“Cognitive distillation” between rationality and possession!

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At a time when military conflicts are escalating on the fronts of the real world, and the major powers are racing to develop their arsenals, enhance their combat capabilities, and employ all available capabilities to reach artificial intelligence products, behind this scene other wars are taking shape and of a different nature, more complex and with greater impact on the future of international influence. Wars that use knowledge and algorithms as a weapon, and artificial intelligence as an open field for competition to possess the power and superiority of extremely sensitive and precise technologies, including the knowledge distillation technology, which opens wide doors to questions that go beyond the limits of innovation to information security, intellectual property rights, and the future of the technical sovereignty of countries. Rather, it penetrates the sources of their security, data, and actual capabilities, whether military or otherwise. So what is knowledge distillation and where do its products end up?

Knowledge distillation is an example of the most troubling challenges, as it opens new paths to the acquisition of technical knowledge, without necessarily having to penetrate systems or seize their programming secrets, as its mechanism relies on subjecting advanced models to an intensive and systematic series of questions and tests to extract the essential conclusion from huge amounts of knowledge or complex data, and present it in a focused, simplified, and quickly digestible form. In short, it is the process of transferring knowledge from a huge, highly complex artificial intelligence model called the “teacher” to a smaller, lighter model. It is called the “student”, and thus its outputs are used to train other models that mimic some of its cognitive and reasoning abilities. It is a practice that varies in legality depending on the means, licenses, and conditions of use, but it turns into a threat when it aims to clone protected capabilities in unauthorized ways. The warnings issued by OpenAI regarding attempts to distill its models have re-shed light on this new model of technical competition, as the value of industrial secrets goes beyond the limits of codes and stored information to the capabilities that systems have acquired through complex training processes.

These shifts reveal a strategic dilemma that will face technology companies and governments alike. Protecting innovation is no longer limited to fortifying servers and securing data, but has extended to monitoring models’ usage patterns, detecting attempts to extract their capabilities, and reconsidering legislation regulating intellectual property. With the growing economic, military, and intelligence value of artificial intelligence, protecting accumulated knowledge will become an integral part of the concept of national security and technical sovereignty, especially among countries that invest in building their independent digital capabilities.

Perhaps what is most worthy of contemplation about this scene is that the world stands on the cusp of a stage in which the nature of secrets and the means of acquiring them are changing, and during which the boundaries of legitimate learning, industrial competition, and technical espionage overlap, and we may witness in the future a conflict whose battles do not revolve around possessing machines and algorithms alone, but rather around the ability to extract what those machines have learned. Then humanity will face a very complex question: How do we protect knowledge from being copied, when the philosophy of artificial intelligence itself is based on learning and simulation?

In conclusion... If traditional wars aim to control land and resources, then future wars may be resolved by the ability to possess knowledge or reproduce it at the lowest cost and in the shortest time!