#vector quantization
243 related articles
·3 min
Ollama + Qwen-Agent: Building a Local Private AI Assistant — From Deployment to Security Best Practices
A complete guide to building a local private AI assistant with Ollama and Qwen-Agent. Covers RAG knowledge integration, voice interaction, and permission isolation for a secure local AI Agent architecture.
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·4 min
Heretic Uncensoring Technology Explained: Practical Applications on Jamba2 and Qwen3.5 Open-Source Models
Deep dive into Heretic uncensoring technology applied to Jamba2-Mini, Qwen3.5-9B, and 27B open-source models, exploring how refusal rates dropped from 97% to 4% and the safety debates involved.
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·5 min
Have AI Doomers Actually Used AI? A Developer Exposes the Gap Between Hype and Reality
AI Doomers warn AI will destroy humanity, but have they actually built AI apps? A developer's sharp critique reveals the vast gap between AI demos and real engineering practice.
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·1 min
Predictive KV Replication: Breaking Through the Bursty Traffic Bottleneck in LLM Inference
Deep dive into predictive speculative KV replication: how anticipating bursty traffic and pre-replicating KV Cache can reduce LLM inference tail latency.
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·3 min
AI Costs Out of Control: Inference Expenses Skyrocketing—Who's Footing the Bill?
An in-depth analysis of why AI costs keep rising—inference expenses, premium model pricing, and context bloat—plus practical optimization strategies including model cascading, caching, and self-hosting.
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·3 min
Gemini Robotics 2 Explained: Full-Body Control, Multi-Robot Coordination, and On-Device Deployment
Google DeepMind releases Gemini Robotics 2, achieving humanoid full-body control, multi-step error recovery, multi-robot coordination, and on-device deployment with built-in safety mechanisms.
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·3 min
Gemini Robotics 2 Explained: Full-Body Control, Multi-Robot Coordination, and On-Device Deployment
Google DeepMind releases Gemini Robotics 2, a robot foundation model enabling humanoid full-body control, multi-step error recovery, multi-robot coordination, and on-device deployment.
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·3 min
LLM Inference Speed Formula: Memory Bandwidth Determines Your tokens/sec
Why memory bandwidth (GB/s), not VRAM size, determines local LLM inference speed. Includes tokens/sec formula, GPU bandwidth comparison, and a practical card selection framework.
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·3 min
LLM Inference Speed Formula: Memory Bandwidth Determines Your tokens/sec
Learn why memory bandwidth (GB/s)—not VRAM size—determines local LLM inference speed. Get the tokens/sec formula, GPU bandwidth comparisons, and a practical card selection hierarchy.
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·2 min
Deploying an iMessage AI Assistant on Raspberry Pi: Building a Home-Resident Smart Agent
iMessage Hermes is an open-source project deploying AI agents on Raspberry Pi, enabling iMessage and SMS interaction via real phone numbers. A deep dive into its architecture and potential.
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·2 min
PlayingFild: A Smart Tab Management Chrome Extension Based on Page Content
PlayingFild is a Chrome extension that uses on-device ML to intelligently classify tabs by page content, separating work from leisure with focus timers, idle tab cleanup, and productivity analytics.
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·3 min
Gemini Pro Job Search Quality Plummets: Model Degradation or Backend Adjustment?
Reddit users report Gemini Pro job search quality dropping drastically in one week, returning expired listings and aggregator junk instead of quality active positions with direct employer links.
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·3 min
Local LLM Agent Lagging? Lowering num_gpu Is the Key
Local LLM crashing in Agent frameworks? The issue may be num_gpu set too high. Learn what num_gpu really controls (GPU layer offloading, not GPU count) and how to tune it for stable Agent performance.
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·3 min
What Are AI Model Weights, Really? The Deep Learning Truth Revealed by a Meme
Starting from a viral Reddit meme, we dive deep into AI neural network weights — what they are, why they can't be read visually, and how open weights drive technological democratization.
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·2 min
ComfyUI KREA 2 v1.2 Identity Edit Workflow: A Practical Guide to Low-VRAM Identity-Preserving Editing
A detailed guide to ComfyUI KREA 2 Identity Edit v1.2 workflow installation and usage, supporting low-VRAM GPUs for identity-preserving editing including pose changes, style transfer, face swap, and virtual try-on.
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·4 min
Project Rai-chan Technical Breakdown: A Complete Guide to Building a Fully Local AI Companion
Deep dive into Project Rai-chan's tech stack: Ollama+Gemma local LLM, Unity rendering, VOICEVOX speech synthesis, and more — exploring the technical path for local AI companions.
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·3 min
ncnn Vulkan Cross-Platform Edge Inference in Practice: Solving the GPU Fragmentation Deployment Challenge
Facing GPU fragmentation on edge devices, the PostSlate team used ncnn's Vulkan backend for cross-platform ML inference, achieving 10× speedup on RTX 4070 with half the model size and zero runtime installation.
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·3 min
Learning AI Large Language Models: A Complete Roadmap from Beginner to Practitioner
A systematic breakdown of the AI LLM learning roadmap covering prompt engineering, AI Agent development, RAG knowledge bases, model fine-tuning, and hands-on projects for beginners.
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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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·4 min
Getting Started with AI Agent Development: A Complete Guide from Concept to Practice
A comprehensive guide to AI Agent architecture and development, covering automated marketing, intelligent customer service, and investment analysis scenarios with single and multi-agent collaboration.
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