SEC Preparing a Proposal to Drop Quarterly Earnings Reports

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For this day. Nvidia's Developers Conference kicks off today with a new focus that reflects a big shift in the world of AI. We'll tell you more about inference in just a bit. Plus, new housing policies intended to help New York City renters might end up pushing out mom and pop landlords.

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And The Wall Street Journal has learned that the SEC is preparing a proposal. It would eliminate the decades-old rule for public companies to post financial results every quarter. It's Monday, March 16th. I'm Alex Ossola for The Wall Street Journal. This is the PM edition of What's News, the top headlines and business stories that moved the world today. We are exclusively reporting that the Securities and Exchange Commission is working on a proposal to eliminate the requirement that public companies post their earnings every quarter. The proposal would make that optional, or companies could just share results twice a year. We've learned that the SEC could publish this proposal as soon as next month. It then eventually goes to a vote. Any change is likely to face opposition from investors who rely on the transparency of regular disclosures. Publicly traded companies in the US have reported results every three months for more than half a century. The push for semi-annual reporting gained steam late last year. President Trump has backed the idea, and supporters say it could help boost the shrinking number of public companies in the US.

Today was the start of Nvidia's annual Developers Conference. But this year, the focus for the first time isn't on graphics processing units, the powerful chips on which Nvidia built its computing empire, and that the event is named for. Instead, the AI industry has moved into a new phase. Nvidia's customers are less concerned today with training large AI models, what GPUs are best at, and more preoccupied with running them and generating big profits from end users. Journal reporter Robbie Whelan told our Tech News Briefing Podcast about the AI shift to a type of computing called inference.

Robbie Whelan (2:45)

Nvidia dominates the world of what's known as AI training, but they don't have quite as much of a foothold in what's known as AI inference, how to run models and make them respond to your user queries faster. So we're expecting them to roll out a new chip that's going to make them a lot better and a lot faster that allow the computer brain to kind of go back into its memory and access all of its training, all the databases that have been pumped into it to teach it how to be an AI model.

Alex Ossola (3:18)

This is a new space for Nvidia, but Robbie says that doesn't mean the company is in a bad position.

Robbie Whelan (3:23)

They have more money than just about anybody in this entire space, so I don't think they're going to be too far behind when it comes to developing products quickly that serve the inference computing needs and, more importantly perhaps, locking up the supply chain that is needed for it to produce inference. For example, right now there's a big crunch in supply of memory chips. There's only a certain number of companies that make memory chips that are usable in AI systems and Nvidia is one of the biggest buyers of those chips and they have essentially locked up their supply for the next two or three years and so there might be other competitors who are smaller who are trying to do the same thing, trying to produce usable, fast, powerful inference systems that don't have the same clout in the supply chain that Nvidia has. There's a company called Cerebras. It's a startup that has raised a ton of money and recently did a $10 billion licensing deal with OpenAI to help OpenAI build its own custom chips for inferencing. So the entire ecosystem is seeing much more competition and suddenly these companies that seemingly appear out of nowhere but have actually been doing research for many years, they're suddenly finding that the world is really thirsty for their product.