#LLM fact-checking
63 related articles
·4 min
A Conversation with Dr. Rubin: How Professionals Fight Viral Medical Misinformation
Misinformation spreads for free; correcting it is costly. We speak with Dr. Zachary Rubin about why professionals must step up, and how AI is reshaping the battle for truth in science communication.
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·7 min
Complete Guide to Claude Code Desktop: Access DeepSeek Domestic Models Without an Account
Step-by-step guide to installing Claude Code Desktop, enabling developer mode for account-free use, integrating DeepSeek via CC Switch, Chinese localization, and custom Skills in ten minutes.
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·6 min
How AI Rumors 'Killed' Jim Carrey: A Trust Crisis in the Age of Search
Jim Carrey was 'declared dead' by AI rumors, revealing how AI-generated content and SEO content farms systematically pollute the information ecosystem.
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·5 min
Introduction to Prompt Engineering: A Complete Guide to Core Concepts, Methodologies, and Limitations
Prompt engineering is a core skill in the AI era. This article breaks down the essential differences between prompts and prompt engineering, the six-step workflow, four evaluation criteria, and key limitations like context limits and hallucination.
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·7 min
Andrew Ng Teams Up with LangChain: Core Principles of LangGraph Agent Development
Andrew Ng and LangChain CEO Harrison Chase present AI Agents in LangGraph, covering five core agent design patterns and LangGraph's graph-based framework for building cyclical agentic workflows.
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·7 min
Andrew Ng Teams Up with LangChain: Core Concepts of LangGraph Agent Development
Andrew Ng and LangChain CEO Harrison Chase's AI Agents in LangGraph course covers five agent design patterns and LangGraph's graph-based framework for building cyclical AI workflows.
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·6 min
Gas Town: A Multi-Agent Workspace Manager Built in Go
Gas Town is an open-source multi-agent workspace manager built in Go with 16,000+ GitHub Stars. This article analyzes its architecture, Go language advantages, and typical multi-agent collaboration scenarios.
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Google Co-Scientist Explained: A Gemin…
·2 min
Google Co-Scientist Explained: A Gemini-Powered Multi-Agent AI Research System
Deep dive into Google's Co-Scientist: a Gemini-powered multi-agent AI system that autonomously generates hypotheses, conducts agent debates, and iteratively evolves research directions.
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·2 min
Sakana AI × Sumitomo Mitsui: Multi-AI Agent Collaboration Auto-Generates Proposals, Boosting Efficiency 100x
Sakana AI and SMBC developed a multi-AI Agent proposal auto-generation app, reducing creation time from 1-2 weeks to hours. Deep dive into the multi-Agent architecture and its implications for financial AI.
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·2 min
Struggling to Deploy AI Agents? Engineering Is the Key to Going from Demo to Product
57% of projects have deployed AI Agents, but 40% will be killed. This article analyzes the engineering methodology for taking AI Agents from Demo to enterprise product, covering the full process from requirements to deployment.
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·4 min
Learning Path for AI Agent Development: A Complete Guide from Core Architecture to Production Deployment
A complete learning path for AI Agent development covering core architecture, ReAct paradigm, multi-agent collaboration, RAG integration, and lightweight deployment to guide developers from basics to production.
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·3 min
AI Large Language Model Learning Path: A Three-Step Practical Guide from Zero to Freelancing
A three-step guide to LLM app development: from Prompt Engineering and API calls, to RAG knowledge bases, to Agent development and multi-agent collaboration.
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·3 min
Claude Code Ultra Code in Practice: One Person Orchestrating 100+ Agents in Parallel Development
Learn how to use Claude Code's Ultra Code and Dynamic Workflow to orchestrate 100+ Agents in parallel, with Deep Research demos, token-saving tips, and workflow reuse methods.
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·4 min
AI Large Language Model Learning Roadmap: A Complete Guide from Zero to Project Implementation
A systematic AI LLM learning roadmap covering prompt engineering, RAG, AI Agent development, and fine-tuning — with beginner-friendly paths and practical tips.
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·4 min
The Age of Information Fragmentation: How to Identify Low-Quality Content and Link Rot
Exploring content identification challenges in the fragmented information age, analyzing low-density content, link rot, and their impact on AI processing, with practical multi-source verification strategies.
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Industry Insights·3 min
Deep Dive into Three Major LLM Career Paths: Requirements, Tech Stacks, and Career Prospects
Deep analysis of three core LLM roles—Application Engineer, Development Engineer, and Algorithm Engineer—covering technical requirements, salary thresholds, and career prospects including RAG, fine-tuning, and inference deployment.
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Deep Dives·2 min
AI-Pilled: When AI Wins You Over Completely, What New Doors Open Up?
What does AI-pilled mean? When AI wins you over, productivity soars, cognitive frameworks shift, and ability boundaries expand. Explore the traits of AI believers and how to embrace AI's paradigm shift.
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Product Reviews·2 min
TRAE + Seed-2.0 Hands-On Review: Three Real-World Challenges for This Free Chinese AI Coding Assistant
Hands-on testing of ByteDance's TRAE with Seed-2.0: three real-world challenges covering game dev, subtitle proofreading, and financial chart analysis validate its engineering-grade AI coding capabilities—completely free.
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Tutorials·2 min
Introduction to Prompt Engineering: The Real Reason AI Can't Understand You
Why does AI always give irrelevant answers? This article explains prompt engineering fundamentals from the probabilistic prediction principles of LLMs, teaching you how to communicate effectively with AI.
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Tech Frontiers·4 min
IBM Think 2025 Deep Dive: Rising Hallucination Rates in Reasoning Models and OpenAI's Acquisition of Windsurf
Deep dive into IBM Think 2025's Generative Computing and Granite 4, why reasoning model hallucination rates are rising, and OpenAI's $3B Windsurf acquisition strategy.
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