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Glossary

Open source and open weights

Open source means the blueprint of software is public and you may use it freely. With an open AI model, the weights, the numbers in which it stores its knowledge, can be downloaded.

With open source, the source code of software is public, and anyone may use, inspect and modify it under certain conditions. Those conditions are set out in a licence. With AI models you mostly come across the term open weights. The weights, or parameters, are the numbers in which a model stores everything it has learned. If they can be downloaded, you can run the model on your own computer.

It is like a recipe that a restaurant shares: with the weights you have the finished dish and can cook with it. With all the sources as well, such as the training data and the training code, you could rebuild the whole recipe yourself.

How does it work?

Open is a spectrum. Some makers share only the weights, others also the code to run or train the model. A licence usually comes with it that determines what is allowed. The large DeepSeek model, for instance, is under the permissive MIT licence, which means anyone may download and use it for free. Nvidia's OpenShell, software that shields AI agents, falls under the Apache 2.0 licence.

What is called open is not always available everywhere. The Chinese tech company Baidu, for example, released a large model that developers can train further themselves, but its licence does not apply in the EU, the United Kingdom and South Korea (link).

Why it matters

Open models can be checked, improved and run on your own hardware by anyone. The company Unsloth, for instance, made a heavily shrunken version of the open DeepSeek model that runs on a powerful laptop or mini computer with 128 gigabytes of memory, although that costs some accuracy (link). The blueprint for shielding agents is open too: Nvidia offers the software for free, so that anyone can use it (link).

For researchers and small companies, that makes the difference: they do not have to depend on the servers of a few large companies, and they can build on what others have already done.

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