Google’s Waymo in NYC near Freedom Tower

Rani Molla/Sherwood News

Where Morgan Stanley thinks autonomous taxis will be in 2032

Google’s Waymo and Tesla will still be in the lead.

12/9/25 8:41AM

Recently we laid out the current autonomous ride-share landscape, which is mostly a battle between Google’s Waymo and Tesla. According to a new report from Morgan Stanley’s research team that looks forward to the next half decade, robotaxis’ future — while expected to grow rapidly — might not be so different.

In 2032, the Morgan Stanley research team expects Waymo and Tesla to command about 70% (~38% and ~29%, respectively) of autonomous miles driven in the US.

In turn, the firm believes autonomous miles will represent about 30% of all ride-share miles in the US.

% of US autonomous ride-share miles — Morgan Stanley

Looking at that from the perspective of trips and the apps that controls them, and using the current partnership mix, Uber and Lyft will capture just about 30% of all AV trips, down from basically controlling the entire ride-share market now.

Share of AV trips by app provider — Morgan Stanley

As these companies scale their autonomous efforts and improve their tech, costs are widely expected to decline. Morgan Stanley believes cost per mile for Waymo, which is currently nearly double Tesla’s cost, will drop from $1.43 to $0.99 by 2028. Meanwhile, the cost per mile for Tesla ride-sharing will dip below the cost of car ownership, which is growing.

autonomous cost per mile — Morgan Stanley

Much of the future of ride-sharing, according to Morgan Stanley, hinges on whether or not robotaxis create more demand or take from current demand.

“AV incrementality remains critical for Uber/Lyft, who will likely lose significant share of the rideshare industry as autonomous platform disruption grows,” the researchers wrote.

$26B

Jon Keegan10h

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 Molla15h

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 Molla15h

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.