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143552 articles · Page 420 of 7178
AI Illustrated Series
AI Illustrated Series
Apr 27, 2026 · Artificial Intelligence

Comprehensive RAG Interview Q&A: 22 In-Depth Questions and Answers

This extensive interview guide covers 22 core RAG questions, detailing the definition, workflow, embedding selection, vector database choices, retrieval optimization, multi‑turn handling, context compression, evaluation metrics, knowledge‑graph integration, operational challenges, Agentic and hybrid RAG, document update strategies, similarity algorithms, and hallucination mitigation, providing concrete examples and practical advice for AI interview preparation.

AI interviewEmbeddingKnowledge Retrieval
0 likes · 29 min read
Comprehensive RAG Interview Q&A: 22 In-Depth Questions and Answers
AI Explorer
AI Explorer
Apr 27, 2026 · Artificial Intelligence

TradingAgents: A Multi‑Agent LLM Framework for Financial Trading

TradingAgents is an open‑source Python framework that splits the trading workflow into five specialized LLM agents, uses structured JSON communication, supports multiple model providers, and lets users quickly backtest or run live strategies with a single pip install.

FinanceLLMOpen Source
0 likes · 6 min read
TradingAgents: A Multi‑Agent LLM Framework for Financial Trading
AI Explorer
AI Explorer
Apr 27, 2026 · Artificial Intelligence

Single-File Hack Boosts Claude Code (92k★) with Four Senior‑Engineer Principles

The author presents a one‑file “CLAUDE.md” that, based on Andrej Karpathy’s four LLM coding pain points, rewrites Claude Code’s behavior using four concrete principles—think before coding, prioritize simplicity, make scalpel‑like edits, and drive execution with tests—turning AI from a noisy intern into a senior‑engineer‑like coder, and explains how to install it.

AI code generationClaude CodeGitHub
0 likes · 6 min read
Single-File Hack Boosts Claude Code (92k★) with Four Senior‑Engineer Principles
AI Explorer
AI Explorer
Apr 27, 2026 · Artificial Intelligence

Manifold AI’s Worldscape 0.2 Wins WorldArena, Marking a Shift from Seeing to Understanding

Manifold AI’s domestically developed Worldscape 0.2 model clinched first place in the rigorous WorldArena benchmark—demonstrating high‑fidelity dynamic scene generation and embodied control—highlighting a breakthrough in AI world models that move from mere visual perception toward genuine physical‑logic understanding, while noting the technology remains early‑stage.

AI benchmarkingManifold AIWorld Model
0 likes · 7 min read
Manifold AI’s Worldscape 0.2 Wins WorldArena, Marking a Shift from Seeing to Understanding
DeepHub IMBA
DeepHub IMBA
Apr 27, 2026 · Artificial Intelligence

DeepSeek‑V4 Deep Dive: Engineering Million‑Token Context Efficiency

The article provides a thorough technical analysis of DeepSeek‑V4, detailing how mixed sparse attention (CSA + HCA), manifold‑constrained hyper‑connections, the Muon optimizer, FP4 quantization, and a suite of infrastructure tricks enable stable training and inference with up to one‑million token contexts while achieving state‑of‑the‑art benchmark results.

CSADeepSeek V4FP4 Quantization
0 likes · 22 min read
DeepSeek‑V4 Deep Dive: Engineering Million‑Token Context Efficiency
Machine Heart
Machine Heart
Apr 27, 2026 · Artificial Intelligence

Why Traditional Video Captions Fail and How MTSS Solves the Problem

The article introduces Multi-Stream Scene Script (MTSS), a structured JSON‑based video description paradigm that replaces monolithic captions, explains its design principles, compares its advantages, and presents experimental evidence showing significant gains in both video understanding and generation tasks.

MTSSVideo Understandingmultimodal AI
0 likes · 8 min read
Why Traditional Video Captions Fail and How MTSS Solves the Problem
Machine Heart
Machine Heart
Apr 27, 2026 · Artificial Intelligence

Testing Alibaba’s HappyHorse 1.0: All‑in‑One Audio‑Video AI That Edits Itself

Alibaba’s HappyHorse 1.0, a native multimodal video generation model launched on April 27, combines audio‑video synthesis and editing in a single platform, tops several AI video benchmarks, offers low‑cost per‑second pricing, and demonstrates strong scene understanding through a series of prompt‑driven examples, while still showing minor glitches such as occasional text artifacts.

AI Video GenerationAlibabaHappyHorse
0 likes · 11 min read
Testing Alibaba’s HappyHorse 1.0: All‑in‑One Audio‑Video AI That Edits Itself
AI Programming Lab
AI Programming Lab
Apr 27, 2026 · Artificial Intelligence

Mastering Parallel Tasks with Claude Code Agent Teams: Best Practices

This guide explains the differences between Subagents and Agent Teams in Claude Code, when to enable parallel agent teams, how to configure and control teammates, display modes, practical examples, and proven best‑practice tips for efficient multi‑agent workflows.

