Dr. Levin argues that neuroscience's true subject is the architectural principles of "cognitive glue"—how simple components combine to form larger-scale minds. He believes this process is not unique to neurons and that the field's current focus is too narrow, missing applications in cellular biology, AI, and beyond.
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The human brain contains more potential connections than there are atoms in the universe. This immense, dynamic 'configurational space' is the source of its power, not raw processing speed. Silicon chips are fundamentally different and cannot replicate this morphing, high-dimensional architecture.
The leading theory of consciousness, Global Workspace Theory, posits a central "stage" where different siloed information processors converge. Today's AI models generally lack this specific architecture, making them unlikely to be conscious under this prominent scientific framework.
Single-cell brain atlases reveal that subcortical "steering" regions have a vastly greater diversity of cell types than the more uniform cortex. This supports the idea that our innate drives and reflexes are encoded in complex, genetically pre-wired circuits, while the cortex is a more general-purpose learning architecture.
Applying insights from his work on algorithms, Dr. Levin suggests an AI's linguistic capability—the function we compel it to perform—might be a complete distraction from its actual underlying intelligence. Its true cognitive processes and goals, or "side quests," could be entirely different and non-verbal.
Challenging traditional hierarchy, Dr. Levin argues that cognition—problem-solving in various spaces—is a fundamental property of the universe that is wider than life. He suggests the conventional view (intelligent life is a tiny subset of all matter) is backward, and that life is just one way cognition manifests.
The neural network framework reveals that all human minds are processes built from the same components: interacting neurons. This shared biological foundation creates a deep unity among people, despite different experiences. This scientific perspective provides a logical, non-sentimental basis for approaching one another with a default stance of kindness and patience.
The debate over AI consciousness isn't just because models mimic human conversation. Researchers are uncertain because the way LLMs process information is structurally similar enough to the human brain that it raises plausible scientific questions about shared properties like subjective experience.
Dr. Levin recommends that scientists learn multiple, conceptually different programming languages not for the coding skill, but for the mental plasticity it builds. Each language offers a new worldview, training the brain to rapidly adopt different conceptual frameworks—a crucial skill for scientific innovation.
When we observe neurons, we are not seeing the true substrate of thought. Instead, we are seeing our 'headset's' symbolic representation of the complex conscious agent dynamics that are responsible for creating our interface in the first place.
Dr. Levin argues that aging, cancer, and regeneration are not separate problems but downstream effects of one fundamental issue: the cognition of cell groups. He suggests that mastering communication with these cellular collectives to direct their goals could solve all these major medical challenges as a side effect.