learning

[2602.18762] Bounds and Identification of Joint Probabilities of Potential Outcomes and Observed Variables under Monotonicity Assumptions

This paper explores the bounding and identification of joint probabilities of potential outcomes and observed variables under monotonicit...

arXiv - Machine Learning · 3 min ·
[2602.18718] Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space
Machine Learning

[2602.18718] Stochastic Gradient Variational Inference with Price's Gradient Estimator from Bures-Wasserstein to Parameter Space

This paper presents advancements in Stochastic Gradient Variational Inference (SGVI) using Price's Gradient Estimator, demonstrating comp...

arXiv - Machine Learning · 4 min ·
[2602.19166] CosyAccent: Duration-Controllable Accent Normalization Using Source-Synthesis Training Data
Machine Learning

[2602.19166] CosyAccent: Duration-Controllable Accent Normalization Using Source-Synthesis Training Data

The paper presents CosyAccent, a novel approach to accent normalization that utilizes source-synthesis training data, enhancing naturalne...

arXiv - AI · 3 min ·
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