#scientific workflow AI
310 related articles
·2 min
Agent A1 Open Source: 35B MoE Local Inference Speed Test & Deployment Guide
Agent A1 is a 35B MoE open-source model from Shanghai's Intern Science, activating only 3B params. Hits 95 tok/s on M4 Mac Studio. Supports 256K context, tool calling, and free local deployment via Ollama.
Read more →
·5 min
DeepSeek V4 Enters Grayscale Testing, Grok 5.0 Ready to Launch | Latest AI Model Developments
This AI Daily covers five sectors: DeepSeek V4 reportedly enters grayscale testing with improved chain-of-thought; Musk previews Grok 4.6 and 5.0 with 2T parameters; Intern-S2 open-source model beats Claude Opus 4.8; xAI builds 2000MW Colossus cluster; NVIDIA RoboTTT breaks long-horizon robotics barriers.
Read more →
·6 min
The Evolution of Claude Code: From Manual Review to 65% Fully-Automated PRs
Anthropic engineers reveal Claude Code's 18-month evolution: system prompt cut by 80%, 65% of PRs shipped automatically by AI, Claude Tag collaboration, and the safety logic behind auto mode.
Read more →
·2 min
Codex Joins ChatGPT: A Beginner's Guide to AI Coding Agents
OpenAI integrates Codex into ChatGPT. Learn what AI coding agents can do, how Codex compares to Claude Code and Cursor, and how to get started today.
Read more →
·4 min
7 Core Components for Designing Long-Running AI Agents
A deep dive into the 7 core components for building long-running AI Agents: Goal, Evaluator, Verifier, Loop, Orchestration, Observability, and Memory.
Read more →
·2 min
Python Learning Path for Beginners: A Complete Breakdown of Three Core Modules
A complete Python learning path for beginners covering three modules: Fundamentals, Intermediate, and Hands-On Practice — including web scraping, office automation, and data analysis.
Read more →
Can LLMs Really Understand Computer Ar…
·3 min
Can LLMs Really Understand Computer Architecture Papers? A Deep Dive into Comprehension Capabilities
Can LLMs truly understand computer architecture papers? This article analyzes core challenges—from surface pattern matching to deep reasoning—and defines their capability limits for researchers.
Read more →
·2 min
Give Claude Code a Warcraft Voice Pack: Turning AI Coding into a Gaming Experience
An open-source project adds 43 game voice packs to Claude Code, covering 500+ lines from StarCraft, Red Alert, and Portal, triggered on task completion, authorization prompts, and errors.
Read more →
·3 min
Zero-Code Research: Using AI Agents to Run Complete Machine Learning Experiments
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.
Read more →
·3 min
No-Code Research: Using AI Coding Tools to Complete the Full Machine Learning Pipeline
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.
Read more →
·2 min
AI Autonomous Execution in Practice: How Codex Handles End-to-End Workflows from Analysis to Image Generation
A hands-on test of AI tool-calling: from e-commerce product page analysis and batch image generation to automated cross-border localization — how Codex-style models handle full workflows.
Read more →
·4 min
Codex Tutorial: Build Monetizable Products with AI Coding — No Experience Required
Step-by-step Codex tutorial: build a product finder tool and a flashcard mini program from scratch. Learn prompt techniques, requirements breakdown, and 4 monetization paths.
Read more →
·2 min
Grok 4.5 vs Composer 2.5: Real-World Code Benchmark — Who Wins?
A developer benchmarked Grok 4.5 High vs Composer 2.5 on real Terraform/AWS bug fixes. Composer 2.5 won decisively — even beating the pricier GPT-5.6 Sol.
Read more →
·2 min
Repaint: Free, Open-Source Offline Painting App with 16-Bit Color and AI Integration
Repaint is a free, open-source, fully offline cross-platform digital painting app built with C/C++, Raylib, and ImGui, featuring 16-bit color, modular brushes, non-destructive layers, and offline Stable Diffusion AI integration.
Read more →
·2 min
Build From Scratch or Just Use sklearn? A Complete ML Engineer Learning Path Guide
Should you implement ML algorithms from scratch or just use sklearn? This guide breaks down the optimal learning path for ML engineers by career stage and company type.
Read more →
·2 min
AI Large Model Learning Roadmap: A Complete Five-Stage Guide from Zero to Independent Deployment
A complete 5-stage AI large model learning roadmap — from Python basics and prompt engineering to RAG pipelines, Agent development, and private model deployment.
Read more →
The Biggest Bottleneck in AI-Driven Re…
·2 min
The Biggest Bottleneck in AI-Driven Research: How the Validation Problem Constrains Scientific Discovery
AI generates scientific hypotheses fast, but experimental validation can't keep up. Explore the validation bottleneck in AI-driven research and four strategic solutions.
Read more →
·3 min
SJTU Professors Open-Source Agent Tutorial: A Four-Stage Path from Zero to AI Engineer
SJTU professors open-source a 4-stage Agent tutorial on GitHub, covering LLM basics, ReAct, multi-agent systems, and real-world projects — a practical path to AI engineering.
Read more →
LFortran + Enzyme: A New Path to Autom…
·2 min
LFortran + Enzyme: A New Path to Automatic Differentiation for Fortran Code
LFortran + Enzyme enables automatic differentiation for decades of Fortran scientific code without rewrites. Learn the technical principles, implementation path, and impact on scientific ML.
Read more →
Dmars: A Modern Toolchain for the Clas…
·2 min
Dmars: A Modern Toolchain for the Classic Core Wars Programming Game
Dmars is a modern toolchain for Core Wars, featuring a Redcode assembler, MARS simulator, and debugging tools. Learn why this 1980s programming battle game still matters today.
Read more →