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Baobao Algorithm Notes
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Baobao Algorithm Notes

Author of the BaiMian large model, offering technology and industry insights.

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Baobao Algorithm Notes
Baobao Algorithm Notes
Apr 27, 2026 · Artificial Intelligence

DeepDive into DeepSeek‑V4: Efficient Million‑Token Context, Hybrid Attention, and Muon Optimizer

The article provides an in‑depth technical analysis of DeepSeek‑V4, detailing its novel hybrid attention architecture (CSA and HCA), the manifold‑constrained hyper‑connection (mHC), massive KV‑cache reductions, FLOPs savings across token lengths, and the Muon optimizer with Newton‑Schulz orthogonalization, all backed by concrete benchmark tables and code snippets.

DeepSeekKV cache reductionLarge Language Model
0 likes · 61 min read
DeepDive into DeepSeek‑V4: Efficient Million‑Token Context, Hybrid Attention, and Muon Optimizer
Baobao Algorithm Notes
Baobao Algorithm Notes
Apr 20, 2026 · Industry Insights

From Prompt Writer to Harness Architect: Redefining the Algorithm Engineer in the LLM Era

The article analyzes how the rise of foundation models shifts algorithm engineers from hand‑crafting models to building robust Harness environments, detailing OpenAI’s agent‑first experiments, the new "Model + Harness" formula, and practical steps for staying valuable in a prompt‑centric world.

AI engineeringHarness architectureLLM
0 likes · 9 min read
From Prompt Writer to Harness Architect: Redefining the Algorithm Engineer in the LLM Era
Baobao Algorithm Notes
Baobao Algorithm Notes
Apr 14, 2026 · Industry Insights

Why Mastering AI Agents Is the Most Critical Skill Right Now

The article argues that leveraging AI agents like Claude Code is now the top priority for developers, explaining how agents boost productivity, the importance of their operating environment, and why embracing them is essential for future success in the AI-driven workplace.

Agent TrainingClaude CodeLLM
0 likes · 10 min read
Why Mastering AI Agents Is the Most Critical Skill Right Now
Baobao Algorithm Notes
Baobao Algorithm Notes
Mar 20, 2026 · Artificial Intelligence

Can AI Self‑Iterate? Inside MiniMax M2.7’s Self‑Improving Magic

The article examines MiniMax M2.7’s claim of self‑iteration, its impressive Kaggle record, and a series of technical tests—including code refactoring, real‑time chart generation, futures backtesting, business analysis, PPT creation, and news tracking—to evaluate the model’s practical AI self‑evolution capabilities.

AIAutoMLKaggle
0 likes · 8 min read
Can AI Self‑Iterate? Inside MiniMax M2.7’s Self‑Improving Magic
Baobao Algorithm Notes
Baobao Algorithm Notes
Mar 2, 2026 · Artificial Intelligence

How “Skills” Turn LLM Prompts into Portable, Engineered Workflows

This article dissects the evolution of LLM prompts into structured, version‑controlled skill packages, explains the AgentSkills specification, details OpenClaw’s implementation, compares prompts, memory, MCP and skills, and provides end‑to‑end examples with code, flowcharts and best‑practice recommendations.

Agent SkillsAutomationLLM
0 likes · 40 min read
How “Skills” Turn LLM Prompts into Portable, Engineered Workflows
Baobao Algorithm Notes
Baobao Algorithm Notes
Feb 25, 2026 · Artificial Intelligence

Exploring Qwen 3.5: Small‑Scale MoE Models, Architecture, and Deployment Guides

This article reviews the three open‑source Qwen 3.5 models—including a 35B MoE, a 122B MoE, and a 27B dense version—detailing their parameter layouts, core attention designs, context length, inference performance, hardware requirements, and provides step‑by‑step code examples for loading them with Hugging Face Transformers and vLLM.

AILarge Language ModelMoE
0 likes · 10 min read
Exploring Qwen 3.5: Small‑Scale MoE Models, Architecture, and Deployment Guides
Baobao Algorithm Notes
Baobao Algorithm Notes
Feb 24, 2026 · Artificial Intelligence

The Bitter Lesson of Building Agentic RL in Terminal Environments

This article recounts the challenges of moving from single‑step RL with verifiable rewards to multi‑step agentic reinforcement learning in terminal environments, detailing infrastructure design, asynchronous pipelines, data quality checks, masking strategies, curriculum training, chunk‑based optimization, and practical lessons learned from large‑scale experiments.

Agentic RLAsynchronous TrainingCredit Assignment
0 likes · 33 min read
The Bitter Lesson of Building Agentic RL in Terminal Environments
Baobao Algorithm Notes
Baobao Algorithm Notes
Feb 12, 2026 · Artificial Intelligence

GLM-5 Unleashed: How the New Chinese LLM Tackles Full‑Stack Architecture and Complex System Design

The article reviews the newly released GLM-5 model, highlighting its ability to generate end‑to‑end system designs, write and debug backend code, and solve large‑scale engineering problems through detailed prompts, positioning it alongside GPT‑5.3 and Claude Opus in the competitive LLM landscape.

AI programmingGLM-5backend architecture
0 likes · 9 min read
GLM-5 Unleashed: How the New Chinese LLM Tackles Full‑Stack Architecture and Complex System Design