98 related articles

Poth Labs models customer knowledge as a dynamic relationship network, using cross-source reasoning and adaptive surveys to help enterprises understand churn drivers and feature adoption.

Poth Labs models customer knowledge as a dynamic relationship network, using cross-source reasoning and adaptive surveys to help enterprises understand churn and feature adoption.

Notate is a new annotation tool that freezes fleeting UI states like hover effects and open menus, enables frame-by-frame animation debugging, and provides structured context for AI agents.

Reddit users report Gemini Pro job search quality dropping drastically in one week, returning expired listings and aggregator junk instead of quality active positions with direct employer links.

A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.

Asking LLMs to self-report confidence scores is a common mistake. Learn why it fails and discover reliable alternatives like logprobs, self-consistency sampling, and RAG.

In-depth analysis of Apple Silicon local LLM inference speed benchmarks covering M-series memory bandwidth, model quantization, MLX framework optimization, and Mac configuration guidance.

Why do AI Agents hallucinate more as they grow more complex? This article analyzes the causes from error accumulation, context noise, and model completion nature, with 5 practical production strategies.

Explore Gemini 3 Flash's core capability: extracting real textures from photos to generate design assets, helping designers and developers build custom creative tools.

GitHub found that giving Copilot more specialized tools actually degraded code review quality. By migrating to Unix-style composable tools and evidence-driven workflows, they cut costs and improved results.

A systematic guide to the complete learning path for AI Agent development—covering prompt engineering, RAG knowledge bases, LangChain & LangGraph, fine-tuning, and multi-agent collaboration.

A hands-on look at Vibe-Research, an open-source AI investment research tool supporting A-share, HK, and US stocks, with DeepSeek, Claude, and Codex integration.

A hands-on case study: using Claude Code and the LVGL graphics library to build a Tetris game running on an embedded dev board from scratch in under 3 hours.

As AI coding assistants like Codex become standard, the risks of overreliance grow too. Learn when developers should "show a red card," reclaim control, and safeguard code quality and responsibility.

Model performance gaps are closing. Real competitive advantage lies in portable AI agent architecture. Learn how to build a workspace that works across Claude Code, Codex, and beyond — no vendor lock-in.

Demystify large language models using middle-school math: LLMs are complex functions, training solves for parameters, and inference predicts next-token probabilities.

How to handle Agent infinite loops? This guide covers three-layer loop detection, four strategy-switching techniques, root cause analysis, and multi-layer fallbacks for building stable, production-grade Agent systems.

OpenSpiel 2.0 by Google DeepMind adds LLM fine-tuning examples, MCP tool server, JSON trajectories, AlphaZero on JAX, 19 new games, and Windows support.

AI agents are revolutionizing JS reverse engineering. This deep dive covers built-in tool chains, automation modes, prompt engineering for e-commerce, and full pipeline automation from parameter extraction to database storage.

OpenAI merges ChatGPT and Codex into a Super App, unveiling the early blueprint of an AI OS. A deep-dive into four core strategies: Loop workflows, tool stack economy, multi-threading, and Sites.