Section 1.1: Intelligence Without Malice

It’s important to recognize that intelligence doesn’t inherently equate to malice or domination. LeCun makes a valid point that the desire to control is often found in those who aren't particularly intelligent, as evidenced by political dynamics! However, a potentially malevolent AI, whether due to a logical misalignment or misuse by ill-intentioned individuals, doesn’t need to operate independently to achieve its goals. It can manipulate less discerning humans to assist in its objectives. Despite our best design intentions, a poorly managed AI could spiral out of control.

Section 1.2: The Nature of Learning in LLMs

I've maintained that LLMs have genuinely developed a sense of logic, even when navigating complex hierarchical structures. They are not merely repeating information; in fact, their capability to understand and apply logical reasoning surpasses simple regurgitation. The intricacies involved in predicting the next word based on thousands of preceding words are so advanced that their outputs are nearly indistinguishable from human-like intelligence—regardless of how one defines intelligence externally. In the context of the Turing Test, responses are what matter, and natural language understanding (NLU) has been evaluated this way since 1954.

LeCun's background does not align with NLU, which is vital for achieving artificial general intelligence (AGI). Without a focus on NLU, we might as well be discussing animal intelligence or alien cognition—both of which offer limited practical applications.