Deeply Personal Current: The Uncanny Valley of Empathy Cooking with an Algorithm All Posts Analysis Paralysis The Uncanny Valley of Empathy: Why AI Therapists Feel ‘Almost’ Human I did something weird last month. ...
Deeply Personal Current: Cooking with an Algorithm Nostalgia on a Plate All Posts The Uncanny Valley of Empathy Cooking with an Algorithm: I Let an AI Plan My Weekly Meal Prep My wife has a habit that’s equal parts adorable and terrifying: she organizes things with military precision. ...
Introduction: Two Systems of Thinking In cognitive science, Nobel laureate Daniel Kahneman described human thinking as two distinct systems: System 1: Fast, automatic, intuitive (e.g., recognizing faces, reading emotions) System 2: Slow, deliberate, analytical (e.g., solving math problems, planning) Traditional LLMs operate almost entirely in System 1 mode: they generate responses instantly, token by token, with no deliberate planning or self-reflection. Ask GPT-4 a question, and it starts answering immediately—no visible “thinking time.” ...
Introduction: The Scaling Dilemma Traditional transformer models face a fundamental trade-off: to increase model capacity, you must scale all parameters proportionally. If you want a smarter model, every single token must pass through every single parameter. This is dense activation, and it’s extremely expensive. Enter Mixture-of-Experts (MoE): a revolutionary architecture that achieves massive model capacity while keeping computational costs manageable through sparse activation. Models like GPT-4, Mixtral, and Switch Transformer use MoE to reach trillion-parameter scales while using only a fraction of those parameters per token. ...