Astera Labs and Montage Technology win the memory redesign rather than the shortage itself. They don't sell memory but determine how much memory everyone else needs to buy, a different kind of moat from that of memory producers. x.comÂ
Matthew Tuttle
CEO & CIO of Tuttle Capital Management, Publisher of Daily H.E.A.T.
Inference's move toward edge devices and dense, memory-hungry racks should drive demand for specialized chips, links, power delivery and cooling. McKinsey projects inference at 60% of AI computing demand by 2030. Ambarella makes on-device AI chips; Astera Labs links GPUs, memory and networks; Credo supplies short copper connections; Rambus earns from memory interfaces; Navitas reduces power waste; Modine cools dense racks; and Super Micro builds inference-specific server racks at volume. x.com … Show more
Montage Technology's strength in memory interfaces is confirmed by the South Korean investigation into it. On top of that, it addresses the huge demand runways of CXL and PCIe retimers, two links AI scale-up cannot bypass. x.comÂ
Astera Labs carries a huge premium for flawless execution against a CXL market that is small near term. Switch-based CXL memory pooling capturing $15-16B in 2026-2028 is low probability: Marvell guides its XConn switch business to only about $100M by fiscal 2028, PCIe included. Pooling software likely stays immature into 2028, per a Samsung white paper, and Nvidia is contesting the warm KV-cache tier. Astera does CXL best, but SK hynix and Micron offer better risk-adjusted returns. x.com x.comÂ
Agentic AI's repeated context favors cache memory and storage demand for Micron, SK hynix and Sandisk over fresh GPU computation. Per @demian_ai, about 95% of input tokens for DeepSeek V4.1 Flash on OpenRouter were cache hits; storage matters unless routing and caching keep almost everything in GPU memory. New products such as 3D DRAM and HBM-on-logic could be the final trigger for a full memory-stock re-rating. x.com x.comÂ
Kimi K3's engineering workarounds for memory limits should lift demand across AI infrastructure suppliers, and more such innovations are expected. Moving prompt history to CPU memory favors Astera Labs, with a 2027 custom Leo CXL design win, and perhaps Penguin Solutions. NVMe overflow memory favors Phison. Denser racks lift Semtech and Credo interconnects. Mass sandboxes favor JFrog and Cloudflare. Rambus supplies memory buffer chips; cluster migrations favor Lumentum's optical switching. x.com … Show more
Micron and SK hynix pricing in a memory shortage past 2030 extends the memory-cycle case beyond the Street's 2028 expectation. SK hynix's record quarter adds evidence: per Wall St Engine, revenue rose 328% to $78.9B, operating profit rose 632% to $62.8B, and operating margin hit 80%. Agentic and physical AI could add demand as they roll out. x.com x.comÂ
Memory pooling and compute should lead the next rally because memory supply simply isn't there. Apple's reported lobbying to buy from CXMT is about missing supply, not price, since CXMT sells at only about a 5% discount, and Samsung and SK hynix plan two massive new fabs as a Korean national project, a sign countries treat the buildout as existential. Astera Labs, Credo, Penguin Solutions and Marvell are the memory pooling plays, and Credo offers good value after quarter-end rebalancing hit it. … Show more
High-bandwidth memory supply may not keep pace with AI demand, supporting the memory makers. Anthropic's S-1 says SK hynix, Samsung and Micron are expanding capacity, but warns that large buyers or competitors could reserve much of the available output. x.comÂ
Astera Labs is positioned to benefit from the next breakout in AI infrastructure because memory is becoming the biggest problem for hyperscalers, and Astera can deliver major improvements and efficiency gains there. The stock has been incredibly strong and is forming a tight flag; a break should bring $400 soon. x.com x.com x.comÂ
Astera Labs and Montage Technology are positioned to benefit as trillion-parameter open-source models push AI inference bottlenecks from compute to memory. Open models grew from 1T to 2.8T parameters in under a year and now rival frontier models. In MoE models over 98% of expert weights are cold at any moment, so keeping hot experts in HBM and warmer ones in CXL-attached DDR5 can cut costs sharply. Astera Labs leads CXL controllers for global hyperscalers, Montage for China's supply chain. x.comÂ