artificial-intelligence

Credit card fraud has become a significant threat to individuals, financial institutions, businesses, and governments, causing substantial annual economic losses through increasingly sophisticated fraudulent activities. This research aims to enhance credit card fraud detection by leveraging machine learning algorithms and ensemble learning techniques to improve detection accuracy and model robust…

Scientific Data, Published online: 25 May 2026; doi:10.1038/s41597-026-07495-7 A High-Resolution Multifocal RGB Pollen Grain Image Dataset for Deep Learning Computer Vision Tasks from Biobío Region, Chile

RAG 시스템 실전 구축 (v38) Real-World RAG Implementation Guide for ML Engineers 1. RAG Fundamentals: The Core Loop Retrieval-Augmented Generation (RAG) is a powerful pattern that combines information retrieval with language generation. The core loop consists of three phases: Retrieval : Find relevant documents from a knowledge base Augmentation : Inject retrieved context into prompts Generation : Genera…

Most developers treat AI agents like traditional software utilities. They run a quick pip install , throw some environment variables into a .env file, spin up a script, and expect magic. But an autonomous, self-improving AI agent is not a static utility. It is a dynamic, stateful entity. It observes its environment, writes its own code, modifies its skills, and accumulates memories. If you instal…

Monday morning, the Roman Catholic Church made its biggest foray yet into the discourse on artificial intelligence and the role it should play in human life as the technology develops. In the first encyclical of his papacy, titled Magnifica humanitas (Latin for “magnificent humanity”), Pope Leo XIV argued that AI is not intrinsically immoral, but […]

I run my own smart home — Home Assistant, voice assistant pipeline, the whole self-hosted thing. The speech-to-text step (Parakeet TDT 0.6B v3 over the Wyoming protocol ) had been running on my i3 1220P intel NUC with an 12gb RTX 3060 eGPU for months. I recently upgraded my home server to a full desktop with an AMD 7900XTX, and since I want to save as much of the VRAM as I can for LLMs, I've been…

Artificial Intelligence is rapidly transforming industries, economies, and societies across the globe. From healthcare and education to finance, agriculture, climate innovation, and digital governance, AI is shaping the future of how people live and work. As Asia continues to emerge as a global hub for technological advancement, the need for young, skilled, and visionary AI […] The post AI for As…

Every new AI session starts cold. You re-explain who you are, what you're building, what constraints you're working under. If you switch models — GPT-4o to Claude to a local Llama — it's a clean slate again. This isn't a model quality problem. It's an architecture gap: there is no portable, user-owned state layer sitting between the user and the model. .klickd is an attempt to build that layer as…

The Cognitive Copernicus proposes a theoretical reorientation of how neurodivergent cognition is understood within institutional and computational environments. The work advances the argument that contemporary computational systems can function as mechanisms of temporal translation, enabling alignment between nonlinear cognitive processing and structurally linear institutional time. Drawing from …

AI-generated code should be treated as third-party code. Same mental model we already use for libraries and dependencies. We don't review every line of lodash, fastapi, or chi. We shouldn't expect to review every line of AI-generated code either. I argued this in my previous post . The natural follow-up question: okay, but what does that actually require? You can't tell people "trust it like you …

LangGraph 워크플로우 템플릿 (v38) Python 개발자를 위한 LangGraph 기반 AI 에이전트 워크플로우 템플릿 LangChain과 LangGraph를 사용한 Python 기반 AI 에이전트 개발을 위한 실전 가이드입니다. 이 템플릿은 실제 개발자들이 겪는 문제를 해결하기 위해 설계되었습니다. 1. LangGraph 아키텍처 개요 LangGraph는 상태 기반 워크플로우 시스템으로, 다음과 같은 핵심 구성 요소로 구성됩니다: 핵심 구성 요소: Nodes : 워크플로우의 단계 Edges : 노드 간의 연결 State : 워크플로우의 상태 관리 Checkpointing : 상태 저장 및 복원 from langgraph.graph import StateGraph , END from typing …

Most creator tools today focus on analytics and suggestions. We wanted to explore something different: What if YouTube post-production could actually be automated? We’ve been building Growati, a system that helps creators generate personalised: titles descriptions thumbnails chapters for YouTube videos. One of the most difficult engineering problems was properly handling video understanding. Inst…

This post originally appeared on tokenjam.dev/blog . Human-in-the-loop (HITL) for AI agents means inserting human approval, review, or intervention into an agent's execution at specific decision points: before high-stakes actions, or when agent confidence is low. Rather than letting an agent act autonomously, HITL creates a checkpoint where a human must explicitly approve, review, or reject an ac…

Cross-posted from carrick.tools . When you read the API documentation for OpenAI, Anthropic, or Google Gemini, the feature called "structured outputs" looks like a solved problem: pass a JSON schema, get back JSON that conforms to it. In production, it is not a contract. It is a well-typed, best-effort suggestion. At Carrick , the code-analysis scanner I work on, our post-LLM pipeline relies on a…

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Traditional search works on keywords. You type "cheap hotel", it looks for documents containing those exact words. Someone asks "affordable accommodation near the beach". Your documents say "budget-friendly lodging by the coast". Zero keyword overlap. Zero results. Search fails. Embeddings fix this. They convert text into vectors of numbers where similar meanings end up geometrically close. "Chea…

npj Science of Learning, Published online: 25 May 2026; doi:10.1038/s41539-026-00429-3 Uncovering subgroup heterogeneity in dyslexia intervention outcomes using explainable machine learning

Most AI résumé tools have the same flaw: they hallucinate. Ask them to tailor your résumé for a job requiring "Rust experience" and they'll happily invent a Rust project you never worked on. It reads great — until the technical interview. I wanted the opposite. So I built Citevault : a local-first résumé tailoring tool where every claim is either grounded in your own evidence, or refused and flag…

Artificial Intelligence is profoundly transforming the way we develop technology, work, and make decisions. However, one of the most significant changes is only beginning to emerge: the rise of “AI-Native” companies — organizations designed from the ground up to operate with a single human founder supported by a coordinated ecosystem of AI systems and a highly automated cloud infrastructure. For …

Every time I start a new conversation with Claude, I re-explain my project context. What we decided, what the architecture looks like, what we tried and rejected. The AI has no memory. I built edgenote-ai to fix this — a lightweight shared knowledge base on Cloudflare Workers that both humans and LLMs can read and write through MCP (Model Context Protocol). The Problem LLMs are stateless. They pr…