Another Zuck Bet, Oracle’s CAPEX, and a Softer CPI.

This was a busy week with some earnings, ai deals, and inflation reports that suggest a solid road ahead.

This week’s CPI and PPI reports came in soft, reinforcing a disinflationary trend we’ve been tracking for months. Markets responded with rates lower and expectations of ~2 rate cuts by year-end. As we’ve said before, the data beneath the panic often tells a steadier story and right now, tariffs haven’t derailed inflation. Core inputs like shelter (lagging but cooling) and producer prices (a leading indicator) are pointing in the right direction.

That gives cover for a policy shift for lower rates, while companies across sectors keep building. In AI, we’re seeing a sharp acceleration in infrastructure investment and platform jockeying. Meta just pulled a major strategic lever with Scale AI, and Oracle’s record CAPEX confirms that enterprise spend on compute is still ramping.

The question now: Who controls the user interface, and who controls the infrastructure? As the lines between apps, data, and hardware blur, the investment opportunities lie in understanding which layer is gaining traction.

Here is the summary if you want just that:

• Inflation inputs came in soft.

• Meta’s AI push intensified with Scale.

• AI mobile market share shifts.

Inflation came in softer this week across the board. Both CPI and PPI were muted, with PPI, a leading input into the Fed’s preferred inflation gauge (PCE), showing little pressure. Historically, PPI tends to lead CPI by 3–6 months, which adds another layer of confidence that inflation is likely to stay contained in the near term.

Even with the tariff headlines, unless there’s a significant and immediate change in import costs, the inflation trajectory looks stable.

Shelter inflation was the sticking point inside the CPI report over the last year or so. Now, the shelter component — still deeply lagged — remains positive despite real-time indicators showing declines. A good sign though. Also, as it catches down, it could more than offset any upward pressure from tariffs.

Markets continue to anticipate rate cuts. Fed Fund Futures are currently pricing in 2.087 cuts by December 10th. This expectation aligns with recent inflation data showing moderation and growing evidence that the Fed has flexibility to ease rates amid a stable yet softening job market.

Last week, Meta signed a 20-year nuclear energy deal to power its AI ambitions. This week? Another major swing: a quasi-acquisition of Scale AI, one of the most important infrastructure players in the AI supply chain.

For those unfamiliar, Scale AI is the data layer behind much of the AI boom providing labeled data to train LLMs and other models. Their client list includes many of Meta’s direct competitors, meaning this move isn’t just about talent or product, it’s also about gaining insight into what others are building. When Zuckerberg places a directional bet, it’s worth noting. He tends to see the wind before most.

To understand the significance of Meta’s move, let’s zoom out and look at the broader landscape of private AI infrastructure companies.

OpenAI is now at a $10B revenue run rate.

Anthropic is approaching $3B.

Scale AI sits around $2B, largely driven by its data-labeling infrastructure that powers many of today’s leading AI models.

Scale may not have the brand recognition of OpenAI, but it’s critical — enabling the very training pipelines that these frontier models rely on. And now, Meta is pulling that capability in-house.

Meta isn’t just trying to beef up its AI infrastructure, it’s trying to catch up to the frontier. While Scale gives them a stronger data pipeline, Meta still trails behind OpenAI, Anthropic, and Google DeepMind when it comes to the sheer scale of training data and model performance. Benchmarks show Meta’s LLaMA models have been surpassed in both size and capability, but that gap may not last long. Zuckerberg is clearly on a mission. Whether through open-source efforts or direct investments, Meta wants to be in the top tier of foundation model builders.

Here’s a surprising stat: 70% of ChatGPT usage happens on desktop, while Google leans 60% mobile. This runs counter to what many might expect in today’s mobile-first world and reveals a key friction point in AI product distribution. While Google is deeply entrenched in the app ecosystem, ChatGPT’s dominance is tied more to productivity and research tasks, which tend to happen at a desk. This doesn’t mean mobile AI is a lost cause it may just be underdeveloped. The app layer is still wide open in my view.

ChatGPT once held ~80% market share in the AI app ecosystem. Today? That’s closer to 60%.

While it remains the dominant player, the trendline is clear, competition is creeping in, particularly through mobile. New entrants are leveraging app-native features, tighter integrations, and real-time UX innovation to carve out share. And with most people spending the bulk of their digital time on phones, this battleground may prove decisive.

Oracle reported earnings this week — and while the topline beat was solid, the real story was CAPEX. Oracle’s CAPEX hit 57% of revenue, an all-time high. The company explicitly stated this is AI infrastructure spend, data centers, GPU clusters, and cloud capacity for AI clients.

It’s a huge signal. Oracle is traditionally seen as legacy tech, yet it’s now going all-in to meet AI demand. And that demand is clearly accelerating.

That is all this week. Steady jobs, inflation muted and companies continue to go after ai.

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