Open source models offer a compelling proposition of distributing the value created by AI more broadly, creating more winners, and enabling more people to build. After the last two months, I’m less convinced it’s that easy. As I worked with the open source model ecosystem, every fix revealed a new bug, each covered up by many layers of abstraction. There’s debt hidden in every layer of the stack, and with open source ML infra, the stack is deep.
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We explored standard advanced algorithms like Contraction Hierarchies (CH), known for their speed. But they presented their own set of deal-breakers for OsmAnd: