#algorithmic decision-making
132 related articles
·3 min
Why Are AI Companies Frantically Hiring Electricians and Carpenters? The Blue-Collar Recruitment Truth Behind the Data Center Building Boom
OpenAI, Google, Meta, and other AI giants are massively recruiting electricians, carpenters, and plumbers. A deep dive into how the AI data center boom is driving a revaluation of blue-collar skills.
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·3 min
Autonomous Combat Tanks: Technical Implementation and Ethical Boundaries of AI Militarization
In-depth analysis of AI autonomous combat tanks: reinforcement learning training, environmental perception, decision engines, global military AI competition, and the ethical dilemmas of lethal autonomous weapons systems.
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·2 min
Can 45 Yes/No Questions Let an LLM Identify 16 Cards? An Information Theory Perspective on AI Reasoning
Analyzing whether LLMs can identify 16 cards through 45 yes/no questions from an information theory perspective. Exploring AI reasoning capabilities in constraint-based multi-turn tasks.
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·3 min
Practical Guide to Agent Development: The Complete Path from Zero to Commercial Deployment
A systematic guide to AI Agent development from beginner to deployment, covering task planning, tool calling, memory management, learning paths, and realistic commercial monetization considerations.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy to Help You Fully Understand
Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.
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·4 min
What Is the True Nature of Large Language Models? A Super Compressor Analogy That Makes Everything Click
LLMs aren't search engines — they're more like super compressors. This article explains how large models compress corpora to learn semantic patterns, and explores the principles and limitations of emergent intelligence.
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·3 min
Record AI Lobbying Spending: How Tech Giants Are Shaping Washington's Policy Agenda
AI industry lobbying in Washington hits record highs as OpenAI, Google, Meta, and other giants spend heavily to shape legislation. A deep analysis of the forces, landscape, and policy implications.
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·3 min
Low Initial Review Scores for NeurIPS 2026 Theory Papers? Community Discussion and In-Depth Analysis
NeurIPS 2026 theory papers are receiving low initial review scores. This article analyzes structural causes, scoring trends, and rebuttal strategies for theory researchers.
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·3 min
Building an Online Game Solo with AI: 877 Users, 12 Daily Actives — What's Still Missing?
One developer used AI (Claude/ChatGPT/Gemini) to build a multiplayer web ARPG in a month for a few hundred dollars. 877 users, 12 daily actives — here's the real story.
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·7 min
The Complete Guide to LLM Application Engineer Interviews: Six High-Frequency Agent Topics
A focused guide to core LLM application engineer interview topics, covering agent architecture, Multi-Agent, Langfuse evaluation, security, and RAG optimization.
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Human-Centered AI: Real-World Implemen…
·6 min
Human-Centered AI: Real-World Implementation in Healthcare and Design
An MSR workshop reveals the truth about AI deployment: from a $20 corneal diagnostic device to expert-in-the-loop chatbots, researchers share real-world experiences of AI in healthcare and design within resource-scarce environments.
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·4 min
Teaching AI to Have "Taste": Exploring Multi-Agent Design with Open-Source Skill Taste
Why does AI-generated UI all look the same? Designer SEN open-sourced a Skill called Taste that uses a four-agent pipeline to reverse-engineer website "taste" into verifiable design principles called Taste DNA.
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·2 min
OpenSpiel 2.0 Released: Reinforcement Learning Framework Fully Embraces Large Language Models
OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.
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·3 min
Interpretability: The Science and Practice of Opening the Neural Network Black Box
Why do neural networks make the decisions they do? This article explores AI interpretability — mechanistic interpretability, CoT monitoring, and safety auditing — and how researchers reverse-engineer large models for AI safety.
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·2 min
When AI Becomes the Third Wheel: The Cult of Productivity and the Boundaries of Human Connection
A Tinder message sparked a Reddit debate: when AI tool windows make people delay dates, what's the real cost of productivity worship? A deep dive into AI-era work culture and social etiquette.
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·2 min
DecisionRL: An Open-Source Reinforcement Learning Library Built for Operational Decision-Making
DecisionRL is an open-source RL library for operational decision-making, with six built-in scenarios (inventory, pricing, energy), OR baselines, and support for DQN, PPO, SAC, and more.
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·3 min
Cracks in the AI Boom: Why Ordinary People Are Being Left Behind
AI-driven growth enriches tech giants while ordinary workers fall behind. We examine wealth concentration, job displacement, and the skills gap in the AI economy.
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·2 min
Carmack and Sutton's First Paper: How Physical Atari Challenges Real-Time Reinforcement Learning
Keen Technologies releases its first paper, bringing classic Atari benchmarks into the physical world via robotic arms and cameras. A deep dive into the paper's core claims, sim-to-real challenges, and Carmack and Sutton's vision for embodied RL and AGI.
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·3 min
UAV Disaster Zone Rescue Priority Assessment: A Deep Feasibility Analysis for Final Year Projects
A deep feasibility analysis of a UAV disaster-zone rescue priority assessment project, covering SARD/HERIDAL/VisDrone datasets, pose detection, YOLO models, and ethical boundaries — a practical reference for CV final-year projects.
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decisionrl: An Open-Source Reinforceme…
·2 min
decisionrl: An Open-Source Reinforcement Learning Library Built for Operational Decision-Making
decisionrl is an open-source RL library for operational decisions, with built-in environments for inventory, pricing, supply chain, and OR baselines for comparison. Built on PyTorch, MIT licensed.
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