AI2ML AI to Machine Learning
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AI2ML AI to Machine Learning

Original articles on artificial intelligence and machine learning, deep optimization. Less is more, life is simple! Shi Chunqi

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Latest from AI2ML AI to Machine Learning

48 recent articles
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Jul 24, 2025 · Artificial Intelligence

Exploring Recent Large‑Model Agent Papers: Insights and Analyses

This article reviews a series of recent research papers on large‑model agents, covering topics such as reinforcement‑learning‑driven ML agents, premise‑critique ability of LLMs, long‑term tool‑augmented LLM evaluation, agentic RAG, set‑based retrieval for multi‑hop QA, mobile VLM agents, and broader surveys of LLM applications, summarizing each work’s problem statement, prior approaches, novel contributions, experimental results, limitations, and future directions.

Agentic AILLM evaluationReinforcement Learning
0 likes · 46 min read
Exploring Recent Large‑Model Agent Papers: Insights and Analyses
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Jun 6, 2025 · Artificial Intelligence

Tackling the Top Challenges of Retrieval‑Augmented Generation (RAG)

The article enumerates common pitfalls of Retrieval‑Augmented Generation—such as missing content, low‑rank document misses, context limits, format errors, incomplete answers, scalability bottlenecks, complex PDF extraction, data‑quality issues, domain adaptation gaps, hallucinations, and feedback‑loop deficiencies—and offers concrete mitigation strategies ranging from data cleaning and prompt design to hybrid search, hierarchical retrieval, document compression, and automated evaluation.

Data QualityHybrid SearchLLM
0 likes · 9 min read
Tackling the Top Challenges of Retrieval‑Augmented Generation (RAG)
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Apr 17, 2025 · Artificial Intelligence

Inside Qwen: A Deep Dive into the Large Model’s Source Code

The article provides a comprehensive technical walkthrough of Qwen’s large‑model series, covering data preparation, tokenization, model tweaks, training settings, RLHF pipeline, Code‑Qwen specifics, Qwen2 and Qwen3 architectural changes, scaling‑law experiments, and detailed source‑code analysis with illustrative diagrams.

Large Language ModelMoEQwen
0 likes · 7 min read
Inside Qwen: A Deep Dive into the Large Model’s Source Code
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Mar 21, 2025 · Artificial Intelligence

Comparing Four Leading Open‑Source LLM Agent Frameworks: Autogen, CrewAI, LangGraph, and Swarm

This article provides a detailed comparison of four prominent open‑source LLM agent frameworks—Autogen, CrewAI, LangGraph, and Swarm—covering their core concepts, strengths, weaknesses, ideal use cases, and how they differ in scalability, memory handling, tool integration, and community support.

AutoGenCrewAIEnterprise AI
0 likes · 14 min read
Comparing Four Leading Open‑Source LLM Agent Frameworks: Autogen, CrewAI, LangGraph, and Swarm
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Feb 10, 2025 · Artificial Intelligence

Eight Ways Enterprises Can Leverage DeepSeek

The article outlines eight distinct enterprise strategies for adopting DeepSeek, categorizing them by model maturity, available data types, and specific business challenges, and maps these approaches onto four capability tiers—from basic compliance requirements to advanced multimodal, low‑cost solutions.

AI agentsDeepSeekEnterprise AI
0 likes · 3 min read
Eight Ways Enterprises Can Leverage DeepSeek
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Feb 8, 2025 · Artificial Intelligence

Analyzing DeepSeek R1 Inference Projects: Source Code, Cold‑Start, and Scaling Techniques

This article examines DeepSeek R1’s three breakthroughs, its low‑cost optimizations that bypass CUDA, and the resulting impact on the AI ecosystem, then provides a detailed technical review of seven open‑source reproductions—Open‑R1, Tiny‑Zero, SimpleScaling‑S1, and simpleRL‑reason—covering their architectures, reinforcement‑learning pipelines, and code implementations.

DeepSeekInference ScalingPTX
0 likes · 10 min read
Analyzing DeepSeek R1 Inference Projects: Source Code, Cold‑Start, and Scaling Techniques
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Feb 5, 2025 · Artificial Intelligence

What Optimizations Power DeepSeek’s High‑Efficiency LLMs?

The article enumerates DeepSeek’s extensive technical optimizations—including Grouped Query Attention, Multi‑head Latent Attention, Mixture‑of‑Experts, 4D parallelism, quantization, and multi‑token prediction—that together enable cheap, high‑performance large language models.

4D parallelismDeepSeekGrouped Query Attention
0 likes · 8 min read
What Optimizations Power DeepSeek’s High‑Efficiency LLMs?
AI2ML AI to Machine Learning
AI2ML AI to Machine Learning
Aug 3, 2024 · Artificial Intelligence

Why Chinese Universities Are Falling Behind in AI4Science Courses

The article analyzes the rapid rise of AI4Science, highlights the talent gap in China’s industrial sector, presents an AI‑driven PDE case study, compares the strengths and challenges of physics‑based versus data‑driven modeling, and surveys leading AI‑for‑Science courses at top Western universities, concluding that Chinese institutions still lag behind in curriculum development.

AI4ScienceCourse ComparisonIndustrial AI
0 likes · 9 min read
Why Chinese Universities Are Falling Behind in AI4Science Courses