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Category: AI/ML & vGPU

vAndu Think Like an Engineer, or Stay Confused About AI

Think Like an Engineer, or Stay Confused About AI

Posted on June 17, 2026June 17, 2026

The current AI moment looks like chaos from the outside. From the inside, it’s just a product development cycle: raw, messy, and completely normal. To understand what’s actually happening in AI right now, you have to stop watching it like a consumer or an investor and start thinking like an engineer. What the rest of…

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AI Will Not Break Security. It Will Reveal It.

Posted on June 12, 2026June 19, 2026

The coming years will be some of the most interesting in cybersecurity history. Two trends are on a collision course: Attackers are adopting AI to find and exploit vulnerabilities at a speed and scale we have not seen before. Meanwhile, many companies are racing to deploy AI in their products and systems, often without taking…

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10 AnythingLLM Quick Setup Guide

10 AnythingLLM Quick Setup Guide

Posted on June 8, 2026June 8, 2026

Short description AnythingLLM is a full local AI application, not just a chat box. In one tool it gives you chat with your models, document RAG, and AI agents that can take actions, and it can serve a whole team rather than a single person. Purpose and how people use it People reach for AnythingLLM…

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Ollama Quick Setup Guide

01 Ollama Quick Setup Guide

Posted on June 8, 2026June 8, 2026

Short description Ollama is a local model runner. It downloads open weight LLMs and serves them through a simple local API at port 11434. Purpose and how people use it Ollama is the engine layer of a local AI stack. People use it to run models like Llama, Mistral, Qwen, and Nemotron on their own…

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Part 0b: Setting Up a Ubuntu Server (Docker and Essentials)

Part 0b: Setting Up a Ubuntu Server (Docker and Essentials)

Posted on June 3, 2026June 8, 2026

Part 0b: Setting Up a Ubuntu Server (Docker and Essentials) Who this is for This guide gets a fresh Ubuntu server ready to run the stack. This is the path for a home server, a spare machine, or a cloud server, rather than a Windows desktop. After this you can follow any tool guide in…

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09 locust quick setup

09 Locust Quick Setup Guide

Posted on June 3, 2026June 3, 2026

Short description Locust is a load testing tool. You describe simulated users in a small Python file, then watch how your service behaves as concurrency rises. Purpose and how people use it People use Locust to find where a service slows down or breaks under load. For an AI stack it answers a specific question:…

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08 dify quick setup

08 Dify Quick Setup Guide

Posted on June 3, 2026June 3, 2026

Short description Dify is an all in one platform to build, run, and publish LLM apps. It covers chatbots, agents, visual workflows, and RAG knowledge bases, then lets you publish any of them as a web app or an API. Purpose and how people use it People use Dify to go from idea to a…

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07 langfuse quick setup

07 Langfuse Quick Setup Guide

Posted on June 3, 2026June 3, 2026

Short description Langfuse is observability and tracing for LLM applications. It records every call, prompt, response, latency, and cost so you can see what your stack is actually doing. Purpose and how people use it People use Langfuse to debug and improve LLM apps. When an agent gives a strange answer, the trace shows the…

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06 litellm quick setup

06 LiteLLM Quick Setup Guide

Posted on June 3, 2026June 3, 2026

Short description LiteLLM is a gateway that puts every model, local or cloud, behind one OpenAI compatible API. It adds virtual keys, usage logging, and a control plane UI. Purpose and how people use it People use LiteLLM to stop juggling different SDKs and keys for different providers. Every app points at LiteLLM, and LiteLLM…

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05 langflow quick setup

05 Langflow Quick Setup Guide

Posted on June 3, 2026June 3, 2026

Short description Langflow is a visual flow builder for LLM pipelines and agents, similar in spirit to Flowise but with its own node set and feel. Purpose and how people use it People use Langflow to design RAG flows, agents, and prompt pipelines visually, test them in a built in playground, and export them as…

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