Human understanding is the ability to connect new information to a global, unified model of the universe. Until recently, AI models were isolated (e.g., a chess model). The major advance with large multimodal models is their ability to create a single, cohesive reality model, enabling true, generalizable understanding.

Language is just one 'keyhole' into intelligence. True artificial general intelligence (AGI) requires 'world modeling'—a spatial intelligence that understands geometry, physics, and actions. This capability to represent and interact with the state of the world is the next critical phase of AI development beyond current language models.

Startups and major labs are focusing on "world models," which simulate physical reality, cause, and effect. This is seen as the necessary step beyond text-based LLMs to create agents that can truly understand and interact with the physical world, a key step towards AGI.

Large Language Models are limited because they lack an understanding of the physical world. The next evolution is 'World Models'—AI trained on real-world sensory data to understand physics, space, and context. This is the foundational technology required to unlock physical AI like advanced robotics.

Broad improvements in AI's general reasoning are plateauing due to data saturation. The next major phase is vertical specialization. We will see an "explosion" of different models becoming superhuman in highly specific domains like chemistry or physics, rather than one model getting slightly better at everything.

To make genuine scientific breakthroughs, an AI needs to learn the abstract reasoning strategies and mental models of expert scientists. This involves teaching it higher-level concepts, such as thinking in terms of symmetries, a core principle in physics that current models lack.

World Labs co-founder Fei-Fei Li posits that spatial intelligence—the ability to reason and interact in 3D space—is a distinct and complementary form of intelligence to language. This capability is essential for tasks like robotic manipulation and scientific discovery that cannot be reduced to linguistic descriptions.

AI is developing spatial reasoning that approaches human levels. This will enable it to solve novel physics problems, leading to breakthroughs that create entirely new classes of technology, much like discoveries in the 1940s led to GPS and cell phones.

The next leap in AI will come from integrating general-purpose reasoning models with specialized models for domains like biology or robotics. This fusion, creating a "single unified intelligence" across modalities, is the base case for achieving superintelligence.