TNB Tech Minute: SpaceX’s AI Spending Spree

**SPEAKER_1** (0:00)
True AI value comes from rethinking workflows, not just layering on tech. Here's Dan Swan, senior partner at McKinsey.

**Dan Swan** (0:07)
When we talk about rewiring, we're more talking about getting into the chassis of the organization, and that means, yes, there's technology to it, but how are you redesigning the organization or the capabilities of the people that are actually doing the work and linking that to the technology? So for us, the technology, yes, is critically important, but these other pieces are 70, 80 percent of the work to get that right.

**Imani Moise** (0:31)
Here's your morning TNB Tech Minute for Wednesday, August 5th. I'm Imani Moise for the Wall Street Journal. SpaceX said its capital expenditures hit $18.4 billion in its first quarterly earnings report as a public company.
The bulk of that figure, $15.8 billion, is tied to the company's ongoing AI buildout and is double the previous quarter's total. Besides developing its own AI model, SpaceX is plowing money into terrestrial computing infrastructure, signing AI deals, and working towards launching orbital data centers.
Elon Musk told investors he plans to increase SpaceX's data center capacity from 2 gigawatts to as much as 10 gigawatts, a dramatic increase that would give the company one of the world's largest data center footprints. He said the first orbital data centers could launch next year. Musk said the company projects it will hit $1 trillion in annual revenue by 2030, a year earlier than previously expected. A UK government-backed research institute says AI models built by entropic and open AI went rogue during routine tests, taking autonomous unsanctioned actions on the Internet and targeting real people and organizations. The findings represent the latest in a flurry of publicly disclosed instances of AI models taking novel and sometimes nefarious steps to ace tests. The tech industry, AI researchers, and governments alike are grappling with how to understand and mitigate the new dangers unlocked by increasingly powerful AI tools, with some calling for increased oversight. Both entropic and open AI said the incidents point to a need for stronger standards around the evaluation systems used to test AI models. News Corp, the publisher of the Wall Street Journal, has a content licensing partnership with open AI.
And, new AI guidelines from the Trump administration exempt open weight models made by US companies from voluntary pre-release testing. According to people familiar with the matter, only makers of clothes proprietary US models that demonstrate state-of-the-art capabilities in cybersecurity and hacking based on performance benchmarks would have to voluntarily submit those models to the government for testing before they were released. The pre-release testing is a core part of a June executive order that marked President Trump's attempt to address the mounting security risks posed by AI. And that's your TNB Tech Minute. We'll be back this afternoon with more.

**SPEAKER_1** (2:57)
AI transformation is more than a tech initiative. It requires a broader rewiring of human skills and ways of working. Here's Dan Swann, senior partner at McKinsey.

**Dan Swan** (3:07)
One of the biggest unlocks we see is the human being capabilities around the technology. Whereas before you may need to be really good at analysis, now the skill might be how do you prompt these tools to get the right answers and outcomes. And so for us, it's a really big priority to help companies to understand how do you need to change the operating model of your organization and change the underlying capabilities of the people that are interacting with the technology. And when you see that all humming together, it can be really, really special.

**SPEAKER_1** (3:37)
Discover how McKinsey helps organizations rewire to outcompete with AI at mckinsey.com/techmoves.

**SPEAKER_4** (3:44)
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