<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:content="http://purl.org/rss/1.0/modules/content/"><channel><title>Ai on knowledged.to</title><link>https://knowledged.to/tags/ai/</link><description>Recent content in Ai on knowledged.to</description><generator>Hugo</generator><language>en-us</language><lastBuildDate>Mon, 25 May 2026 23:31:16 +0530</lastBuildDate><atom:link href="https://knowledged.to/tags/ai/index.xml" rel="self" type="application/rss+xml"/><item><title>Anti-Narration in Harness Engineering</title><link>https://knowledged.to/ai/concepts/anti-narration/</link><pubDate>Mon, 25 May 2026 18:01:07 +0000</pubDate><guid>https://knowledged.to/ai/concepts/anti-narration/</guid><description>Harness pattern that forces verification before accepting fluent AI outputs as correct.</description></item><item><title>PPO — Proximal Policy Optimization</title><link>https://knowledged.to/notes/ml/ppo-proximal-policy-optimization/</link><pubDate>Tue, 19 May 2026 17:18:44 +0000</pubDate><guid>https://knowledged.to/notes/ml/ppo-proximal-policy-optimization/</guid><description>Overview of PPO, the clipped policy-gradient RL algorithm used in RLHF for InstructGPT and original ChatGPT.</description></item><item><title>GRPO — Group Relative Policy Optimization</title><link>https://knowledged.to/notes/ml/grpo-group-relative-policy-optimization/</link><pubDate>Tue, 19 May 2026 17:17:58 +0000</pubDate><guid>https://knowledged.to/notes/ml/grpo-group-relative-policy-optimization/</guid><description>Critic-free RL algorithm that replaces PPO&amp;#39;s value model with group-relative rewards for LLM fine-tuning.</description></item><item><title>Tool-DC Strategic Anchor Grouping — Web Search Example</title><link>https://knowledged.to/notes/ml/tool-dc-strategic-anchor-grouping-example/</link><pubDate>Tue, 19 May 2026 06:12:48 +0000</pubDate><guid>https://knowledged.to/notes/ml/tool-dc-strategic-anchor-grouping-example/</guid><description>Concrete web-search example showing how Tool-DC strategic anchor grouping reduces schema-confusion in tool calls.</description></item><item><title>AgentFlow</title><link>https://knowledged.to/notes/ml/agentflow/</link><pubDate>Tue, 19 May 2026 05:08:59 +0000</pubDate><guid>https://knowledged.to/notes/ml/agentflow/</guid><description>Overview of AgentFlow, an agent architecture that trains a planner with Flow-GRPO for multi-turn tool use.</description></item><item><title>Tool-DC Framework</title><link>https://knowledged.to/notes/ml/tool-dc-framework/</link><pubDate>Tue, 19 May 2026 03:53:48 +0000</pubDate><guid>https://knowledged.to/notes/ml/tool-dc-framework/</guid><description>Overview of Tool-DC, a try-check-retry framework for robust long-context tool-calling with large tool registries.</description></item><item><title>Attention in Machine Learning</title><link>https://knowledged.to/notes/ml/attention/</link><pubDate>Sun, 17 May 2026 05:54:45 +0000</pubDate><guid>https://knowledged.to/notes/ml/attention/</guid><description>Explanation of the attention mechanism in ML, covering Query/Key/Value, self-attention, multi-head, causal, cross-attention, and efficiency variants like FlashAttention and GQA.</description></item><item><title>Six-Dimension Art Evaluation Rubric</title><link>https://knowledged.to/notes/ml/art-evaluation-rubric/</link><pubDate>Thu, 14 May 2026 13:02:47 +0000</pubDate><guid>https://knowledged.to/notes/ml/art-evaluation-rubric/</guid><description>A six-dimension rubric (Beauty, Color, Texture, Content Detail, Line, Style) for evaluating AI-generated artworks, derived from traditional painting analysis principles.</description></item><item><title>Commitment Gate (Harness Engineering)</title><link>https://knowledged.to/ai/concepts/commitment-gate/</link><pubDate>Wed, 13 May 2026 16:14:59 +0000</pubDate><guid>https://knowledged.to/ai/concepts/commitment-gate/</guid><description>A workflow checkpoint in harness engineering that enforces quality criteria before an agent&amp;#39;s change can be merged or committed.</description></item><item><title>Commitment Gate (Harness Engineering)</title><link>https://knowledged.to/notes/ml/commitment-gate/</link><pubDate>Wed, 13 May 2026 16:01:45 +0000</pubDate><guid>https://knowledged.to/notes/ml/commitment-gate/</guid><description>Verification checkpoint in agent harnesses that blocks irreversible actions until cross-skill, cross-scale, and evidence-sufficiency checks pass.</description></item><item><title>Deterministic Graders (for LLM / AI Evaluation)</title><link>https://knowledged.to/ai/concepts/deterministic-graders/</link><pubDate>Fri, 24 Apr 2026 17:18:23 +0000</pubDate><guid>https://knowledged.to/ai/concepts/deterministic-graders/</guid><description>Definition and best practices for deterministic grading in LLM evaluation using code-based rules instead of model-in-the-loop judgment.</description></item><item><title>Chain of Thought (CoT)</title><link>https://knowledged.to/notes/ml/chain-of-thought/</link><pubDate>Thu, 23 Apr 2026 15:53:32 +0000</pubDate><guid>https://knowledged.to/notes/ml/chain-of-thought/</guid><description>Prompting technique where an AI model is guided — or learns — to reason through a problem step by step before arriving at the final answer, rather than jumping straight to the conclusion.</description></item><item><title>Multi-Turn Conversation in AI</title><link>https://knowledged.to/ai/concepts/multi-turn-conversation/</link><pubDate>Tue, 21 Apr 2026 15:13:14 +0000</pubDate><guid>https://knowledged.to/ai/concepts/multi-turn-conversation/</guid><description>Explains how AI models maintain context across multiple exchanges using conversation history injection rather than internal memory.</description></item><item><title>Agent Harness Engineering</title><link>https://knowledged.to/notes/ml/agent-harness-engineering/</link><pubDate>Fri, 17 Apr 2026 17:47:03 +0000</pubDate><guid>https://knowledged.to/notes/ml/agent-harness-engineering/</guid><description>Overview of agent harness engineering — the scaffolding, infrastructure, and tooling surrounding an AI agent, covering execution environments, tool orchestration, memory management, control flow, tracing, safety, and state persistence</description></item></channel></rss>