#LLM post-training
106 related articles
·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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·2 min
The Five-Layer Evolution of Scaling Law: How Physical AI Opens the Next Growth Curve
Deep analysis of Scaling Law's five-layer evolution from Pre-Training to Multi-Agent, exploring Physical AI's World Models, edge inference, and emotional interaction.
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·3 min
Claude Opus 4.8 Identifies Itself as DeepSeek: Data Contamination or Distillation? A Technical Analysis
Anthropic's Claude Opus 4.8 failed within 2 hours of launch, identifying itself as DeepSeek and Tongyi Qianwen in Chinese. Deep analysis of data contamination vs distillation hypotheses and multilingual alignment gaps.
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·3 min
Cursor Design Mode Launch and OpenAI Codex Updates: Latest Developments in AI Programming Tools
Cursor launches Design Mode for visual development, OpenAI Codex updates and Safety Lock Mode released, Anthropic doubles limits, AI agent leaderboards debut, Google DeepMind model compression breakthrough.
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·3 min
vLLM Deep Dive: How PagedAttention Enables High-Throughput LLM Inference
Deep dive into vLLM's core technologies for high-throughput LLM inference, including PagedAttention memory management, continuous batching, distributed deployment, and comparisons with TensorRT-LLM.
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Tech Frontiers·1 min
Gemini 3.5 Flash Achieves a Massive Leap on the GDPval Benchmark
Google Gemini 3.5 Flash surpasses Gemini 3.1 Pro on the GDPval benchmark. The lightweight Flash model leverages post-training techniques to approach frontier-level performance, redefining the balance between quality and cost.
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Deep Dives·3 min
Complete Guide to LLM Training: Pre-training, SFT Fine-tuning, and Preference Alignment Explained
Complete guide to the three core LLM training stages: pre-training, supervised fine-tuning (SFT), and preference alignment (DPO/PPO), covering LoRA, distillation, quantization, and pruning.
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Expert Opinions·3 min
The Salary Ceiling for Agent Engineers: Two Critical Dividing Lines
Agent engineer salary gaps hinge on two dividing lines: real production deployment experience and depth of foundational theory including deep learning, fine-tuning, and reinforcement learning.
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Product Reviews·3 min
Llama 3.3 70B In-Depth Review: Testing the Strongest Open-Source LLM with 13 Questions
Meta releases Llama 3.3 70B open-source model with just 70B parameters rivaling 405B performance. Tested on 13 logic, math, and coding questions, it passed 12 — reshaping the open-source model landscape.
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Tech Frontiers·2 min
Qwen Core Team Turmoil, OpenAI and Google Release New Models in Rapid Succession | AI Daily
Multiple core leaders depart Alibaba's Qwen team amid metric disputes. Same day: MiniMax Music 2.5+, OpenAI GPT 5.3 Instant, Google Gemini 3.1 Flashlight, and Seedance 2.0 pricing announced.
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Product Reviews·2 min
OpenAI Codex Deep Dive: The Real Reasons Developers Are Switching to It
In-depth analysis of why OpenAI Codex is becoming developers' preferred AI coding tool. From product evolution and competitor comparison to practical strategies, a comprehensive guide to Codex's advantages.
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Tutorials·4 min
NVIDIA Model Optimizer Post-Training Quantization (PTQ) Practical Guide
A deep dive into NVIDIA Model Optimizer's PTQ workflow, covering INT8/INT4 quantization principles, calibration methods, RTX GPU optimization, and best practices for deploying quantized LLMs on consumer GPUs.
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Deep Dives·5 min
Hugging Face Transformers: A Comprehensive Guide to the 160K-Star Open-Source AI Framework
Comprehensive guide to Hugging Face Transformers, the 160K-star GitHub framework—covering architecture, multimodal support, quantization, and inference optimization for loading, fine-tuning, and deploying pre-trained models.
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Product Reviews·4 min
Hugging Face Transformers: Deep Dive into the 160K-Star Open Source AI Model Framework
Deep dive into Hugging Face Transformers: architecture, multimodal support, ecosystem, and trends. Learn how this 160K-Star project became essential for AI developers.
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Tutorials·3 min
OpenAI Open-Sources GPT-OSS: Run O4-Level Models on 16GB VRAM — Complete Deployment Guide
OpenAI open-sources GPT-OSS (20B/120B) with MOE architecture and native FP4 precision. Run O3-level reasoning on a single RTX 4090. Full deployment guide for Ollama, vLLM, and more.
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Tech Frontiers·3 min
UK AISI Assessment Report: GPT-5.5 Cybersecurity Capabilities and Public Availability Raise Governance Concerns
UK AISI releases GPT-5.5 cybersecurity assessment showing vulnerability discovery capabilities on par with Claude Mythos, but its public availability raises urgent AI safety governance challenges.
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Product Reviews·3 min
GitHub 8000+ Stars: A Deep Dive into awesome-LLM-resources — The Most Comprehensive Large Language Model Resource Collection
Deep dive into the GitHub 8000+ star project awesome-LLM-resources, covering LLM training, multimodal generation, AI Agents, MCP protocol, AI-assisted coding, and more for developers.
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Product Reviews·3 min
awesome-LLM-resources: Deep Dive into a GitHub 8000+ Star LLM Resource Collection
Deep dive into GitHub's 8000+ star project awesome-LLM-resources, covering AI Agents, model training, MCP protocol, multimodal generation and more across 10 core LLM directions.
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Tutorials·4 min
Hugging Face Transformers: Deep Dive & Practical Guide to the 160K-Star AI Model Framework
Deep dive into Hugging Face Transformers: core features, multi-framework support, 500K+ pretrained models, full-modality task coverage, and hands-on code examples to build AI apps efficiently.
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