The Illusion of Intelligence: Why Deep Learning Alone is Not Enough

In the age of AI hype, Deep Learning is often hailed as the magical ingredient behind the “intelligence” of large language models (LLMs) like GPT, Gemini, or Claude. But here’s a necessary reality check: Deep Learning alone is not enough. The true power lies in the Internet. The architecture may be cutting-edge, but it’s the data that gives these systems their apparent brilliance.

The term “AI” creates an image for consumers of thinking, understanding, even consciousness.
LLMs like GPT meet none of these criteria – yet they are still marketed as “intelligent.”

Core Problems:

• Semantic deception: The term “intelligence” suggests human cognition, while LLMs merely analyze large amounts of text statistically. They simulate language without understanding meanings or pursuing goals. The model has no real-world knowledge but instead makes predictions based on past training data.