Jun. 21 at 2:16 PM
These names sit at different layers of the AI stack, but all share one common theme: accelerating revenue visibility driven by structural demand, not cyclical noise.
$MU is benefiting from HBM-driven memory tightness, turning a historically cyclical business into a pricing-power story.
$ALAB sits in the connectivity layer, still early stage but increasingly embedded in AI data center buildouts with index-driven flow support.
$AVGO is the mature compounding engine-AI revenue scaling fast while free cash flow anchors valuation support.
$AMD is gaining share as inference demand expands and hyperscalers diversify GPU supply chains.
$PLTR remains the software compounding story, with accelerating commercial adoption and steady institutional accumulation.
