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1. Commits on Nov 13, 2026

   • ai-notes: decisions 29-31, NaN and -0.0 against an identity, and index errors

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   • Tensor: select and apply take a 0-d Tensor as their scalar operand

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   • Tensor: notes and user guide take in the SAPS pilot's findings

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   • Tensor: keep the cached selector where it fits, and find values without a search where cheap

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   • Tensor: X | Y and X & Y on their own follow Matrix: BOOL only

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   • ai-notes: the row hash that the Tensor's internal waits build, as a roadmap idea

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   • ai-notes: broadcast unions with broadcast axes split across groups stay unsupported

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   • Tensor: Review 5's nits on wait(), which now returns the Tensor

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   • Tensor: document wait()'s row hash and the choice of no per-mode copies

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   • Tensor: Review 4's wording fixes, and a stolen row keeps its sparsity control

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   • Tensor notes: where TTM's time goes off the stored order, and the A/B of all five

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   • Tensor: sum unsigned data with a row selector typed like it

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   • Tensor: price many relayout targets from one planner search

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   • Tensor: filter a column range of sparse rows in place

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   • Tensor: take a row as a Vector without an extract

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   • Tensor: price the extract by the rows it visits

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   • Tensor: a TTV past 2^60 positions goes through the entries

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   • Tensor: a broadcast ewise_mult with no option left looks up the small side at the entries

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   • Tensor: after a failed compile the array-UDT engine leaves the JIT control at load

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   • ai-notes: the Tensor's benchmarks with the JIT on, run and off

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   • Tensor: the UDT TTM engine leaves the JIT control alone when it declines

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   • Tensor: BOOL selector products with lor_land, which SuiteSparse precompiles

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   • Tensor PageRank notebook: check the CSVs' hashes, not the zip's

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   • ai-notes: name the benchmarked commits by subject, not by id

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   • Tensor notebooks: a quickstart, and multiplex PageRank on EU airlines

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   • Tensor: randomized oracles as slow tests, with teeth

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   • Matrix and Vector isequal / isclose compare with a Tensor too

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   • ai-notes: write the Tensor's benchmarks page

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   • ai-notes: write the SuiteSparse:GraphBLAS wishlist for the Tensor

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   • Add ai-notes for the experimental Tensor

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