BWhat changed
Trained and evaluated the dense 540-billion-parameter PaLM language model using the Pathways system, reporting few-shot performance across language and reasoning tasks.
Scientific scope
Trained and evaluated the dense 540-billion-parameter PaLM language model using the Pathways system, reporting few-shot performance across language and reasoning tasks. Scope limitation: PaLM's benchmark findings and compute configuration are paper-specific; this record is not PaLM 2 or a claim that scaling alone solves general reasoning.
Evidence
The retained primary-source abstract, bibliographic record and stated review scope support this provisional assessment. No independent experimental replication by WRS is claimed. PaLM's benchmark findings and compute configuration are paper-specific; this record is not PaLM 2 or a claim that scaling alone solves general reasoning.
Contributors
- The named authors listed in the linked research record · SCIENCE: Complete source byline retained in the research record; human research direction, method development and evaluation. Individual labor shares are not measured.
- Chowdhery and colleagues: PaLM language-model scaling with Pathways — original paper
- Chowdhery and colleagues: PaLM language-model scaling with Pathways — company research page
Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.
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