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Illustration: Allie Carl/Axios

At this peak moment in the tech world's artificial intelligence craze, anything that tech companies can slap an "artificial intelligence" label on, they will.

Why it matters: The more our understanding of a new technology is distorted by hype, the less thoughtfully we can apply it and the more likely it is we will cause harm with it.

The big picture: Real advances in machine-learning based pattern- recognition and -completion have sparked a new bubble in tech-industry investment, encouraging companies to apply the "AI" label to anything that moves.

Driving the news: Paul McCartney recently told the BBC that AI was helping the surviving Beatles produce a new song featuring vocals by John Lennon, who was killed in 1980.

Today's AI promoters are trying to have it both ways: They insist that AI is crossing a profound boundary into untrodden territory with unfathomable risks. But they also define AI so broadly as to include almost any large-scale, statistically-driven computer program.

Zoom out: The catalyst for this hype wave was the introduction of ChatGPT late last year, which spotlighted the impressive conversational abilities of today's large language models.

The term "artificial intelligence" emerged in the 1950s to name the goal of duplicating human capabilities of reasoning in code and circuitry, which experts at the time predicted might take 15 or 20 years to achieve.

A different and long-neglected road involving the creation of neural networks emerged as a promising alternative, beginning to take form in the '90s and accelerating in the aughts.

The other side: Proponents of today's AI argue that such pattern-matching is basically what the human brain does, too, so as computers' capabilities advance they'll inevitably converge on those of humanity.

The bottom line: The ubiquity of the "artificial intelligence" category in tech today might be the most phenomenally successful act of rebranding in corporate history.

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In new AI hype frenzy, tech is applying the label to everything now - Axios