#LLM post-training
104 related articles
·6 min
GLM 5.2 Arrives: Industry Upheaval on the Eve of AI Margin Collapse
The rise of Zhipu's GLM 5.2 is accelerating the democratization of LLM capabilities. This article analyzes the commoditization of foundation models, the logic behind margin collapse, and the opportunities and challenges facing application-layer and foundation model firms.
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·4 min
NVFP4 Quantization in Practice: A Guide to Compressing Large Models with NVIDIA Model Optimizer
Deep dive into NVFP4 quantization: using NVIDIA Model Optimizer to compress Nemotron 3 Ultra to FP4 checkpoints, reducing memory by 75% and boosting inference throughput on Blackwell GPUs.
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·5 min
NVIDIA AI-Q Blueprint × OCI: A Practical Guide to Production Deployment of Enterprise AI Agents
Deep dive into NVIDIA AI-Q Blueprint production deployment on Oracle Cloud Infrastructure, covering NIM microservices, RAG architecture, multi-agent orchestration, and OCI GPU selection.
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·5 min
NVIDIA AI-Q Blueprint × OCI: A Practical Guide to Production Deployment of Enterprise AI Agents
Deep dive into NVIDIA AI-Q Blueprint production deployment on Oracle Cloud Infrastructure, covering NIM microservices, RAG architecture, multi-agent orchestration, and OCI GPU selection for enterprise AI agents.
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·3 min
LLM Development Learning Path: From Zero to Enterprise-Level Projects
A complete LLM development learning roadmap covering prompt engineering, RAG, AI Agents, and fine-tuning — helping beginners master LangChain, LlamaIndex, and more.
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The True Nature of Moving Fast: Freque…
·3 min
The True Nature of Moving Fast: Frequent Contact with Reality Is a Form of Humility
"Moving fast" isn't recklessness — it's intellectual humility. This article explores the shared logic behind Agile, MVP, and AI iteration: true arrogance is believing you don't need to be tested.
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·3 min
Cursor & Claude Code Enterprise Training: AI Coding Tool Division of Labor and Practical Methodology
How can R&D teams truly leverage AI coding tools? This article breaks down Cursor vs. Claude Code division of labor, an eight-step framework, and how to build reusable AI collaboration assets.
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·4 min
LLM Job Interviews: Multi-Agent and Harness Engineering Are Now Must-Know Topics
Deep analysis of LLM job interview essentials: Multi-Agent architecture, Harness engineering, Agent Loop, sandbox isolation, and memory management with career transition tips.
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·3 min
Cursor Composer 2.5: The Secret Behind an Open-Source Model's Reinforcement Training to a Top-3 Coding Benchmark Ranking
Cursor built Composer 2.5 on Kimi K2 open-source model, ranking 3rd on coding benchmarks and surpassing K2.6. Deep dive into Cursor's data flywheel, product architecture, and pricing.
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·3 min
Fireworks Platform Adds Nemotron 3 Ultra Post-Training Support: End-to-End Fine-Tuning and Deployment
Fireworks AI adds NVIDIA Nemotron 3 Ultra post-training support with SFT, DPO, LoRA, and full fine-tuning, enabling seamless train-to-deploy workflows for open-weight LLM customization.
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·2 min
How Low-Quality RL Environments Sabotage Model Training: A Diagnosis and Repair Guide
Diagnose and fix common RL training environment issues including reward hacking, flawed state spaces, and broken verifiers that silently degrade model performance.
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·3 min
Claude Code with Local LLMs: Token-Free Deployment Guide & Configuration
Learn how to connect Claude Code to local LLMs for token-free AI coding. Covers three-layer architecture, Ollama/LM Studio/vLLM setup, protocol translation, and hardware selection.
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·2 min
Nex N2 Pro Real-World Testing: Top 5 on Official Benchmarks, Only 12th in Independent Tests
Deep-dive testing of Nex N2 Pro open-source Agent model comparing official benchmarks vs independent results. The 397B parameter model shows decent frontend generation but ranks 12th independently, not top 5 as claimed.
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·4 min
AI Engineer Job Search: The Capability Leap from Demo to Production System
AI job demand is surging but companies can't find qualified candidates. Learn the 3 core skills—advanced RAG, local model deployment, and full-stack monitoring—to leap from demo builder to production engineer.
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·4 min
Nex-N2 Pro In-Depth Review: Impressive Code Generation, But How Inflated Are the Benchmarks?
In-depth review of open-source agent model Nex-N2 Pro: testing code generation, SVG output, and game dev capabilities while analyzing benchmark inflation, GPT distillation traces, and speed issues.
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·3 min
Claude Code Local Deployment: A Practical Guide to Connecting Local LLMs
Complete guide to deploying Claude Code locally with Ollama, LM Studio, or vLLM. Covers architecture, protocol translation, hardware requirements, and model selection for zero-cost, private AI coding.
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·3 min
Hermes Agent Deep Dive: A Self-Evolving Agent Architecture with Practical Implementation Guide
Deep dive into Hermes Agent's core architecture: four-layer memory system, Skill self-evolution mechanism, Harness Engineering methodology, OpenCloud comparison, and Feishu integration tutorial.
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·3 min
Complete Guide to Pi Coding Agent: Building Customized AI Programming with Minimalist Four Tools + Extension System
In-depth guide to Pi Coding Agent: its four core tools, extension system development, Skills management, and detailed comparison with Claude Code for building customized AI programming workflows.
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·4 min
Harness Engineering: A New Software Development Paradigm Where Humans Steer and AI Agents Execute
OpenAI engineer Ryan Lopopolo introduces Harness Engineering — a methodology where humans build constraint systems and AI agents handle all code implementation.
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·3 min
ChatGPT Financial Services Workflow in Practice: A Complete Guide from Investment Research to Financial Modeling
OpenAI demonstrates how ChatGPT transforms financial services workflows — from GPT 5.5 financial optimization and Deep Research investment dossiers to Excel financial modeling and automated decision presentations.
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