The real race in AI is no longer about who builds the most powerful model, but rather who turns the technology into a foundation upon which others can build. In a world where advanced capabilities are becoming rapidly accessible, competitive advantage is moving away from the model itself and focusing on what it enables: who can use it, extend it, integrate it into everyday work, and generate lasting value around it.
This is not a new story. In the history of technology, the long-term winners have rarely been those who built the most impressive autonomous tools. They are the ones who built systems around themselves. Apple won not only because of the iPhone, but also because of the App Store. Google didn’t create Android to sell an operating system, but to build an ecosystem of manufacturers, developers and services. AWS didn’t become dominant because of a single technology, but because it provided a platform that allowed thousands of businesses to grow on it.
The same change is now happening in AI. Isolation is no longer a gap. It became a constraint. Companies that try to keep all the value for themselves quickly discover that the world is changing faster than they are. Those who enable others to build, expand, share knowledge and implement solutions become the center of gravity of the market.
The few companies developing AI models and the infrastructure behind today’s most visible products face a fundamental choice. This choice is not technological, but conceptual. It’s a choice between maintaining total control or creating a force greater than themselves. Between keeping the model a secret and making it a foundation that others can build on.
Full control may seem appealing. Everything is tightly regulated, everything goes through one company. In reality, this approach slows progress. When a model is closed, each adaptation, extension or new idea depends on a single organization. The world is simply changing too quickly for this model to keep up.
An AI model can be considered a cake. In a closed approach, the company serves a cake. You can eat it, but the recipe stays in the kitchen. In an open approach, the company provides both the cake and the recipe. Others may prepare it themselves, modify it, add new ingredients and create results never expected. This is how ecosystems are formed. Innovation no longer comes from a single team or a single roadmap. It accumulates in all directions and becomes much greater than the sum of its parts.
This gap between closed and open approaches is widening today, as AI has entered a new stage. The question is no longer what can be demonstrated, but how AI works in real businesses on a daily basis. Cost, reliability, regulation, privacy, and reliance on a single vendor suddenly matter. At this point, the weaknesses of closed solutions become obvious. Every change becomes a negotiation and growth brings operational uncertainty.
Open models offer a more flexible path. They allow organizations to start small, experiment, learn and evolve without replacing infrastructure or losing control. They adapt more easily to changing realities and real business constraints. This is where the real benefit appears. A company that maintains its closed model must do almost everything on its own. A company that builds an open platform effectively recruits the entire market. Value does not escape to the outside. It accumulates around the infrastructure and the business that enables it.
With this understanding, we have chosen to release LTX-2, our advanced video model, as a fully open source version. Not to lead a technological debate, but to enable others to integrate this technology into their own work on their own terms, at their own pace and in their own context. This openness drives broader adoption, accelerates research and experimentation, and creates an ecosystem in which knowledge, use cases, and capabilities evolve faster than any organization could alone.
The companies that define the market have not tried to control every detail. They built platforms that others wanted to join. In the age of artificial intelligence, this principle matters more than ever. Advantage is no longer measured just by what a model can do, but by what it allows others to build. The real race for AI is not just a race for technology. It’s a race for openness, adoption and the ability to turn one success into a whole world.
The author of the article is Dr. Zeev Farbman, co-founder and CEO of Lightricks.