#Wan 2.2 i2v
32 related articles
·2 min
Krea 2 Turbo + Wan 2.2: A Detailed Workflow for Turning Static Images into Dynamic AI Videos
A detailed guide on using Krea 2 Turbo for high-quality static images and Wan 2.2 i2v to add dynamic motion—covering technical principles, key steps, and practical tips.
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·4 min
Can AI Deliver a Real "LK-99 Moment"?
From the LK-99 room-temperature superconductor frenzy to AI-driven scientific discovery — exploring how AI can accelerate the next major breakthrough through materials screening, hypothesis generation, and closed-loop experimentation.
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·2 min
Wizstar: An AI Tool That Makes Digital Avatars Perform Like Professional Actors
Wizstar is an AI digital avatar tool with natural gestures, object interaction, and complex-scene lip sync, enabling creators and brands to produce multilingual video content at scale.
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·2 min
HTML-in-Canvas API: Rendering Real, Interactive HTML Inside Canvas
Explore how the HTML-in-Canvas API renders real, interactive HTML inside Canvas, supporting WebGL/WebGPU effects while preserving accessibility and native browser capabilities.
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·2 min
Macrobite: Snap a Photo to Calculate Nutrition, Making Macro Tracking Effortless
Macrobite is an AI-powered nutrition tracking app that identifies food nutrients from photos, supports voice logging and Apple Watch integration, making macro tracking fast and simple.
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·2 min
Wan2.2 LoRA Fine-Tuning in Practice: A Complete Guide from Principles to Effect Optimization
A detailed guide to Wan2.2 video model LoRA fine-tuning: working principles, common failure causes, and solutions covering weight settings, trigger words, version compatibility, and optimization tips.
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·2 min
OpenNutriTracker In-Depth Review: Can Open-Source Nutrition Tracking Replace MyFitnessPal?
In-depth analysis of open-source nutrition tracker OpenNutriTracker — covering database coverage, barcode scanning reliability, and privacy — to help you decide if it's worth switching from MyFitnessPal.
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·4 min
Colibri: Running a 744-Billion-Parameter LLM on an Ordinary Laptop
Colibri uses MoE hot-cold separation and 4-bit quantization to run 744B-parameter models like GLM 5.2 on consumer hardware. Learn about its three-tier memory architecture and speculative decoding.
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·3 min
What Happens After You Click a Link? A Complete Technical Breakdown
From DNS resolution, TCP handshake, and TLS encryption to the Blink rendering engine — a detailed breakdown of what happens after you click a link.
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·3 min
Building a YOLO26 Inference Engine from Scratch in ARM64 Assembly: A Deep Dive into Low-Level Optimization
Deep dive into building a YOLO26n object detection inference engine from scratch using ARM64 assembly and C, covering NEON SIMD, Winograd convolution, GEMM micro-kernels, and cache tiling optimizations.
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·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.
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·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.
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·7 min
The Complete AI Character LoRA Training Workflow: Hands-On Multi-Character Consistency Generation with Local Deployment
A detailed guide to a complete local AI character generation workflow: from the five golden rules of LoRA training and automated ComfyUI dataset construction to hands-on comparisons of Crea2, Ideogram4, and Wan for multi-character same-frame interaction—all running free on personal hardware.
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·6 min
OpenAI vs Anthropic IPO Race: Who's Really Burning Cash? A Deep Dive Into AI Giants' Finances
OpenAI's adjusted operating margin hits -122%, Anthropic's profitability remains murky, and SpaceX claims a $22.7T AI market. A deep dive into three AI giants' real financials and the capital game behind the IPO race.
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·3 min
Claude Code Enterprise Guide: Environment Setup, Git Workflows, and Switching to Chinese AI Models
Enterprise guide to Claude Code: CLI setup, switching to DeepSeek and other Chinese AI models, Git workflow automation, and bug fix loops to boost team productivity.
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·2 min
Forge: Adding Reliability Guardrails to Local Model Tool Calling
Forge is an open-source Python middleware for local models (Ollama, llama.cpp, vLLM) that boosts tool-calling reliability via three-layer guardrails: validation, rescue parsing, and retry.
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·2 min
The Complete Optimization Guide for Local AI Image & Video Generation with 16GB VRAM
What can 16GB VRAM do? This guide covers FLUX, SDXL, Wan video models, ComfyUI workflows, GGUF quantization, and VRAM optimization to max out your RTX 16GB GPU.
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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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·4 min
AMD Ryzen AI Halo Hands-On: Can x86 Architecture Challenge NVIDIA's DGX Spark?
In-depth review of the AMD Ryzen AI Halo mini AI box: powered by the Ryzen AI Max Plus 395 (Strix Halo) chip with 128GB unified memory, priced at $4,000. Compared against NVIDIA's DGX Spark across token generation, prefill speed, and x86 advantages.
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·6 min
GPT-5.6 Hands-On Deep Dive: ChatGPT and Codex Merge, Full Analysis of the Sol Model
GPT-5.6 is officially released, merging ChatGPT and Codex into one app and launching the three-tier Sol, Terra, and Luna models. A detailed breakdown of 16 hands-on tests plus Worker mode and Codex dev upgrades.
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