1836 related articles

Perplexity integrates Deep Research as a native skill in Computer, enabling automatic invocation without manual mode switching. Analyzing the Agent Harness design philosophy and AI capability fusion trends.

Some AI companies are mass-purchasing physical books for destructive scanning and pulping—even rare and antiquarian volumes—to obtain training data, sparking heated cultural preservation debates.

Deep analysis of the EYG programming language's core design, including algebraic effects, program state persistence, and cross-platform portability, exploring how it addresses modern software fragmentation.

An in-depth look at the real daily work of data scientists, MLEs, and MLOps engineers — covering responsibilities, essential tools, and career paths to help you find your direction in AI.

A comprehensive guide to AI Agent architecture and development, covering automated marketing, intelligent customer service, and investment analysis scenarios with single and multi-agent collaboration.

Google DeepMind announces Gemini 4 pre-training has begun, calling it their most ambitious training yet. A deep dive into its technical direction, compute scale, multimodal breakthroughs, and competitive impact.

Discover how LiDAR laser technology penetrates deserts and jungles to reveal Sela's underground cistern system and Nan Madol's hidden structures, rewriting the history of lost civilizations.

SlopCodeBench sparks deep reflection on AI code evaluation. From benchmark contamination to pass-rate pitfalls, exploring why current benchmarks fail to measure real code quality.

AI research automation will look more like data cleaning than inventing the Transformer. Explore how automating 60%-80% of repetitive research work reshapes the AI research paradigm.

Why AI research automation looks more like data cleaning than inventing the Transformer. Exploring the value of automating 60%-80% of repetitive research work and how human-AI collaboration reshapes the research paradigm.

A deep dive into LLM Agent frameworks covering RAG, Agent core components (tools, memory, planning), and Agent Tuning workflows with cost considerations for production deployment.

Large models aren't search engines — they're more like super compressors. This article explains how LLMs compress data to learn semantic patterns, and explores the phenomenon of intelligent emergence.

A 6-week systematic learning path for frontend engineers transitioning to AI Agent development, covering core architecture, ReAct, multi-agent collaboration, RAG integration, and deployment.

Chinese open-source AI models surged from under 10% to 58% of U.S. AI consumption. Kimi K3, DeepSeek, and Qwen are reshaping AI cost structures as DoorDash, Airbnb, and other Silicon Valley giants adopt them at scale.

Exploring the key evolution in coding agent architecture: separating the reasoning core from code execution environments to decouple control and execution planes.

Generative AI is profoundly redefining the personal computer — from passive tool to intelligent collaborator. This article examines the core shifts of the AI PC era and the productivity gap created by cognitive lag.

Deep analysis of FeyNoBg, an open-source background removal project with pre-trained models and training library, compared to remove.bg and rembg solutions.

Analysis of why Gemini and other AI LLMs exhibit capability drift, including tool-calling mechanisms, context window limits, and safety policy triggers, plus practical strategies for PDF generation failures.

Fields Medal winner Jacob Tsimerman joins OpenAI's safety team on award day, declaring math careers won't survive. Meanwhile, NVIDIA finances a $250B data center and Kimi K3 open-sources 2.8T parameters.

Fields Medal winner Jacob Tsimerman joins OpenAI's safety team on award day, saying math careers won't survive. NVIDIA finances a $250B data center. Kimi K3 opens a 2.8T-parameter model.