The Case That A.I. Is Thinking

"Dario Amodei, the C.E.O. of the artificial-intelligence company Anthropic, has been predicting that an A.I. "smarter than a Nobel Prize winner" in such fields as biology, math, engineering, and writing might come online by 2027. He envisions millions of copies of a model whirring away, each conducting its own research: a "country of geniuses in a datacenter." In June, Sam Altman, of OpenAI, wrote that the industry was on the cusp of building "digital superintelligence.""

"Meanwhile, the A.I. tools that most people currently interact with on a day-to-day basis are reminiscent of Clippy, the onetime Microsoft Office "assistant" that was actually more of a gadfly. A Zoom A.I. tool suggests that you ask it "What are some meeting icebreakers?" or instruct it to "Write a short message to share gratitude." Siri is good at setting reminders but not much else."

"I used to be sympathetic to that view. I sought comfort in the idea that A.I. had little to do with real intelligence or understanding. I even celebrated its shortcomings-rooting for the home team. Then I began using A.I. in my work as a programmer, fearing that if I didn't I would fall behind. (My employer, a trading firm, has several investments in and partnerships with A.I. companies, including"

Prominent AI leaders predict near-term arrival of systems exceeding human experts in domains such as biology, math, engineering, and writing, envisioning massive parallel model deployments conducting independent research. Public-facing AI features remain rudimentary and inconsistent, with examples ranging from helpful meeting prompts to fabricated anecdotes. The rapid, uneven rollout generates both hype and skepticism, and some timelines appear overly optimistic given current model improvement rates. Skepticism about AI's intelligence has shifted for some practitioners who began incorporating AI into programming work to stay competitive, influenced by institutional investments and partnerships in AI.

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