3522 related articles

A detailed guide on using AI Agents to build Research Logs for scientific experiments, covering skeleton structure, daily workflows, pre-experiment thinking standards, code change tracking, and Agent-researcher division of labor.

Learn how to use AI Agents to build a Research Log for scientific experiments, covering structure, daily workflows, pre-experiment thinking, code change tracking, and human-AI division of labor.

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.

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.

last30days-skill is a GitHub AI Agent skill with 50K+ Stars, enabling cross-platform research across Reddit, X, YouTube, Hacker News, and Polymarket to generate grounded 30-day summary reports.

last30days-skill is a 50K+ Star AI Agent skill on GitHub that performs cross-platform research across Reddit, X, YouTube, Hacker News, and Polymarket to generate grounded 30-day summary reports.

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.
Open Deep Research: A Complete Guide t…
A deep dive into LangChain's open-source project open_deep_research: an AI deep research agent built on LangGraph, supporting flexible multi-model and multi-search tool configuration, with 12,000+ stars.
From Math to AI Research Engineer: A D…
A GitHub project called maths-cs-ai-compendium surpassed 6,000 Stars with a roadmap for becoming an AI/ML Research Engineer. Here's what makes it worth following.

Former OpenAI researcher Daniel Kokotajlo, who forfeited $2M in equity, warns of a 70% chance AI leads to catastrophic outcomes and superintelligence by 2029.

No coding required: use AI agents like Codex and Claude Code to complete full ML experiments via natural language. A real case study with a heart disease dataset.

No coding skills? No problem. Learn how AI tools like Codex and Claude Code let researchers complete ML workflows — data cleaning, model training, visualization — using only natural language.

AI Agents are taking over experiment design, execution, and paper writing. Learn how graduate students can redirect their competitive edge in the age of automated research.

A curated open-source repo of 500+ active AI research tools covers the full workflow—literature review, code reproduction, paper writing, and LaTeX formatting—potentially saving 80% of research time.

A psychology study on corporate buzzword receptivity reveals the cognitive traps behind AI industry hype. Why do jargon-speakers outshine engineers? A deep dive.
The Biggest Bottleneck in AI-Driven Re…
AI generates scientific hypotheses fast, but experimental validation can't keep up. Explore the validation bottleneck in AI-driven research and four strategic solutions.

No coding required — just describe your needs in natural language. AI Agents handle data cleaning, model training, and visualization automatically. We tested Codex and Claude Code on a heart disease prediction task.

MSR India director Venkat Padmanabhan reveals Microsoft's shift to an infrastructure company with $200B annual investment, covering AI efficiency, SLMs, and Global South tech diffusion.

An in-depth look at AI interpretability research: from chain of thought and probes to sparse autoencoders, exploring how scientists understand neural network internals and assess AI alignment and safety.
The Complete AI Researcher Learning Ro…
A structured AI/ML learning roadmap covering Python, math, machine learning, deep learning, and MLOps — with timelines, milestones, and free resource recommendations.