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Memory & storage · Thesis 06 · settles Oct 27 · 4 days · rung 2/3

Will Seagate's operating cash flow hit at least 36 percent of revenue for the quarter ended October 2, 2026?

How it settles

Divide net cash from operating activities by revenue that Seagate reports for the quarter ended October 2, 2026 on SEC EDGAR. Yes if the ratio is at or above 36.0 percent, no if below. SEC EDGAR, XBRL company facts of Seagate (Forms 10-Q and 10-K)

The exact question and the full rule

Did the net cash from operating activities of Seagate for the quarter ended October 2, 2026 come to at or above 36.0% of its revenue?

Divide the net cash from operating activities by the revenue that Seagate reports for the quarter ended October 2, 2026 in its 10-Q or 10-K filing on SEC EDGAR. The answer is yes if the ratio is at or above 36.0%; no if it is below 36.0%.

If the source is late or silent: If Seagate has not filed by November 18, 2026, or a filing restates a period the rule reads, the test is inconclusive, and the Result says what was read and what was missing.

If no

Memory export records do not materialize

No if Seagate's cash from operations falls below 36 percent of revenue as margins or working capital shift.

If yes

Inference demand outgrows training

Yes if Seagate's cash from operations lands at or above 36 percent of revenue, matching its strong prior quarter.

50%
NoYes

No position, no money. The crowd, the Call and the machines appear after you lock your number.

The case · 2 people · 2 minutes
Memory export records do not materialize1 people argue noInference demand outgrows training1 people argue yes
Stronger if no · 1 people

Memory export records do not materialize

Kerrisdale Capital Management LLCSep 1

Training workloads require high-end GPUs and can be run remotely, aligning with CoreWeave's model of renting expensive, cutting-advantage capacity on long-term contracts. Inference, by contrast, is steady-state, latency-sensitive, and cost-conscious…

Stronger if yes · 1 people

Inference demand outgrows training

GaetanoMay 14

Training is compute-bound and GPU-focused, but inference is memory-bound and latency-sensitive. As AI moves into production across enterprises, the full system around the GPU matters more: memory capacity, context length, responsiveness, and data…

What would change the Call
  • The operating cash flow and revenue figures Seagate reports for the quarter ended October 2, 2026 would move the call.
The Call · Thesis 06 · Inference demand outgrows training

The house leans to "Inference demand outgrows training".

The dossier · 5 minutes
The machines' reasons

3 models ran this one. Their numbers and reasons appear after you lock yours.

The thesis

Will Korea's monthly memory semiconductor exports set a new all-time monthly record in any month between 2026-11-15 and 2027-12-31?

Inference workloads are read by some as memory-bound rather than compute-bound, pulling HBM, DRAM and CXL demand toward record levels, while this side tests whether Korean export data actually registers a new all-time monthly high.