Coin Puzzle: 0 or 1/13? Why AI Picks the Wrong One
3 coins, P(heads)=1/3, tails always even: is the answer 0 or 1/13? Full math and why this puzzle breaks every AI.
3 coins, P(heads)=1/3, tails always even: is the answer 0 or 1/13? Full math and why this puzzle breaks every AI.
AI agents work in demos. They break in production. Six failure modes nobody explains — and what actually helps.
Sonnet 4.6 matches or beats Opus 4.6 on several benchmarks at 40% less cost. Frontier intelligence is no longer expensive. What it means for your AI budget.
Claude Opus 4.6 brings 1M context and agent teams. Cowork plugins wiped $285B off software stocks. What changed and why it matters.
Stanford identifies artificial flattery as one of AI's major problems in 2026. If you've used ChatGPT lately, you know exactly what they're talking about.
OpenAI integrates X/Twitter data into ChatGPT. What it means when your chatbot drinks from Musk's fountain.
Do language models reason or just improvise? The answer through Kahneman's framework and what it means for how we use them.
The 7 AI trends defining 2026: autonomous agents, small models, MCP, ROI focus and more. A guide for data professionals.
Practical guide to choosing between the big three LLMs. Pricing, capabilities, use cases, and which one fits your situation.
Complete DeepSeek guide for 2026. Free ChatGPT alternative: web, mobile app, and local installation with Ollama.
Everything you need to know to write effective prompts. From beginner to advanced, with practical examples and the limits nobody tells you about.
What World Models are, how V-JEPA works, and why Yann LeCun is betting $3.5 billion on them.
The godfather of AI bets $3.5 billion on a different architecture: World Models.
Language models fail in four distinct ways. Each requires a different fix: prompt tuning, RAG, fine-tuning, or guardrails. A practical taxonomy.
17 prompt iterations revealed that the model finds the correct answer but self-censors for not being standard
How an exhaustive meta-prompt caused context overflow and reached the same error on a random walk problem
3 coins, P(heads)=1/3, tails always even — 0 or 1/13? A prompt that forces LLMs to find the correct interpretation.
Two-Box separates contexts so the LLM reviews without bias. Problem: counterintuitive answers get discarded.