"In Meta's case, it looks like a consolidation and reprioritization issue. Meta has hundreds of separate AI initiatives spanning Llama, infrastructure, content moderation, recommendation systems, and ad optimization. The 600 jobs being cut are largely from overlapping research or support teams as Meta shifts from "AI research mode" to "AI productization mode." Once the models are trained and deployed, you simply don't need the same headcount to maintain that velocity."
"Think of it like the moment after an airplane reaches cruising altitude: you need fewer hands in the cockpit. The heavy lift training, data labeling, model architecture is done. Now the focus is on efficiency, inference, and monetization. More broadly, all the major AI players - Meta, Google, Microsoft, Broadcom - are demonstrating the same pattern. They're investing billions in infrastructure while trimming the human layers that are being"
Major profitable tech companies are cutting staff despite rapid AI-driven growth because AI automation and internal consolidation reduce labor needs. Meta cut 600 roles from its Superintelligence Labs as teams overlap and priorities shift from research to productization. Once models are trained and deployed, fewer engineers are required due to automated internal tools handling tasks such as data labeling and support. Companies invest heavily in infrastructure while streamlining human layers and management. The shift focuses on inference efficiency, monetization, and operational scalability, transforming the cost structure of technology and prompting workforce restructuring across Meta, Google, Microsoft, and Broadcom.
Read at Business Insider
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