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#434 – Aravind Srinivas: Perplexity CEO on Future of AI, Search & the Internet
Lex Fridman Podcast
Importance of Scale and Data Quality in Model Training
Model training has evolved to focus on training models on large datasets with trillions of tokens and parameters, emphasizing the need for data quality and quantity, as well as evaluation on reasoning benchmarks. Attention alone is not enough; scaling up with attention, parallel computation, transformers, and unsupervised pre-training is crucial for breakthroughs in language model advancements. RLHF is significant, serving as a valuable addition to the model training process.
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