The case for boring AI

What would artificial intelligence look like if it was actually built for people?

VALENTIN FLAURAUD/AFP via Getty Images

The AI benchmark race has a winner. It just isn't you.

Every few months, a new model drops and a new leaderboard reshuffles. Labs compete to out-reason, out-code, and out-answer each other on tests designed to measure machine intelligence. The coverage follows. So does the funding.

What gets less attention is whether any of this is inevitable. The benchmarks, the arms race, the framing of AI as either salvation or catastrophe — these are choices, not laws of physics. They reflect what the industry decided to optimize for, and what it decided to fund. Technology that will take decades to pan out in ordinary, useful ways doesn't raise billions this quarter. Extreme narratives do.

Some researchers think the goal is simply wrong. Not that AI isn't important, but that important doesn't have to mean unprecedented. The printing press changed the world. So did electricity. Both did it gradually, through messy adoption, giving societies time to respond. If AI follows that pattern, the right questions aren't about superintelligence. They're about who benefits, who gets harmed, and whether the tools we're building actually work for the people using them.

Plenty of researchers have been asking those questions from very different directions. Here are three of them.

Ruchir Puri has been building AI at IBM $IBM since before most people had heard of machine learning. He watched Watson beat the world's best Jeopardy players in 2011. He's watched several cycles of hype crest and recede since. When the current wave arrived, he had a simple test for it: is it useful?

Not impressive. Not general. Useful.

"I don't really care about artificial general intelligence," he says. "I care about the useful part of it."

That framing puts him at odds with much of the industry's self-image. The labs racing toward AGI are optimizing for breadth, building systems that can do anything, answer anything, reason about anything. Puri thinks that's the wrong target, and he has a benchmark he'd like to see the industry actually try to reach.

The human brain lives in 1,200 cubic centimeters, consumes 20 watts, the energy of a light bulb, and, as Puri points out, runs on sandwiches. A single Nvidia $NVDA GPU consumes 1,200 watts, 60 times more than the........

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