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For years, the central question in AI has been some variation of: “Is it truly intelligent?” Proponents point to dazzling capabilities—solving novel Olympic-level mathematics problems, generating coherent proofs, achieving human-level performance on ...

We’ve diagnosed AI’s fundamental limitation—now comes the harder task: living wisely with systems that simulate understanding without possessing it. In Episode I, Wittgenstein revealed that meaning emerges from participation in forms of life—shared h...

Wittgenstein showed that words gain meaning through use in shared human practices. But to understand why AI cannot join those practices, we must examine what lies beneath: the structure of signs themselves. A century of semiotic thought—from Saussure...

What does it mean for words to be meaningful? A century-old philosophical quest holds the key to understanding our AI age. Cambridge University, 1911. Bertrand Russell watches his brilliant but restless student, Ludwig Wittgenstein, pace the room lik...

Picture this: you ask a chatbot about the weather, and it replies, “I’m feeling a bit cloudy today, but the forecast is sunny!” It’s charming, witty, and… a little weird. Why is an AI “feeling” anything? This is no nascent personality peeking through...

In our relentless pursuit of artificial intelligence that can match or exceed human capabilities, we may be overlooking fundamental questions about the nature of understanding itself. Recent research into Large Language Models (LLMs) has revealed fas...

Imagine a detective standing in front of a whiteboard, piecing together clues to solve a complex crime. The whiteboard is filled with photos, notes, and strings connecting suspects, motives, and timelines. The detective’s task is not just to collect ...
