The AI party is far from over, as $MSFT announced an $80B capex for FY 2025 -- nearly double its $44B in 2024 -- signaling that big tech will keep aggressively ramping up AI investments.

This has major implications for the semiconductor space -- here's how  🧐

• $NVDA -- Massive demand for Blackwell GPUs will arise from AI training & inference at scale.

• $ASML -- Increased production of advanced AI chips will rely heavily on EUV lithography machines.

• $TSM -- Cutting-edge nodes like 3nm will be critical for fulfilling AI chip orders.

• $AVGO -- Networking chips will play a vital role in scaling expanded data center infrastructure.

• $ARM -- Low-power designs may dominate energy-efficient AI servers and edge devices.

• $MRVL -- Interconnect & storage solutions will underpin scaled AI data center operations

• $AMD -- EPYC processors & MI300 GPUs are positioned to gain share in diversified AI hardware.

• $QCOM -- AI-enabled processors could support energy-efficient global AI deployments.

• $MU -- Surging demand for DRAM & NAND will support expanding AI workloads.

• $AMAT -- Chip manufacturing equipment will see heightened demand to support AI production.

• $CDNS & $SNPS -- Advanced design & EDA tools will be indispensable for designing next-gen AI chips.

• $ALAB -- CXL-based connectivity solutions will enable AI-driven workloads across data center architectures.

• $KLAC -- Process control systems will ensure high yields in AI chip production.

• $LRCX -- Etching & deposition tools will be vital for increased semiconductor manufacturing.

• $INTC -- Xeon CPUs & emerging AI GPUs are poised to play a key role in scaling cloud AI.