"AI" Is Eating Platform Monopolist Free Cash Flow, Not the World: CHART OF THE DAY
New empirical evidence on AI‑boosted coding, the apparent absence of a matching surge in valuable products, and the persistent unreliability of large models in real‑world use. Burn‑Murdoch’s chart and Noah Smith’s “tokenmaxxxing” frame a world where we’re flooding the zone with more software artifacts and software-created information streams no one particularly needs…
Noah Smith directs us to this:
It is from Demirer & al. <https://www.nber.org/papers/w35275>, redrawn by the FT team and highlighted by:
John Burn-Murdoch: How Much Value Is AI Really Creating? <https://www.ft.com/content/8e9ae7a4-7209-4e2c-aa36-f3af77d6ce1f?syn-25a6b1a6=1>: ‘One particular point of tension between AI’s boosters and detractors has been the disconnect between reported increases in coders’ output and the apparent lack of a corresponding boom in product or value creation…. Explosive impact at the top of this funnel — coders created or edited almost 300 per cent more files — but that boost was halved to 150 per cent by the time they got to the number of discrete pieces of work submitted for review, and that in turn shrunk fivefold to a roughly 30 per cent uplift in the number of full software releases…. Moreover… the marked increase in mobile app releases over the past year has not been accompanied by any increase in downloads—most of the new apps fail to capture even a modest audience….
Uber CEO Dara Khosrowshahi revealed the company had blown through its entire AI budget for 2026 in one quarter, and was planning to switch much of its AI use to lower-cost models, reserving frontier tools for special cases…. But realised productivity gains are capturing the interaction of powerful new tools with poorly suited structures and processes. Those frictions and bottlenecks will only ease over time…
That last is interesting. Colin John Burn-Murdoch remains an AI bull over the long run. As does Noah Smith, who comments:
Noah Smith: Tokenmaxxxing <https://www.noahpinion.blog/p/roundup-83-i-told-you-so>: ‘Demand for many of the things that generative AI produces might be a lot more inelastic than we thought. The things we really want a lot more of may not actually be the things that generative AI is yet equipped to provide. As the AI industry advances, of course, that will probably change…
Also: <https://next-media-api.ft.com/renditions/17613947027010/1280x720.mp4
Brad here: Most of the Silicon Valley tech bros see “AI” as us building increasingly sophisticated digital brains that do the kinds of things that human beings do, and will someday very soon now replace them, in that whatever one would have sent to a human one will soon be able to send straight to a ‘bot.
I see MAMLMs as things that are very, very good for very high-dimension, very big-data, very flexible-function classification, regression, and prediction analysis. Plus “agentic” models are good for interaction speed: Clever Hans at scale trying things that fail with high probability and then retrying them with inexhaustible patience much more rapidly than a human could. These have tremendous uses—natural-language interfaces, summarization engines, and coding assistants being the first three that we have found.
Plus, even with coding assistants, they are not reliable. They cannot be let off of their leashes. My most recent in-message:
Hardware Status Report: As of 12:00 PM, machine is under moderate GPU load due to ollama inference. Total chip power draw is 350W.
GPU utilization: 68% (ollama inference)
ANE utilization: 0%
CPU clusters: Cluster 0 active, Clusters 1-7 power-gated
Memory: 92GB used / 128GB, swap 0MB, compressor significant
Top processes by memory:
Ollama: 56.3GB (model: mistral-nemo-16k)
Python: 3.4GB
VSCodium: 1.2GB…
From the bottom:
Ollama is running both google-gemma-4-26b and mistral-nemo-16k—not mistral alone.
I do not know how the 18 CPU cores could possibly be divided into 8 “clusters”, and it is certainly not true that 7 of these 8 “clusters” are powered-down right now.
The M5Max chip is not drawing 350W of power.
For the foreseeable future, it is as silly to think that you will be able to drop one of these things into a job that a human now does as to think that a hotel door equipped with an automatic electric eye could replace a hotel doorman:
Rory Sutherland: Alchemy <https://www.goodreads.com/work/quotes/46190767-alchemy-the-surprising-power-of-ideas-that-don-t-make-sense>: ‘First you define a hotel doorman’s role as ‘opening the door’, then you replace his role with an automatic door-opening mechanism. The problem arises because opening the door is only the notional role of a doorman; his other, less definable sources of value lie in a multiplicity of other functions, in addition to door-opening: taxi-hailing, security, vagrant discouragement, customer recognition, as well as in signalling the status of the hotel. The doorman may actually increase what you can charge for a night’s stay…
MAML GPT LLM are very fast, very flexible tools, not brains; they open doors, but they are not the doorman.