The AI Scaling Wall of Diminishing Returns: Of LLMs, Electric Dogs, and General Relativity
Fuente:
arXiv
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| Autore principale: | |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| Accesso online: | |
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| _version_ | 1866912785503354880 |
|---|---|
| author | Shukla, Hemant |
| author_facet | Shukla, Hemant |
| contents | LLMs are hitting the scaling wall - compute grows 10-100x while accuracy barely moves. This note quantifies the slowdown and argues that the next leap in AI will come not from bigger models, but from smarter, more efficient ones. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_20264 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | The AI Scaling Wall of Diminishing Returns: Of LLMs, Electric Dogs, and General Relativity Shukla, Hemant Instrumentation and Methods for Astrophysics Computational Physics LLMs are hitting the scaling wall - compute grows 10-100x while accuracy barely moves. This note quantifies the slowdown and argues that the next leap in AI will come not from bigger models, but from smarter, more efficient ones. |
| title | The AI Scaling Wall of Diminishing Returns: Of LLMs, Electric Dogs, and General Relativity |
| topic | Instrumentation and Methods for Astrophysics Computational Physics |
| url | https://arxiv.org/abs/2512.20264 |