Tanner from Future Investing delivers a midday market monitor reacting to the ongoing AI stock sell-off, with Nvidia at $195, Palantir down to $107, and Cerebras falling below its IPO price. The core thesis: the sell-off is seasonal/technical, not fundamental — Micron's blowout quarter (345% revenue growth, 84.5% gross margins, $17.5B free cash flow) proves AI demand is accelerating, not slowing. He walks through Google and Meta earnings to argue hyperscaler spending is rational and margin-accretive, then frames the drawdowns in names like Palantir as long-term accumulation opportunities.
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Tanner opens the stream visibly rattled by the AI sell-off — Nvidia at $195, Palantir at $107, Apple down 6% — but immediately frames it as a seasonal phenomenon ("sell in May and go away") rather than a fundamental breakdown. He notes the irony: Micron is up 16% on earnings while the broader AI complex bleeds, and SanDisk is up ~20%, confirming that memory/bottleneck plays are being rewarded while the rest of AI gets de-rated. His core argument rests on a chain of reasoning: the hyperscalers (Google, Meta, Microsoft, Amazon) are spending record amounts on AI infrastructure, and that spending is rational because it's producing higher margins and accelerating revenue growth, not destroying value. …
Risk-off in AI/tech with seasonal summer headwinds (June-October historically weak); Micron's blowout quarter is a bright spot but not yet pulling the broader complex higher — the market is in "show me" mode and punishing names without immediate fundamental catalysts. Tactically, this favors accumulation in proven compounders at compressed multiples while avoiding catching falling knives in unprofitable or early-stage AI names.
Over the next several months, the path depends on whether hyperscaler Q2/Q3 earnings confirm the margin-expansion-plus-CapEx-acceleration pattern. If they do, AI stocks should re-rate as the "spending is wasteful" narrative breaks; if growth slows or margins compress, the sell-off could deepen. Micron's guidance raise suggests Q2 hyperscaler prints are more likely to confirm than refute the bull case, but positioning is crowded and the unwind may take time to clear.
Structural view: AI infrastructure spend is in the early-to-middle innings of a decade-long buildout, analogous to cloud computing in the 2010s. The companies that own the bottlenecks (memory, networking, compute) and the hyperscalers that can monetize AI through existing distribution (Google, Meta, Amazon) are structurally positioned to compound. Periodic 30-50% drawdowns in the leading names are features of the path, not evidence the thesis is broken.
Nvidia at $195 looks criminally cheap given the AI demand backdrop.
Speaker asserts the price drop is unjustified relative to fundamentals, without citing specific valuation metrics.
Micron's revenue growth of 345% year-over-year to $41.45 billion dramatically beat Wall Street's $33 billion estimate, and this scale of beat cannot be dismissed as a one-off.
Wall Street expected $33B, Micron did $41.45B — a miss of $7-8B, which is as large as entire quarters for other companies.
The 'sell in May and go away' seasonal weakness narrative is wrong to attribute to any lack of AI demand; all channel checks show Nvidia seeing more customers and backlog is enormous.
The speaker rejects seasonal weakness as indicative of AI demand falling; channel checks show continued customer growth and massive backlogs across Nvidia and cloud hyperscalers.
How can you be confident Wall Street's expectations are right when they have been so wrong on Micron's numbers?
The speaker argues that Wall Street is still behind and that its estimates need time to catch up to Micron's actual results and guidance. He says the company just beat earnings by a large margin, raised guidance, and is still not priced as if growth will continue.
Why is the stock not being treated as hype if people are so excited about it?
He says excitement from individual investors is not the same as market consensus, and the stock is extremely cheap rather than priced like a hype trade. He points to the modest stock reaction after a big earnings beat and raised guidance as evidence.
Why are companies like Amazon, Microsoft, and Google spending so heavily on compute and memory?
The speaker says the spending is justified because those companies can use the compute themselves and also sell it externally. He contrasts that with his greater concern about Meta, where the end-use of the compute is less clear.
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