(Bronson Stamp for Sherwood News)

What company’s past reveals the future of OpenAI?

Sherwood asked a baker’s dozen of writers to make their best case for what’ll happen to the most important company of 2024: OpenAI.

Walt Hickey

12/26/24 8:52AM

OpenAI has, in a very short time, catapulted itself from a small operation tinkering in a speculative and math-heavy field to a household name that’s been compared favorably to some of the most lucrative blue-chip companies in the history of American commerce.

This fast trajectory has made the company itself the topic of fascination and speculation, with the ultimate power of its technology, and the ultimate value of its business, the subject of endless discussion and debate. Contemplating the future of AI in general and OpenAI in particular isn’t just a Silicon Valley parlor game but national watercooler chatter. OpenAI is the next Google, some cry — it’ll change the way we use the internet! Others warn it’s the next FTX, an over-hyped scam led by a charismatic founder that’ll go to zero.

Here at Sherwood we wanted to consider the many paths that lay ahead for OpenAI, and we’ve assembled an all-star crew of writers who make their case for what they argue is OpenAI's future. Some see huge returns, others serious peril. In some cases, the tech is transformative on a scale that today we have difficulty even imagining; in others, you’ll hear about a rather boring but extremely lucrative business. And then there’s Taco Bell.

Let the arguments begin:

OpenAI is Visa by Taylor Lorenz
OpenAI is bitcoin by Crystal Kim
OpenAI is Uber by Max Knoblauch
OpenAI is Lyft by J. Edward Moreno
OpenAI is Adobe by Sophia Smith Galer
OpenAI is Pixar by Jon Keegan
OpenAI is Intel by Jeff Wise
OpenAI is IBM by Jack Raines
OpenAI is Microsoft by Ryan Broderick & Adam Bumas
OpenAI is Salesforce by Rani Molla
OpenAI is Napster by Jamie Wilde
OpenAI is Taco Bell by Adam Chandler
OpenAI is Lehman Bros. by Ed Zitron

OpenAI did not respond to a request for comment on the series from Sherwood News.

$26B

Jon Keegan11h

Nvidia is planning on spending $26 billion to train its own AI open-weight models, according to a 2025 financial filing. Wired was first to report the information. Nvidia has released several of its own AI models, including the Nemotron reasoning model, as well as specialized ones for specific tasks.

Nvidia making its own large frontier models could allow the company to go head-to-head against some of its biggest AI customers.

Rani Molla13h

Musk blurs the boundaries of his companies even more with joint xAI-Tesla AI agent project

Tesla and SpaceX CEO Elon Musk said Wednesday that Tesla and xAI, which is part of SpaceX, would work on a joint AI agent project called “Macrohard,” also referred to as “Digital Optimus,” as part of Tesla’s $2 billion investment in xAI. The collaboration would pair Grok with what Musk described as a real-time computer-controlling AI agent running on Tesla hardware.

In his post, Musk said Grok would serve as the higher-level “System 2” reasoning layer directing “Digital Optimus,” a faster “System 1” layer that processes the last five seconds of screen video and keyboard/mouse inputs to take action. He said the system would run inexpensively on Tesla’s low-cost AI4 chip alongside more expensive Nvidia chips at xAI, and suggested it could, “in principle,” emulate the function of entire companies. “No other company can yet do this,” he said.

Macrohard or Digital Optimus is a joint xAI-Tesla project, coming as part of Tesla’s investment agreement with xAI.

Grok is the master conductor/navigator with deep understanding of the world to direct digital Optimus, which is processing and actioning the past 5 secs of…
— Elon Musk (@elonmusk) March 11, 2026

Business Insider reported earlier Wednesday that Tesla was taking up the AI agent mantle as xAI’s similar project stalled, but Musk’s post suggests the initiatives are more intertwined than previously understood.

The collaboration marks the latest example of Musk’s companies working closely together, further blurring the lines between Tesla and the recently merged SpaceX-xAI entity.

Rani Molla16h

Meta doubles down on custom inference chips after reportedly scrapping training chip

Meta said today that it’s expanding its custom silicon development to include four new generations of Meta Training and Inference Accelerator (MTIA) chips. The announcement comes just weeks after The Information reported that the social media company had scrapped its most advanced AI training chip, dubbed Olympus, after facing design challenges. In the meantime, it signed outside chip deals with Nvidiaand Advanced Micro Devices.

Early in its recent conference call, Broadcom CEO Hock Tan sought to reassure investors that the custom chip specialist’s relationship with the social media giant was only getting stronger.

“Now contrary to recent analyst reports, Meta’s custom accelerator MTIA road map is alive and well,” he said. “We’re shipping now.”

The new road map suggests Meta’s in-house chips will focus more on inference, which has more predictable workloads, over training — a technically more demanding area dominated by Nvidia:

“MTIA 300 will be used for ranking and recommendations training, and is already in production. MTIA 400, 450 and 500 will be capable of handling all workloads, but we will primarily use these chips to support GenAI inference production in the near future and into 2027.”

Meta CFO Susan Li told attendees at Morgan Stanley’s tech conference earlier this month that the company “eventually” plans to expand its custom chip design to include training models.

Expanding Meta’s Custom Silicon to Power Our AI Workloads

Early in its recent conference call, Broadcom CEO Hock Tan sought to reassure investors that the custom chip specialist’s relationship with the social media giant was only getting stronger.

“Now contrary to recent analyst reports, Meta’s custom accelerator MTIA road map is alive and well,” he said. “We’re shipping now.”

The new road map suggests Meta’s in-house chips will focus more on inference, which has more predictable workloads, over training — a technically more demanding area dominated by Nvidia:

“MTIA 300 will be used for ranking and recommendations training, and is already in production. MTIA 400, 450 and 500 will be capable of handling all workloads, but we will primarily use these chips to support GenAI inference production in the near future and into 2027.”

Meta CFO Susan Li told attendees at Morgan Stanley’s tech conference earlier this month that the company “eventually” plans to expand its custom chip design to include training models.

Rani Molla16h

Google completes acquisition of Wiz — its biggest ever

Today Google said it has completed its $32 billion acquisition of cybersecurity startup Wiz, the largest deal in the company’s history.

“This acquisition is an investment by Google Cloud to improve cloud security and enable organizations to build fast and securely across any cloud or AI platform,” the company wrote in the press release.

The companies agreed to the all-cash purchase last year, after quite a bit of back-and-forth.