Scaling AI: Discourse and Future Directions

This chapter explores the evolving discourse on AI scaling laws, particularly in relation to large language models. It highlights key concerns regarding parameter limits, data availability, and the potential shift from pre-training to inference that may reshape the competitive landscape. Additionally, it discusses advancements in memory technology and their implications for consumer AI interactions, emphasizing the anticipated breakthroughs and ongoing trends in enterprise applications.

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