Manus, vibe coding, scaling laws and Perplexity’s AI phone
Mixture of Experts
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Reevaluating Scaling Laws in AI
This chapter discusses how DeepSeq challenges traditional scaling laws in machine learning, highlighting that smaller and more efficient models can outperform larger ones. It explores advanced optimization techniques for GPU performance and the importance of data quality and smart training approaches. The conversation emphasizes a shift towards sustainability and efficiency in AI development rather than merely increasing model size.
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