AI multi‑agentAgent TeamsBest Practices
0 likes · 15 min read
Mastering Parallel Tasks with Claude Code Agent Teams: Best Practices
SuanNi
SuanNi
Apr 27, 2026 · Artificial Intelligence

Agent Skills Explained: Definition, Structure, and Engineering Practices

This article breaks down the official Anthropic definition of Agent Skills, shows how they are simple file‑system‑based, composable units stored in SKILL.md, scripts, references and assets, and explains the three‑layer progressive‑disclosure loading model, discovery, selection, execution, composition patterns, security, version‑control integration and evaluation practices.

AIAgent SkillsComposable
0 likes · 14 min read
Agent Skills Explained: Definition, Structure, and Engineering Practices
Smart Workplace Lab
Smart Workplace Lab
Apr 27, 2026 · Industry Insights

Data‑Application Illusion, Agentic AI, and New‑Hire Employment – US‑China AI Workplace Weekly (Apr 21‑27)

The report analyzes why AI project failure rates remain 70‑85%, how data‑application illusion and workslop erode productivity, and why integrating Agentic AI into native workflows is the only viable path, while highlighting a 16% drop in Gen Z AI‑related job placements and practical mitigation strategies.

AI workplaceData GovernanceEmployment Trends
0 likes · 8 min read
Data‑Application Illusion, Agentic AI, and New‑Hire Employment – US‑China AI Workplace Weekly (Apr 21‑27)
Baidu App Technology
Baidu App Technology
Apr 27, 2026 · Artificial Intelligence

Boosting End-to-End Efficiency with AI: From Single-Point Gains to Full Process Integration

The YoyoMan Drama team details how they transformed their product development pipeline by building Prompt‑friendly PRDs, design‑as‑code, AI coding infrastructure, and AI agents, creating a seamless “requirement‑design‑development‑test” loop that shifts work from manual effort to AI‑augmented processes across the entire workflow.

AIAI codingProduct Management
0 likes · 27 min read
Boosting End-to-End Efficiency with AI: From Single-Point Gains to Full Process Integration
AI Architect Hub
AI Architect Hub
Apr 27, 2026 · Artificial Intelligence

Why HNSW Can Speed Up Search 50× Compared to Brute‑Force? A Hands‑On Guide to Building Vector Indexes

The article explains why brute‑force vector search is painfully slow, introduces Flat, IVF, and HNSW index structures, compares their speed, memory and accuracy, shows common pitfalls, provides production‑grade Python code, and presents benchmark results that demonstrate HNSW’s superior speed‑accuracy trade‑off.

AIFAISSHNSW
0 likes · 12 min read
Why HNSW Can Speed Up Search 50× Compared to Brute‑Force? A Hands‑On Guide to Building Vector Indexes
Architect's Tech Stack
Architect's Tech Stack
Apr 27, 2026 · Artificial Intelligence

Can Your RAG System Pass the Demo and Remain Accurate Across 5,000 Documents?

The article dissects a tough interview question about building a production‑grade Retrieval‑Augmented Generation (RAG) system that not only works in a demo but also delivers stable, correct answers over a knowledge base of 5,000 documents, covering chunking, hybrid retrieval, intent routing, constrained generation, evaluation metrics, and operational safeguards.

Hybrid RetrievalIntent RoutingRAG
0 likes · 15 min read
Can Your RAG System Pass the Demo and Remain Accurate Across 5,000 Documents?
Machine Heart
Machine Heart
Apr 27, 2026 · Artificial Intelligence

ACL 2026: Unveiling a Predictive Scaling Law for Reinforcement Learning Fine‑Tuning of Large Models

The paper presents a systematic empirical study that derives a power‑law scaling formula for reinforcement‑learning‑after‑training of large language models, demonstrating accurate inter‑ and intra‑model performance prediction, learning‑efficiency saturation, data‑reuse benefits, and cross‑architecture validity.

Data ReuseLarge Language ModelsLlama-3
0 likes · 11 min read
ACL 2026: Unveiling a Predictive Scaling Law for Reinforcement Learning Fine‑Tuning of Large Models
Ops Community
Ops Community
Apr 27, 2026 · Operations

10 Essential Linux Commands Every Sysadmin Must Master

This guide walks system administrators through the ten most frequently used Linux commands—top/htop, df/du, free, ss/netstat, ping/traceroute, ps/kill, grep/sed/awk, tail/less, uname/hostname/uptime, and tar/rsync—explaining core options, output interpretation, common pitfalls, and practical troubleshooting scenarios.

LinuxMonitoringSystem Administration
0 likes · 25 min read
10 Essential Linux Commands Every Sysadmin Must Master