Allison Morrow

2024 may not have been the best or worst year ever for McDonald’s — but it was certainly a memorable one.

It’s impossible to describe Taylor Swift’s Eras Tour, which had its final show Sunday, without mentioning its economic superlatives: the highest-grossing tour of all time; a force that gave tourism a shot in the arm around the world; a core memory for millions of fans, some of whom flew around the world and shelled out thousands of dollars to attend.

Once upon a time, a brash outsider entered the Oval Office with a promise to “drain the swamp.” He brought in a posse of businesspeople, led by a leading industrialist, to work like “tireless bloodhounds” to root out inefficiencies in Washington’s vast bureaucracy.

Sam Altman, the PT Barnum of the AI industry, has a message for the folks concerned about the technology he’s dedicated his life to advancing: Don’t worry, the nerds are on it.

The New York Times once wrote a fascinating story about how Mark Zuckerberg, the 40-year-old Meta CEO, had become disillusioned with the lefty politics he’d once promoted. Zuck was “declining to engage with Washington except when necessary,” “stopped supporting programs at his philanthropy that could be perceived as partisan” and “tamped down employee activism at Meta.” In short, the Times concluded, he was over it.

Moving from a Wall Street corner office to a DC corner office comes at a cost: For a top financier who’s been asked to run the Treasury Department, say, you could be looking at a pay cut of tens of millions of dollars a year. On top of that, you’d have to offload any stock holdings that create a potential conflict of interest with the new gig.

Marc Rowan, a contender for what is arguably the most important economic job in the US government, is the CEO of Apollo Global Management, a behemoth in private equity, an industry notorious for its cutthroat, profit-at-all-costs standards.

Trump’s Commerce secretary pick is a crypto booster with ties to one of the industry’s most controversial players

Skeptics of AI have long warned of “scaling laws” — the idea of continually improving a model’s output just by adding data and computing power. They aren’t so much laws as educated guesses and even the scientists who built this framework don’t fully understand how they work.

Every hero’s journey has its downbeat second act — the part where many-headed monsters have to be fought back, where the road gets dark and twisty and teeming with threats — before the sun comes up and suddenly everything is, more or less, back on track.