The future of AI models may see a balance between open-source and closed-source, with predictions suggesting a 50/50 split in inference token usage over the next five years.

This year has been positive for open-source AI, with many innovative models emerging, and there's a prediction that open-source will surpass closed-source models in usage.

Open-source AI models, like those released by Deepseek, are closing the gap with proprietary models, and Google has also released competitive open-source models.

Open source AI development is progressing faster than proprietary models, as it allows for a diverse range of ideas and contributions from around the world.

The transparency and high leverage of open-source models will lead future generations to prefer creating open-source solutions over closed-source ones, as they grow up learning about state-of-the-art machine learning.

Open source models are essential for ensuring that AI achieves its full economic potential, as they allow for broader access and innovation in AI technologies.

Just because a model is open-sourced doesn't mean it can't be subverted; there have been instances of backdoors in open source software that could also apply to AI models.

The future of AI relies on open-source models to ensure freedom and prevent centralization of power in AI development.

Decentralized inference providers gained traction as they offered models that met market demand, resulting in a rapid increase in interest that many in the AI space are still unaware of.