Let me analyze this portfolio that's focused on suppliers to AI/GPU needs, specifically looking for esoteric/downstream companies related to LLM use cases.
Current Portfolio Analysis:
- ONTO: Onto Innovation - semiconductor process control equipment
- RMBS: Rambus - memory interface technology and IP
- VRT: Vertiv Holdings - data center infrastructure (power/cooling)
- MU: Micron Technology - memory (DRAM, NAND)
- AMKR: Amkor Technology - semiconductor packaging/testing
- MRVL: Marvell Technology - data infrastructure semiconductor solutions
- AEHR: Aehr Test Systems - semiconductor test & burn-in equipment
These align well with the AI infrastructure strategy. The news about MU is particularly interesting - they're buying a fab for $1.8B to boost DRAM capacity due to AI demand, and they've flagged an "unprecedented memory shortage" that will stretch beyond 2026.
Key observations:
1. Memory is indeed a major bottleneck for LLMs - the news confirms this with MU's shortage warnings
2. The portfolio is well-positioned in memory (MU, RMBS) and semiconductor equipment/testing
3. VRT might not align perfectly with the strategy (it's more power/cooling infrastructure)
4. AMKR is down 8.2% - need to consider wash sale rules since it's been sold recently
Market conditions:
- VIX spiked 19.51% indicating increased volatility
- Major indices slightly down
- Trump tariff concerns affecting sentiment
Strategy alignment:
The portfolio is actually quite well-aligned with finding esoteric AI infrastructure plays. Memory (MU, RMBS) is crucial for LLMs, and semiconductor testing/packaging (AEHR, AMKR, ONTO) is essential for AI chip production.
Cash deployment:
With only $2,384.33 in cash (2.3% of portfolio), there's limited room for new positions. I'll recommend being conservative with 0.8 deployment.
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MU should remain a core holding given the bullish fab acquisition and confirmed memory shortage extending into 2026. VRT's general data center focus doesn't fit the AI-specific thesis as tightly, so trimming 50% of that position makes sense to free up capital for more targeted opportunities. RMBS and ONTO are essential to the strategy—memory interfaces and process control are both critical bottlenecks in AI chip production. AEHR's strong performance reflects the demand for test systems in this space, so maintaining that position is warranted. MRVL should stay despite the current loss, as data infrastructure semiconductors remain foundational to the thesis.
AMKR's packaging and testing capabilities are vital for AI chips, and the wash sale implications make selling inadvisable. With limited dry powder even after the VRT reduction, I should focus new capital on memory-specific plays and advanced packaging companies that directly address AI infrastructure constraints rather than spreading across too many positions.