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In 2016, TSMC developed and named its InFO FOWLP technology, and applied it to the A10 processor used in the iPhone 7. TrendForce points out that since then, OSAT providers have been striving to develop FOWLP and FOPLP technologies to offer more cost-effective packaging solutions.
TrendForce reveals that although the overall environment this year has been impacted by AI budget constraints—leading to slower-than-expected growth for general—recent procurement strength for related components such as BMCs and new CPUs indicates an improving trend for new server platforms among OEMs and CSPs. Additionally, surveys of ODM supply chains reveal that server shipments, after a seasonal dip in the first quarter, are expected to show sequential growth in the second and third quarters.
TrendForce reports that while the enterprise sector continues to invest in server infrastructure—especially with the rising adoption of AI driving demand for enterprise SSDs—the consumer electronics market remains lackluster. This, combined with NAND suppliers aggressively ramping up production in the second half of the year, is expected to push the NAND Flash sufficiency ratio up to 2.3% in the third quarter, curbing the blended price hike to a modest 5–10%.
TrendForce reports that a recovery in demand for general servers—coupled with an increased production share of HBM by DRAM suppliers—has led suppliers to maintain their stance on hiking prices. As a result, the ASP of DRAM in the third quarter is expected to continue rising, with an anticipated increase of 8–13%. The price of conventional DRAM is expected to rise by 5–10%, showing a slight contraction compared to the increase in the second quarter.
TrendForce has observed that in 2024, major CSPs such as Microsoft, Google, Meta, and AWS will continue to be the primary buyers of high-end AI servers, which are crucial for LLM and AI modeling. Following establishing a significant AI training server infrastructure in 2024, these CSPs are expected to actively expand into edge AI in 2025. This expansion will include the development of smaller LLM models and setting up edge AI servers to facilitate AI applications across various sectors, such as manufacturing, finance, healthcare, and business.
