U.S. markets had their worst day since Oct. 10. That marks a sharp reversal for the Dow Jones Industrial Average, which shed 1.65% to settle at 47,457.22, a day after it closed above 48,000 for the first time. Meanwhile, the S&P 500 lost 1.66% and the Nasdaq Composite tumbled 2.29%.

The slump in stocks can partly be traced to a turnaround in sentiment regarding artificial intelligence. Tech behemoths such as Nvidia, Broadcom and Oracle slumped, with the last losing more than one-third in value since it rocketed 36% in September.

Investors, it seems, are growing worried over the high valuations of tech names, as well as the gigantic amount of capital expenditure they are committing to — with some, like Oracle, having to take on debt to fulfil those obligations.

Uncertainty over an interest rate cut in December is also putting a downer on Wall Street. It’s a coin toss as to whether the U.S. Federal Reserve will ease monetary policy then, according to the CME FedWatch tool. That’s a huge difference from a month ago, when traders were pricing in a 95.5% chance of a December cut.

Not having October’s employment and inflation numbers, and possibly never getting them, means the Fed lacks visibility into the state of the economy — and whether it should try to support the labor market or continue reining in inflation.

After all, flying blind makes it hard to see where you’ll land. As of now, that applies both to the Fed and investors trying to navigate the still-hazy ambitions of tech companies.

CEO of Southeast Asia’s largest bank says AI adoption already paying off: ‘It’s not hope, it’s now’

“The proliferation of generative AI has been transformative for us,” DBS CEO Tan Su Shan told CNBC on the sidelines of Singapore Fintech Week. She adding that the company was experiencing a “snowballing effect” of benefits thanks to machine learning. 

Tan expects AI adoption to bring DBS an overall revenue bump of more than 1 billion Singapore dollars (about $768 million) this year, compared to SG$750 million in 2024. That assessment is based on about 370 AI use cases powered by over 1,500 models throughout its business. 

— Dylan Butts