#mixed precision training
105 related articles
·3 min
AMD CDNA5 Architecture Deep Dive: Technical Evolution and the AI Computing Competition Landscape
Deep analysis of AMD's CDNA5 architecture covering Chiplet packaging upgrades, HBM memory evolution, and low-precision compute optimization, examining how AMD challenges NVIDIA's AI chip dominance.
Read more →
·3 min
AI Not Performing Well? Start by Getting These Simple but Often Overlooked Things Right
When your AI system underperforms, the problem is often not the model or algorithm — it's basic work like data cleaning, prompt writing, and evaluation that hasn't been done right.
Read more →
·3 min
AI Not Working Well? Start by Getting These Simple but Often Overlooked Things Right
When AI systems underperform, the problem often isn't the model or algorithm — it's that basics like data cleaning, prompt writing, and evaluation aren't done right. Learn the simple fixes that matter most.
Read more →
·3 min
DeepSeek-OCR Deployment & Fine-Tuning in Practice: From vLLM Inference to Unsloth Fine-Tuning
Complete guide to DeepSeek-OCR from vLLM inference deployment and Unsloth model loading to fine-tuning, covering cloud server setup, GPU selection, and code examples — all on a single 4090 GPU.
Read more →
·3 min
Ideogram 4.0 Turbo Workflow: An AI Image Generation Solution Balancing Speed and Quality
Detailed look at the Ideogram 4.0 mixed turbo workflow: RTX 4090 inference in just 15 seconds, rivaling Krea2 speed, with stable output up to 8K resolution.
Read more →
·3 min
Ideogram 4.0 Turbo Workflow: An AI Image Generation Solution Balancing Speed and Quality
Detailed look at the Ideogram 4.0 mixed turbo workflow: RTX 4090 tested at just 15s inference, matching Krea2 speed with up to 8K resolution output.
Read more →
·4 min
Robot Valet Parking at Gatwick Airport: How the AGV Automated Parking System Works
London Gatwick launches UK's first robot valet parking using AGV technology, boosting parking capacity by 30-60%. Learn how the system works, its challenges, and the business case for automated parking.
Read more →
·6 min
AI Application Engineer Interview Guide: Core Topics in Model Quantization and Inference Deployment
A systematic review of must-know topics for AI Application Engineer interviews: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
Read more →
·6 min
AI Application Engineer Interview Guide: Core Topics on Model Quantization and Inference Deployment
A systematic guide to must-know AI application engineer interview topics: PTQ/QAT quantization, operator fusion, inference pipelines, latency/throughput analysis, and edge deployment of detection/segmentation/BEV models.
Read more →
·7 min
Context Engineering: A Systematic Approach to Stop AI Agents from 'Talking Nonsense'
Context engineering is the core methodology for building efficient AI Agents, covering query enhancement, RAG retrieval, prompt design, memory management, and tool invocation. Master Write, Select, Compress, and Isolate to solve LLM hallucination at its root.
Read more →
·4 min
Qwen-Image 3.0 Released: Image Generation Moves Toward Production-Ready Design
Qwen-Image 3.0 supports 4.5K token instructions, 10px text rendering, and 12-language typography for production-ready posters and infographics. Plus: Anthropic settlement, Grok in Excel, Tencent HRAP 1.0.
Read more →
·4 min
The Rise of Chinese Open-Source AI Models: A Head-On Challenge to Closed-Source Dominance
Chinese open-source models rapidly close the capability gap with top closed-source AI. DeepSeek shocks the industry while Qwen matches global benchmarks.
Read more →
·3 min
V100 GPU Showdown: 4×16G PCIe vs. 2×32G SXM — Which Gives You More Bang for Your Buck?
Benchmarking 4×V100 16G PCIe vs. 2×V100 32G SXM adapter for local LLM inference. Prefill speed, decode speed, power limits, and bandwidth bottlenecks analyzed.
Read more →
·3 min
Qwen's Six-Generation Evolution: A Complete Breakdown from Architecture Innovations to the Reasoning Race
From Qwen1 to Qwen3-2507: a complete breakdown of six generations of evolution over two years — GQA, MoE, GRPO, dynamic thinking, and the core shift from architecture to reasoning.
Read more →
·3 min
Ornith 9B/35B Hands-On: A New Local Deployment Option for Code Agents
Ornith 1.0 by Deep Reinforce reinforces Qwen 3.5 for code agents. We test Ornith 9B & 35B MoE on Chinese writing, logic, and invoice OCR, with full llama.cpp deployment guide.
Read more →
·3 min
Running a 27B Model on iPhone: How 1-bit Quantization Achieves Extreme Compression
PrismML's Bonsai compresses a 27B model from 54GB to 3.9GB, running at ~11 tokens/sec on iPhone. A deep dive into QAT, knowledge distillation, and speculative decoding.
Read more →
·7 min
Claude Code Practical Tutorial: A Complete Beginner's Guide to Automating Your Entire Workflow
No coding required! This guide breaks down the complete Claude workflow: custom Projects, batch SEO content, one-sentence tool building with Artifacts, and Claude Code terminal ops—with real traffic-growth cases.
Read more →
·3 min
Open-Source LLM Surge: K3 and V4 Drop Together as the Marginal Cost of Intelligence Approaches Zero
Kimi K3, DeepSeek V4, Liquid, and Mistral are all dropping at once. MXFP4 quantization and MoE architecture are pushing the marginal cost of intelligence toward zero. Here's what it means.
Read more →
Bonsai 27B: The First 1-bit LLM That R…
·3 min
Bonsai 27B: The First 1-bit LLM That Runs on Your Phone — A New Milestone for On-Device AI
Bonsai 27B is the first 27B-parameter LLM that runs on smartphones via 1-bit quantization, compressing to 3–4GB. We break down the tech, privacy benefits, and community debate.
Read more →
·2 min
Running Qwen 122B on 8GB VRAM: A Complete Guide to Quantized Local Deployment
A Bilibili creator ran Qwen 122B with 256K context on just 8GB VRAM + 64GB RAM using llama.cpp. Full breakdown of quantization, deployment params, performance, and cost-effective alternatives.
Read more →