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AI@home: Classifying images with Ollama – part five: Places and more!
I am kind of still amazed how much information exists in mere 7 billion tokens in an ai model (my current preferred model, qwen2.5vl:7b). It is pretty good at understand what happens in an image, and it also is able to, all by itself, recognize places like the Corinth Canal, Eiffel Tower, the Kiomizu-Dera Temple…
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AI@home: Classifying images with Ollama – part four: Face recognizion
Most modern systems have some form of face recognizion. The one I use, digikam, also have face recognizion, but I wanted to see if I could do it myself. Besides, wouldn’t it be cool if my ollama-generated descriptions could say «Vegard And Anita on a mountain top» instead of just «A man and a woman…
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AI@home: Classifying images with Ollama – part three: A command-line app
Submitting jobs from the command line with RAW API calls works, but isn’t exactly user friendly in the long run. Getting the results, you might also want to use it for something. I decided I wanted XMP sidecar files that my digikam can understand. So, let’s get started! Architecture decisions As much as my decision…
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AI@home: Classifying images with Ollama – part two.
In my previous blog post, I created a basic API that would take a file as input, analyze it in ollama with a vision capable model and return the output. However, it had one major weakness: The HTTP call to the API would hang until the classifier job was finished. Especially classifying videos takes quite…
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AI@home: Classifying images with Ollama – part one.
After having tried deepseek a bit, I quickly decided it was more fun to dig a bit deeper. Deepseek looks like a solid tool for good results with not too much hardware resources, as opposed to what I am exploring in this article, classifying an image with a general purpose LLM. Nevertheless, it’s a fun…
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AI at home: Image and video classification with AI – deepstack
After having played with coding assistants for a while, I decided to let that theme rest for a while. But that doesn’t mean I need to stop with exploring usage for my self-hosted AI. One thing all of us have these days are an ever-growing library of pictures and videos. There exists quite a few…
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My self-hosted AI journey Part 2: Using Ollama as your coding assistant
One of the big use-cases for AI for developers today is coding-assistants. It basically serves as your assistant for useful suggestions, a sparring-partner, and occationally you can hand off larger tasks to it while you are taking a lunch break. Hiring human assistants means you can have them sign work contracts and confidentiality agreements –…
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Playing with AIs at home – beginning the journey
After having upgraded my home server, I found myself with an abundance of both CPU power and memory, both of which are meant to be used. After having given my other down-scaled components the memory and CPU they truly need, I decided to see what my new hardware could be used for. One of the…
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A hardware upgrade!
In short: In essence, I wanted to play with fun functionality instead of battling defects and too little resources. So, I went on a shopping hunt. And I found The Beelink GTI14 Ulta 9. I spec’ed it high, with 2*1TB m.2 SSD (I somewhat regret not going for lower (it was the max), and rather…
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Using Claude as Your Kubernetes Copilot: A Home Lab Journey
Editor’s Note: This blog post was written by Claude (Anthropic’s AI assistant) based on actual conversations and experiences with Vegard’s home lab Kubernetes cluster. All examples, troubleshooting sessions, and insights are from real interactions, but the narrative and analysis were composed by the AI to share these experiences with a broader audience. Over the past…