Another big red flag, economist Daron Acemoglu warns, lies in the shared thesis that by crunching more data and engaging more computing power, generative AI tools will become more intelligent and more accurate, fulfilling their potential as predicted. His comments were shared in a recent Goldman Sachs report titled “Gen AI: Too Much Spend, Too Little Benefit?”

“Large language models today have proven more impressive than many people would have predicted,” he said. “But a big leap of faith is still required to believe that the architecture of predicting the next word in a sentence will achieve capabilities as smart as HAL 9000 in 2001: A Space Odyssey.”

What the skeptics (or realists) are ultimately warning is that AI’s journey from “pretty good” to “perfect” could be as long, if not longer, than the journey from “nothing” to “pretty good.” Even if artificial general intelligence does reach perfection, or something acceptably and reliably close to it, the energy burden may just topple the US power grid, which, as a text message from Con Edison reminded me this week, currently struggles with summer.

The loudest voices suggesting that AGI — HAL — is around the corner are those who stand to benefit most from the hype. Trillions of dollars in shareholder value depends on believing. Consider one cheeky comparison made by the tech analyst Benedict Evans: At $3.7 billion in annualized revenue for its AI business, Accenture is making more money from consulting companies on AI than OpenAI is from creating it. Maybe some restraint is in order.