My view is that post training and open models are turning AI from a centralized product into a distributed ecosystem
The AI story is changing, and it is happening faster than most people expected. For the last few years, the narrative was simple. The biggest companies with the most compute, the most data, and the largest models controlled the direction of AI. That created a kind of gravitational pull around a handful of giants who defined what was possible and how quickly it could scale. But that model is starting to break.
The shift is not coming from bigger models alone. It is coming from what happens after the model is built. Post training has quietly become the most important battleground in AI. This is where models are refined, aligned, and tuned with specific data for real world tasks. And this is where smaller players now have an opening.
Instead of building everything from scratch, startups and researchers can take strong base models and adapt them for very specific use cases. That changes the economics completely. You no longer need billions in compute to compete at the application layer. You need smart data, targeted training, and a clear use case.
This is what is driving the rise of open source models.
Over the past year, open models have improved rapidly. They are becoming more capable, more efficient, and easier to customize. That means developers are no longer locked into a single provider. They can choose a model, fine tune it, and deploy it in a way that fits their exact needs. This is the real disruption. The power of AI is moving from a centralized system controlled by a few companies into a more distributed network of builders. Open models create a shared foundation that anyone can build on. That lowers barriers and increases competition. And once competition increases, innovation accelerates. We are already seeing this play out. Startups are building specialized AI tools for industries like healthcare, finance, education, and manufacturing using open foundations. Researchers are pushing forward new techniques without waiting for access to closed systems. Even large companies are starting to blend open and proprietary models to stay flexible. This is not the end of big AI companies. They still have massive advantages in scale, infrastructure, and integration. But their control is no longer absolute. The ecosystem is expanding around them.
My view is that this is where things get interesting.
The next wave of AI will not be defined by one dominant model or one dominant company. It will be defined by thousands of smaller, more focused systems built on top of shared foundations. That is how most major technologies evolve over time. They start centralized, then fragment into ecosystems.
AI is now entering that phase. The biggest breakthrough is not just smarter models. It is the ability to adapt them quickly, cheaply, and at scale. That is what open source enables. It turns AI from a product you consume into a system you can shape. The monopoly was always going to be temporary. The real future of AI looks more like the internet itself. Open, distributed, and constantly evolving.