Fusion Fund's Lucy Zhang predicts a significant shift in AI infrastructure, with inference computing demands set to surpass training by a 70/30 split. She highlights that communication within data centers consumes vastly more energy than computation itself, suggesting a critical need for advancements in optical communication. Zhang also emphasizes that the primary bottleneck for physical AI is the lack of high-quality, real-world data, rather than model size or compute power, pointing to sectors like healthcare as rich sources for this data. AI
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IMPACT Shifts focus to inference and data quality, potentially altering infrastructure investment and R&D priorities.
RANK_REASON The cluster consists of an opinion piece from an investor discussing future trends in AI infrastructure and data, rather than a direct product release or research finding.