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Can a Local LLM Run My AI Assistant?
I replayed the same 27 real production tasks through two local models, one hardware upgrade apart, to find out what it actually takes to replace Claude as the brain behind a 90-tool personal agent. The post Can a Local LLM Run My AI Assistant? appeared first on Towards Data Science.
One Manuscript, Twelve Languages: Documenting an Experiment in AI-Assisted Independent Publishing
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The AI takeover of mathematics has begun
Mathematician James Maynard has spent a lot of time this past year "soul searching." A professor at the University of Oxford and winner of the prestigious Fields Medal, Maynard told The Verge he's been grappling with the future of his field as the traditionally slow-moving discipline hurries to adapt to AI. Days before we spoke, OpenAI revealed it had produced the solutions to 10 long-standing mathematics problems, some of which had confounded academics for decades. Like generative AI used to produce text and images or propose ideas in science and medicine, the technology learns patterns and connections from the vast amount of material it' … Read the full story at The Verge.
Why the Smartest Employees Are Hiding Their AI Scripts From Their Bosses
Are your employees using Shadow AI ?Continue reading on Medium »
Požeminiai vartai — išsamus gidas
Po eminiai vartai kod l vis daugiau investuotoj renkasi i technologij ?Continue reading on Medium »
AI Calling Company in Navi Mumbai -AI Sales, Marketing, Lead Generation & Promotions
Navi Mumbai has become one of Maharashtra s important business and commercial hubs, with growing activity across real estate, education Continue reading on Medium »
Your Organization Is Already Using AI. Does It Have a Governance Policy?
A stat from my last piece kept nagging at me after I published it: 63% of organizations still don t have an AI governance policy in place Continue reading on Medium »
The EU Just Made AI Tell You It's AI. Here's What Actually Changes
For years the running joke online was that you can never tell whether you are talking to a person or a bot.Continue reading on Medium »
Are We Really Using Artificial Intelligence? Understanding Narrow AI and AGI
Artificial Intelligence (AI) has become a part of our everyday lives. We use AI tools almost everywhere sometimes without even realizing Continue reading on Medium »
Flow-by-Flow:Content-Judgment Bypass for Governing AI Output in High-Loss Domains
arXiv:2608.07474v1 Announce Type: new Abstract: Prior work showed that human-in-the-loop oversight becomes structurally untenable in high-loss domains when AI output velocity V exceeds human cognitive capacity C_max. The operative constraint, however, is not V alone but V x L, where L denotes per-item cognitive load. L consists of triage, judgment, and response, which respond asymmetrically to AI capability improvement. Triage cost does not decline as models become more capable, because semantic indeterminacy is inherent in general-purpose design. Response cost is invariant to accuracy improvements. Only judgment cost faces downward pressure, and this pressure often operates by inducing omission rather than genuine reduction. Capability improvement therefore restructures L rather than reducing it. Governance mechanisms based on evaluating whether AI output is correct either delegate that evaluation to AI and inherit hallucination risk, or delegate it to humans and face the V x L ceilin
Application of Artificial Intelligence for Fraudulent Banking Operations Recognition
arXiv:2608.07471v1 Announce Type: new Abstract: This study considers the task of applying artificial intelligence to recognize bank fraud. In recent years, due to the COVID19 pandemic, bank fraud has become even more common due to the massive transition of many operations to online platforms and the creation of many charitable funds that criminals can use to deceive users. The present work focuses on machine learning algorithms as a tool well suited for analyzing and recognizing online banking transactions. The study`s scientific novelty is the development of machine learning models for identifying fraudulent banking transactions and techniques for preprocessing bank data for further comparison and selection of the best results. This paper also details various methods for improving detection accuracy, i.e., handling highly imbalanced datasets, feature transformation, and feature engineering. The proposed model, which is based on an artificial neural network, effectively improves the ac
SC$^{2}$-WM: A Self-Correcting World Model with Closed-Loop Feedback for Vision-and-Language Navigation in Continuous Environments
arXiv:2608.07548v1 Announce Type: new Abstract: Vision-and-Language Navigation in Continuous Environments (VLN-CE) requires agents to make fine-grained navigation decisions under partial observability. However, most existing methods rely on open-loop execution, lacking mechanisms to detect and correct internal state drift during inference. We propose SC$^{2}$-WM, a self-correcting world model framework that introduces internal feedback for closed-loop decision making in VLN-CE. Our method derives feedback from world-model foresight to perform state-level plan refinement before action execution. To handle challenging scenarios, we further introduce conditional world-aware adaptation, which enables model-level correction by selectively updating the world model at test time when feedback indicates model capacity insufficiency. Experiments on standard VLN-CE benchmarks demonstrate improved navigation robustness and generalization. Our code is available at https://github.com/sunrise-ikun/SC