Aug 31, 2025 · 4 min read · Large language models (LLMs) have taken the world by storm, capable of everything from writing essays to generating code. Yet, despite their impressive outputs, these models don't "think" in the human sense. They operate as non-thinking models, predi...
Join discussion
Aug 15, 2025 · 5 min read · Most language models will answer quickly and confidently—but not always correctly—because they jump straight from input → output. A “thinking model” inserts a deliberate reasoning phase in the middle: input → reasoning (scratchpad) → answer. This art...
Join discussion
Aug 15, 2025 · 4 min read · Have you ever wondered if an AI can truly think? 🤔 It turns out, it can! A thinking model can reason by talking to itself through a fascinating process of self-reflection. The magic behind this capability is a powerful technique known as CoT (Chain-...
Join discussion
Aug 15, 2025 · 1 min read · Building a Thinking Model from a Non-Thinking Model with Chain-of-Thought Most AI models answer directly without showing their reasoning. While fine for simple tasks, this “non-thinking” approach often fails for problems requiring multi-step logic. C...
Join discussion
Aug 15, 2025 · 4 min read · Introduction Large Language Models (LLMs) like GPT-4, Claude, or LLaMA are incredible at producing fluent, contextually relevant text. But at their core, these models don’t truly think they predict the next word based on patterns in the data they’ve ...
Join discussion
Feb 21, 2025 · 4 min read · Welcome to Silicon Valley's latest spectacle, where OpenAI's "thinking models" play the role of the bearded lady—a classic misdirection in the AI circus. Under the bright TED stage lights, OpenAI's star researcher Noam Brown sells an illusion: langua...
Join discussion
