

Different definitions for intelligence:
- The ability to acquire, understand, and use knowledge.
- the ability to learn or understand or to deal with new or trying situations.
- the ability to apply knowledge to manipulate one’s environment or to think abstractly as measured by objective criteria (such as tests)
- the act of understanding
- the ability to learn, understand, and make judgments or have opinions that are based on reason
- It can be described as the ability to perceive or infer information; and to retain it as knowledge to be applied to adaptive behaviors within an environment or context.
We have plenty of intelligent AI systems already. LLM’s probably fit the definition. Something like Tesla FSD definitely does.
That’s because it is.
The term artificial intelligence is broader than many people realize. It doesn’t mean human-level consciousness or sci-fi-style general intelligence - that’s a specific subset called AGI (Artificial General Intelligence). In reality, AI refers to any system designed to perform tasks that would typically require human intelligence. That includes everything from playing chess to recognizing patterns, translating languages, or generating text.
Large language models fall well within this definition. They’re narrow AIs - highly specialized, not general - but still part of the broader AI category. When people say “this isn’t real AI,” they’re often working from a fictional or futuristic idea of what AI should be, rather than how the term has actually been used in computer science for decades.