Question
Tom B. Brown et al. 2020 describes power law-based empirical scaling laws that restrict analysis of this type of data. This is the canonical type of data whose analysis is tailored via "indexing" and "retrieval" steps in RAG. A mechanism for processing this type of data is parallelized in a "multi-head" approach. Seq2seq ("seek two seek") inspired the paper "Attention Is All You Need," which improved encoder-decoder architecture for handling this type of data. This (*) autoregressive type of data is the focus of tools like PaLM, Chinchilla, and Meta’s Llama. Transformers typically handle this non-visual type of data, which is studied in NLP and processed by LLMs. For 10 points, name this type of data that is processed by translators. ■END■
Buzzes
Summary
Tournament | Edition | Exact Match? | TUH | Conv. % | Power % | Neg % | Average Buzz |
---|---|---|---|---|---|---|---|
2025 PACE NSC | 06/07/2025 | Y | 42 | 95% | 19% | 0% | 95.15 |