MLX

MLX is a new open source technology from Apple that makes it possible to run powerful AI models (Large Language Models, LLMs for short) directly and locally on Apple Silicon Macs - without an internet connection or cloud constraints. MLX stands for maximum control, data protection and independence: users load a model onto their Mac and can use it offline - e.g. for texts, analyses or creative tasks. MLX is a significant step towards sovereign, locally usable artificial intelligence.

AI Studio 2025: Which hardware is really worth it - from the Mac Studio to the RTX 3090

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Hardware 2025 for AI studio

Anyone working with AI today is almost automatically pushed into the cloud: OpenAI, Microsoft, Google, any web UIs, tokens, limits, terms and conditions. This seems modern - but is essentially a return to dependency: others determine which models you can use, how often, with which filters and at what cost. I'm deliberately going the other way: I'm currently building my own little AI studio at home. With my own hardware, my own models and my own workflows.

My goal is clear: local text AI, local image AI, learning my own models (LoRA, fine-tuning) and all of this in such a way that I, as a freelancer and later also an SME customer, am not dependent on the daily whims of some cloud provider. You could say it's a return to an old attitude that used to be quite normal: „You do important things yourself“. Only this time, it's not about your own workbench, but about computing power and data sovereignty.

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Apple MLX vs. NVIDIA: How local AI inference works on the Mac

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Local AI on Silicon with Apple Mac

Anyone working with artificial intelligence today often first thinks of ChatGPT or similar online services. You type in a question, wait a few seconds - and receive an answer as if a very well-read, patient conversation partner were sitting at the other end of the line. But what is easily forgotten: Every input, every sentence, every word travels via the Internet to external servers. That's where the real work is done - on huge computers that you never get to see yourself.

In principle, a local language model works in exactly the same way - but without the Internet. The model is stored as a file on the user's own computer, is loaded into the working memory at startup and answers questions directly on the device. The technology behind it is the same: a neural network that understands language, generates texts and recognizes patterns. The only difference is that the entire calculation remains in-house. You could say: ChatGPT without the cloud.

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LoRA training: How FileMaker 2025 simplifies the fine-tuning of large language models

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LoRA Fine tuning - FileMaker 2025

The world of artificial intelligence is on the move. New models, new methods and, above all, new possibilities are emerging on an almost weekly basis - and yet one thing remains constant: not every technical innovation automatically leads to a better everyday life. Many things remain experimental, complex or simply too costly for productive use. This is particularly evident in the so-called fine-tuning of large language models - a method of specializing generative AI to its own content, terms and tonalities.

I have accompanied this process intensively over the last few months - first in the classic form, with Python, terminal, error messages and nerve-wracking setup loops. And then: with FileMaker 2025. A step that surprised me - because it wasn't loud, but clear. And because it showed that there is another way.

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Artificial intelligence: which jobs are at risk and how we can arm ourselves now.

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Which jobs will be eliminated by AI in the future

Hardly any other technological change has crept into our everyday lives as quickly as artificial intelligence. What was considered a visionary technology of the future yesterday is already a reality today - whether in texting, programming, diagnosing, translating or even creating music, art or legal briefs.

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Integration of MLX in FileMaker 2025: Local AI as the new standard

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Local AI with MLX and FileMaker

While MLX originally started as an experimental framework from Apple Research, a quiet but significant development has taken place in recent months: With the release of FileMaker 2025, Claris has firmly integrated MLX into the server as a native AI infrastructure for Apple Silicon. This means that anyone working with a Mac and relying on Apple Silicon can not only run MLX models locally, but also use them directly in FileMaker - with native functions, without any intermediate layers.

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MLX on Apple Silicon as local AI in comparison with Ollama & Co.

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Local AI on the Mac with MLX

At a time when centralized AI services such as ChatGPT, Claude or Gemini are dominating the headlines, many professional users are increasingly looking for an alternative - a local, self-controllable AI infrastructure. Especially for creative processes, sensitive data or recurring workflows, a local solution is often the more sustainable and secure option.

Anyone working with a Mac - especially with Apple Silicon (M1, M2, M3 or M4) - can now find amazingly powerful tools to run their own language models directly on the device. At the center of this is a new, largely unknown component: MLX, a machine learning framework developed by Apple that is likely to play an increasingly central role in the company's AI ecosystem in the coming years.

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