#GPU selection guide
147 related articles
·3 min
Cherry Studio + MCP + Ollama: The Complete Guide to Building a Local AI Agent and Private Knowledge Base
A hands-on guide to building a local AI agent and private knowledge base using Cherry Studio, MCP, and Ollama — with web scraping, report generation, and terminal control.
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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
Two Paths to Better AI Reasoning: Test-Time Scaling and Formal Verification
This article synthesizes two MSR India Summit talks, exploring two key paths to better AI reasoning: test-time scaling with variable granularity search, and a formal verification framework for trustworthy agent execution.
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JAX Host Offloading: A Practical Guide…
·2 min
JAX Host Offloading: A Practical Guide to Breaking Through LLM Training Memory Bottlenecks
Memory capacity is the core bottleneck in LLM training. This guide explores JAX-based host offloading — covering optimizer state offloading, activation strategies, PCIe bandwidth trade-offs, and how it complements activation recomputation.
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·3 min
Local Gemma 3 12B as an AI Agent: A Practical Guide to Tool Calling and Framework Selection
Running Gemma 3 12B locally via Ollama and want to build an AI Agent? This guide covers tool calling, n8n/LangChain/CrewAI comparisons, context limits, and more.
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·2 min
Reproducing GitHub Projects from Scratch: A Complete Guide to Environment Setup and Practical Pitfall Avoidance
Reproducing GitHub projects isn't just git clone. This guide covers project evaluation, conda setup, dependency installation, running .sh scripts on Windows, and debugging tips.
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·4 min
A Deep Dive into Claude Cookbooks: A Guide to the Official 47K-Star Hands-On Code Repository
Anthropic's open-source Claude Cookbooks project offers runnable Jupyter Notebook examples covering RAG, Tool Use, multimodal processing, and more—helping developers master Claude API best practices.
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·3 min
30 Cents vs $27: Open-Source Models Face Off in Coding, With DeepSeek Leading at 100x Cost-Efficiency
A hands-on comparison of AI models—Fable 5, DeepSeek V4 Flash, GLM 5.2, Qwen 3.6—building a sales CRM. The priciest cost $27.69, the cheapest just 30 cents. A deep dive into open-source LLM coding value.
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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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·4 min
E2AM: An Open-Source Tool to Quantify AI Training Energy Consumption and Carbon Emissions in Two Lines of Code
E2AM is a Green AI open-source tool that monitors AI model training energy use, carbon emissions, and accuracy-per-joule metrics in just two lines of code. Supports PyTorch and Hugging Face, runs locally with no server needed.
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·5 min
Advanced Machine Learning Reading List: How to Choose the Right Book Among These 4 Classics?
Torn between Géron, Chollet, and Raschka? This article breaks down 4 classic ML books for self-learners aiming at finetuning and small language models (SLM), helping you find the best advanced path.
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·5 min
Building DeepSeek Agents and Knowledge Bases from Scratch: A Practical Guide to Commercial Deployment
A systematic guide to the full DeepSeek Agent development process: covering prompt engineering, the ReAct framework, workflow orchestration, local deployment, and business requirement breakdown for commercial-ready AI Agents.
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·4 min
ChatGLM Large Model Development Tutorial: From Zero to Enterprise Deployment
Systematically learn ChatGLM large model development, covering Transformer principles, RAG, private deployment, fine-tuning, and Agent development, with a roadmap and hands-on cases.
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·5 min
Krea 2 Turbo Style Reference LoRA: Define Your Generation Style with a Single Image
ostris releases the Krea 2 Turbo Style Reference LoRA, supporting single or multi-image style extraction for precise AI style transfer. Open-source, free, and locally deployable.
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·6 min
Getting Started with AI Agents: Principles, Frameworks, and a Guide to Building Enterprise-Grade Agents
In-depth analysis of AI Agent core principles: why LLMs need Agent technology, the evolution from Prompt to RAG to Agent, Agent Tuning methods, and enterprise cost evaluation to help you build enterprise-grade agent applications.
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·3 min
The Complete AI Agent Development Workflow: A Seven-Step Guide from Requirements Analysis to Deployment
Want to build an AI Agent but don't know where to start? This guide covers the complete seven-step workflow—from requirements analysis, platform selection, prompt engineering, data storage, and UI building to testing and deployment.
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·6 min
Grok 4.5 Coding Benchmark: A Deep Dive into Performance, Speed, and Cost
xAI releases Grok 4.5, purpose-built for coding agents. 80 TPS speed, $2/M input tokens, SWE Bench Pro score of 64.7, and 4.2x better token efficiency than Opus 4.8. A deep hands-on review.
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·5 min
Practical Guide to Deploying Invoice Analysis AI: Model Selection and Architecture Pitfalls
How can enterprises process 50+ invoice formats with AI? This article analyzes visual document understanding approaches—multimodal LLMs, OCR+LLM, and hybrid architecture—with key decision advice for non-technical AI leads.
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·8 min
GPT-5.6 Hands-On: Farm Automation, Mathematical Breakthroughs, and End-to-End AI Execution
GPT-5.6 (Sol, Terra, Luna) hands-on testing: a Hokkaido farmer controls a greenhouse with AI, a NYC small business builds custom software, and a Polish mathematician breaks a 3-year problem. A deep dive into end-to-end autonomous execution.
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·2 min
GPT-5.6 Three-Model Showdown: A Complete Breakdown of So, Terra, and Luna
OpenAI's GPT-5.6 preview introduces So, Terra, and Luna. All three score perfect marks on long-horizon agentic tasks, with Terra priced 50% below GPT-5.5.
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