#LLM post-training
98 related articles
·2 min
Selling Reinforcement Learning Environments: Real Business Opportunity or Phantom Demand?
Can selling RL environments be a viable startup? We break down TAM, technical barriers, Scale AI competition, and real niche opportunities in this emerging space.
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·4 min
RAM: First-Principles Approach to 50x Faster RL Post-Training for Diffusion Models
RAM (Reinforce Adjoint Matching) achieves 50x faster RL post-training for diffusion models by discarding path costs, combining ODE sampling with decorrelated training objectives. A deep dive into RAM's core principles and experiments vs. Flow-GRPO.
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·3 min
The Complete LLM Learning Roadmap: From Beginner to Expert — Courses and Resources Recommended
Confused by scattered LLM resources and unclear learning paths? This guide maps a complete roadmap from basics to advanced, covering Karpathy, Stanford CS224N, DeepLearning.AI, Hugging Face, plus RAG, fine-tuning, and Agent deep dives.
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·2 min
Distributed AI Systems: A Practical Engineering Guide to Training, Inference, and Production Deployment
A deep dive into distributed AI systems engineering: data/model/tensor parallelism for training, KV cache, quantization, elastic scaling for inference, and cloud deployment with Kubernetes, Ray, and DeepSpeed.
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·7 min
Breaking Down the Core Skills of an AI Application Engineer: From Beginner to Industrial-Grade Deployment
Knowing how to call an API doesn't make you an AI engineer. This article breaks down the complete skill structure of an AI application engineer, covering Python fundamentals, LLM fine-tuning, Agent development, and enterprise projects.
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Mesh LLM: A Practical Exploration of B…
·3 min
Mesh LLM: A Practical Exploration of Building a P2P Distributed AI Inference Network with iroh
Mesh LLM leverages the Rust P2P framework iroh to integrate compute from scattered nodes, exploring a viable path for decentralized LLM inference. This article analyzes its architecture, challenges, and prospects.
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·4 min
Unsloth Releases Qwen3.6 NVFP4 Quantization: 2.5x Faster with Zero Accuracy Loss
Unsloth releases NVFP4 quantization for Qwen3.6 using W4A4 true 4-bit Tensor Core computation, delivering up to 2.5x inference speedup over NVIDIA's official implementation with accuracy matching or exceeding BF16 on benchmarks like MMLU-Pro.
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·5 min
GPT-5.6 In-Depth Review: Crushing Competitors on Value, But Its Jailbreak Vulnerabilities Can't Be Ignored
OpenAI's GPT-5.6 Soul, Terra & Luna are priced at one-third of Claude, leading Anthropic Fable on many benchmarks. We analyze its value, reasoning, and jailbreak risks.
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·5 min
ChatGPT Work Officially Launches: How GPT-5.6 Is Reshaping the Way You Work
OpenAI launches the GPT-5.6 model family (Sol/Terra/Luna) and ChatGPT Work, enabling automated financial analysis, local file operations, Codex coding, and cross-app workflows—AI officially becomes a real work partner.
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·7 min
AI Agent Runs a Fully Automated Chess Channel: A Real-World Practice of Combining LLMs with Engines
A German engineer built a fully automated chess YouTube channel with an AI Agent, combining LLMs and chess engines to auto-generate explainer videos nightly, reaching 500K views. Here's the tech architecture, tool design, and real costs.
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·4 min
AI Agents Powering the Full Research Pipeline: A Practical Guide to Automation from Topic Selection to Publication
Learn how to use AI Agents to link the entire research pipeline—from literature management, data analysis, and paper writing to scientific illustration and dissemination—building a reusable research automation workflow with NotebookLM, N8N, and Ollama.
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Local Coding Agents in Practice: A Com…
·6 min
Local Coding Agents in Practice: A Complete Guide to Replacing Your Claude Subscription with Open-Source Models
An in-depth look at local coding agents—core concepts, advantages, and real challenges. Compare against Claude Code and learn to build a zero-subscription, private AI coding workflow with open-weight models.
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·6 min
Zuckerberg Admits AI Progress Falls Short of Expectations: The Industry Truth Behind the Layoffs
Meta laid off 8,000 to bet on AI, yet Zuckerberg admits AI agents fell short of expectations. A look at the collective 'AI reflection' among OpenAI, Microsoft, and Google, plus research on AI's selective impact on jobs.
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·6 min
GPT-5.6 Sol Limited Preview: The Safety Boundaries Behind AI's Capability Expansion
OpenAI's flagship GPT-5.6 advances on three fronts—Sol, Kara, Luna tiered rollout; ByteDance CGN 5.0 Pro and Meta Muse push image generation toward controllable workflows; AI coding agents expose new supply chain risks.
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·3 min
ComfyUI-INT4-Fast: Running Flux Models Smoothly on 6GB GPUs
ComfyUI-INT4-Fast brings W4A4 quantized inference to ComfyUI. RTX 3060 (6GB VRAM) generates 1024×1024 images in 17s. Per-layer mixed-precision routing balances speed and quality for Flux models.
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·2 min
GPT-5.6 Official Launch: What's the Difference Between the Sun, Earth, and Moon Versions?
OpenAI officially launches GPT-5.6 with three celestial-named versions: Sun, Earth, and Moon. Learn what sets them apart, the rollout schedule, and what to expect.
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·5 min
Ollama Raises $65M Series B: 85% of Fortune 500 Have Already Deployed Local LLMs
Local LLM tool Ollama closes a $65M Series B, bringing total funding to $88M. With 9M developers and 85% of Fortune 500 having deployed internally, this deep dive explores why enterprises embrace local LLMs: compliance, Agent cost savings, and open-source ecosystem.
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·7 min
50 AI Research Job Applications to FAANG, 0 Replies? Unpacking the Truth Behind the Job Search Struggle
An AI research engineer with 3 years of experience sent 50 applications to FAANG with zero replies. This article breaks down the hidden barriers of top-tech AI roles, the truth about LinkedIn ghost jobs, and the MLE vs. Research Engineer divide.
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·5 min
Real-World Comparison of 6 Open-Source LLMs for On-Premise Deployment: A Selection Guide to Avoid Pitfalls
A hands-on comparison of 6 open-source LLMs (DeepSeek, Qwen3, Zhipu GLM, Kimi K2, MiniMax M3, Tencent Hunyuan 3) for on-premise deployment—covering hardware cost, inference efficiency, and deployment difficulty.
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·6 min
Tencent Hunyuan HY3 Official Version Open-Sourced: The Strongest Under 300B, at 1 Yuan per Million Tokens
Tencent Hunyuan HY3 official version is open-sourced under Apache 2.0, priced as low as 1 yuan per million input tokens, with major gains in agents, reasoning, coding, and long context. On the same day, Meituan open-sourced its trillion-parameter LongCat 2.0.
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