open source licenses

Microsoft recently seemed to propose that Open Source software didn’t belong in the Windows app store. Excuse me? After the news broke, Giorgio Sardo, Microsoft’s General Manager of the Microsoft Store, argued on Twitter that it wasn’t Microsoft’s intent. “We absolutely want to support developers distributing successful OSS apps. In fact, there are already fantastic OSS apps in the Store! The goal of this policy is to protect customers from misleading listings.” Predictably, confusion results. And the kerfuffle over FairEmail and the Google Play Store earlier this year is a good example of how this sort of confusion is not entirely new, leading to questions about intent. I’ve talked with developers and business managers about their experience in preparing software packages for commercial app stores. Universally, everyone reports having issues with app stores’ packaging. These include...

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In a revival and expansion of the principles that drove the first generation of community-led open source commercial players, creators are now coming together in a new form of collaboration. Rather than withholding software under a different license, they're partnering with each other to provide the same kinds of professional assurances that companies such as Red Hat discovered were necessary back in the day, but for the thousands of discrete components that make up the modern development platform. Today's generation of entrepreneurial open source creators is leaving behind the scarcity mindset that bore open core and its brethren. Instead, they're advancing an optimistic, additive, and still practical model that adds missing commercial value on top of raw open source.

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Machine learning has been around for a long time. But in late 2022, recent advancements in deep learning and large language models started to change the game and come into the public eye. And people started thinking, “We love Open Source software, so, let’s have Open Source AI, too.” But what is Open Source AI? And the answer is: we don’t know yet. Machine learning models are not software. Software is written by humans, like me. Machine learning models are trained; they learn on their own automatically, based on the input data provided by humans. When programmers want to fix a computer program, they know what they need: the source code. But if you want to fix a model, you need a lot more: software to train it, data to train it, a plan for training it, and so forth. It is much more complex. And reproducing it exactly ranges from difficult to nearly impossible.

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