Scaling up language models has been shown to predictably improve performance and sample efficiency on a wide range of downstream tasks. Thus, emergent abilities cannot be predicted simply by extrapolating the performance of smaller models.
This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.
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| Category | 🤖 Artificial Intelligence |
| Published | Jun 15, 2022 |
| Journal | arXiv (Cornell University) |
| Authors | Wei, Jason, Yi Tay, Rishi Bommasani, Colin Raffel, Barret Zoph |
| DOI | 10.48550/arxiv.2206.07682 |
| Citations | 1,030 |
| Source | OpenAlex |