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⭐ Federico Faggin — Why Computers Cannot Understand Meaning (Bullet Points Only)

• Computers process symbols, not meaning. In computer science, “information” means the manipulation of symbols (bits, patterns, probabilities). This is syntactic processing, not semantic understanding.

• Symbolic information ≠ knowing. A computer can recognize and transform symbols, but it has no interior experience of what those symbols represent.

• Knowing requires consciousness. True understanding involves subjective experience — taste, emotion, sensation, intuition — none of which exist inside a machine.

• AI can mimic language but cannot feel it. A computer can output “I love you,” but without consciousness, the phrase has no meaning to the machine.

• Humans give meaning to symbols through lived experience. Meaning arises from the interiority of consciousness — the felt sense behind words, not the words themselves.

• We anthropomorphize AI because it imitates us. But imitation is not understanding; it is mechanical pattern‑matching.

• Computers represent our thoughts, not reality itself. They are tools built to manipulate symbols according to rules we designed — not conscious entities with their own interiority.

If you want, I can also tabulate this, map it to Advaita, or connect it to your voltage/magnetism cosmology.