AI research is dead, long live AI
The article argues that traditional AI research has been replaced by a focus on applying large language models to various tasks, a shift the author views as intellectually stagnant. The author contends that the field has collapsed into creating agent pipelines that rely on existing models rather than inventing new knowledge or understanding. This transition is described as a Kuhnian revolution where the goal has shifted from achieving artificial general intelligence to interpreting the outputs of stochastic oracles.
- ▪Approximately half of current AI papers focus on creating new agent pipelines to perform human tasks using existing large language models.
- ▪The author suggests that natural language processing has been subsumed by AI research, with classical subtopics like syntax parsing being discarded in favor of LLM-based approaches.
- ▪The field's focus has shifted from inventing new knowledge to making AI appear to possess knowledge, a process the author describes as boring and environmentally devastating.
- ▪The moment of ChatGPT is characterized as a scientific revolution that transformed AI from an eschatological goal into a present reality that requires interpretation rather than creation.
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Story provenance
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Record
| Original publisher | Kyle Roth |
| Canonical URL | https://kylrth.com/post/ai-research-is-dead/ |
| Publication time | Thu, 01 Oct 2026 04:19:52 +0000 |
| Retrieval time | 2026-10-01T04:27:20.596Z |
| Last seen | 2026-10-01T04:27:43.281Z |
| 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 | f8OO2cxrFPE- · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| 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 |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| 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
AI research is dead, long live AIPosted on 2026-09-30 at 10:41:41 UTC-0400ai politics scienceinspired by Mike Cook’s 2026-09-22 article “Why I love AI” (MHTML archive)MHTML is a web archiving file format that combines an HTML page and its associated resources into a single file.This may be showing my youth, but I am surprised to learn that route optimization algorithms were once considered a part of AI research; I’ve always seen it treated as a highly distinct field, sometimes even outside the realm of informatics/CS. My department is named Département d’informatique et de recherche opérationelle, or “department of informatics and operations research”, where “operations research” is about such optimization algorithms.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Kyle Roth.
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