Artificial Intelligence, especially Large Language Models (LLMs), seems to be reaching a plateau. More data no longer guarantees better results. This mirrors human history: when knowledge became too vast for one person, we created specialists—individuals with deep expertise in narrow fields. These specialists collaborated to achieve interdisciplinary progress.

The risk? Compartmentalizing knowledge and losing sight of the connections between sciences.

The next step—both for humans and AI—might be learning on demand: acquiring exactly the knowledge needed, at the moment it is needed. For humans, this requires enormous effort, flexibility, and rapid adaptability—skills that are still difficult to master. For AI, however, this challenge looks different. With the right structures, AI systems could access, process, and apply information instantly, anywhere, anytime.

This vision suggests a new paradigm: not just larger AI, but teams of specialized AIs working together, capable of learning on demand and bridging expertise across fields. Just like humans, but with a speed and scalability we can only imagine.

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