I'm not sure Ms Meeker is as relevant as she once was.
As to gospel, another contender might be "Stanford University's 2025 AI Index Report".
From Dave Friedman's Buy the Rumor, Sell the News, June 1:
Mary Meeker's 2025 AI Trends Report charts a future of exponential adoption and investor euphoria. But what isn't she saying?
Mary Meeker1 just dropped her 2025 AI Trends report, a 300+ slide compendium of hockey-stick charts, CapEx surges, and breathless adoption curves. If you wanted a single document that encapsulates Silicon Valley's consensus AI worldview—growth is good, more is better, and China is a threat—you've found your catechism.
But like most techno-optimist narratives, it's what the report doesn't say that matters most. The problem isn’t Meeker’s exuberance about growth. It’s her silence about the material preconditions of that growth. AI adoption curves don’t ascend in a vacuum. They run on electrons, water, and land. AI doesn’t scale on vibes. It scales on grid interconnects, substation backlogs, and megawatts-per-megachip.
What the Report Gets Right
AI Is a Compounder on Internet Rails
Meeker's sharpest insight is structural: AI isn't a new internet. It's a layer on top of the existing digital substrate. Adoption is fast not because AI is magical, but because the infrastructure for instant scale already exists. ChatGPT's global user growth outpaces the internet itself because it rides the rails of smartphones, APIs, and cloud distribution.
CapEx and Developer Growth Are Real
The developer ecosystems around NVIDIA and Google are exploding—6x and 5x YoY, respectively. CapEx among the "Big Six" (Apple, Microsoft, Meta, Alphabet, Amazon, NVIDIA) surged 63% to $212B. That money isn't imaginary. Neither are the chips or the hiring sprees.
Inference Is Getting Cheaper, Training Is Not
One of the more balanced takeaways: per-token inference costs are dropping, while training costs are skyrocketing. This leads to greater developer experimentation even as model development becomes more exclusive. It’s a tale of diffusion at the edge and concentration at the core.
AI's Physical World Infiltration
Real-world use cases, including robotics in China, autonomous taxis in SF, ambient AI scribes in healthcare, and more are starting to move from pilot to production. The “AI meets atoms” story is maturing.
What the Report Misses
The Energy and Infrastructure Cliff
The report glamorizes Jensen Huang's metaphor of “AI factories” but completely ignores the energy input side of that equation. Where is the power coming from? How does this scale without melting grids or overloading transformers? No mention of cooling, latency, or land constraints. It’s CapEx euphoria without physical context....
....MUCH MORE
Recently from Mr. Friedman, May 28's "Stargate and the AI Industrial Revolution"