AI Is Getting Way Too Expensive
Even in Exponential View’s deliberately-pro-industry analysis, there’s only around $110 billion in trailing twelve-month revenues across the entire industry, including OpenAI and Anthropic’s cloud spend. For those counting at home, that’s $12 billion less than the $122 billion OpenAI raised in March, and a full $145 billion less than all AI startups raised combined in the first quarter of 2026.
- ▪Even in Exponential View’s deliberately-pro-industry analysis, there’s only around $110 billion in trailing twelve-month revenues across the entire industry, including OpenAI and Anthropic’s cloud spend.
- ▪For those counting at home, that’s $12 billion less than the $122 billion OpenAI raised in March, and a full $145 billion less than all AI startups raised combined in the first quarter of 2026.
Hacker News (AI / LLM) files mainly under ai. We currently carry 3,087 of its stories.
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| Original publisher | Ed Zitron's Where's Your Ed At |
| Canonical URL | https://www.wheresyoured.at/premium-ai-is-getting-way-too-expensive/ |
| Publication time | Fri, 31 Jul 2026 17:34:04 +0000 |
| Retrieval time | 2026-07-31T17:38:31.609Z |
| Last seen | 2026-07-31T17:38:31.609Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | aepK7JzPYf7j · 1 stories |
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| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
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| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
A great deal of the discussion of the so-called benefits or problems with AI comes down to the theoretical jobs that are (or are not) lost as a result of things LLMs can (or cannot do), or the equally theoretical productivity benefits that’ll come from using LLMs in place of (or in conjunction with) humans.Anthropic’s Economic Index and OpenAI’s Economic Research Exchange are marketing operations that exist to propagate the (wrongheaded) belief that LLMs are either leading or will soon lead to massive economic or productivity shifts, even though little or no actual evidence exists to show that this is the case, other than the occasional story about LLMs make people worse or slower at their jobs or single lines in studies that are used (incorrectly) to prove that “AI is making it harder to…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Ed Zitron's Where's Your Ed At.
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