Micron's memory demand could outlast current forecasts because sparse AI models must keep all their weights in HBM even when only a fraction is active in computation. Kimi's 2.8T-parameter model activates 104B per token but needs roughly 3TB to hold its weights; serving millions requires parallel copies. If models reach 100T parameters by 2030, each copy could need about 100TB. Micron should continue to outperform the market. x.com 

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.com 

Networking, power and compute look more durable than cyclical memory in the AI buildout. Lumentum's revenue compounded year after year across the 2010s and 2020s, unlike Micron's; AWS revenue also compounded. Lumentum, Nebius, Bloom Energy and Credo should heavily outperform SanDisk and Micron from here, though AI itself remains heavily doubted. x.com  x.com 

Micron's ordinary memory could see tighter supply because HBM consumes far more factory capacity than conventional DRAM. Meeting AI demand could thus extend Micron's opportunity beyond AI memory. x.com 

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.com 

Micron faces a tough road through 2027 because the current AI spending path is not economically sustainable and tech progress can undercut memory demand. Micron's weak price action on blowout earnings is a tell. Token usage will keep rising, but Nvidia is already pivoting to LPUs with Groq, and tech progress should never be underestimated. x.com  x.com  x.com 

Micron's bet on 3D DRAM over rivals' 4F2 could give it an edge as AI memory demand rises. Micron expects shortages for at least two more years: HBM per GPU rose 3.6x from H100 to B300, inference memory per server doubled in three years, and agent context grows about 30x annually. It plans further 6F2 nodes, 1-delta DRAM in 2H27 and 400-plus-layer G11 NAND in 2027; processor-stacked vHBM is targeted around 2028. If Micron is right, rivals are spending on the wrong path. Overweight Micron. x.com 

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.com 

Inflation, rising rates, Chinese competition and rising AI-related financial costs are pressuring the memory market. Micron, Samsung and SK hynix look exposed; waiting for the cycle to turn. x.com  x.com 

A worsening memory shortage in 2027 could favor Micron, SanDisk and SK hynix as AI stocks. Samsung warns that the shortage will worsen then. x.com