Dontopedia

Mlx Branch

From Dontopedia, the open, paraconsistent wiki. (Last updated 2026-06-06.)

Mlx Branch has 10 facts recorded in Dontopedia across 2 references, with 1 live disagreement.

10 facts·8 predicates·2 sources·1 in dispute

Mostly:contains code(3), lacks training loop(1), contains benchmark(1)

Maturity scale raw canonical shape-checked rule-derived certified

Other facts (10)

The long tail: predicates that appear too rarely to warrant their own section. Filter or scroll to find a specific one. Each row links to its source.

10 facts
PredicateValueRef
Contains CodeAttention Layers[2]
Contains CodeModel Code[2]
Contains CodeBenchmark Code[2]
Lacks Training LoopMlx Training Loop[1]
Contains BenchmarkTheir Benchmark[1]
Contains ModelTheir Model[1]
Incomplete for TrainingTraining[1]
Lacks Mx Eval DisciplineMx Eval[1]
Contains Attention LayersAttention Layers[1]
Lacks CodeTraining Loop[2]

Timeline

Timeline axis is valid_time — when each source says the fact was true in the world, not when Dontopedia learned about it. Retracted rows are kept for provenance; coloured stripes indicate the context kind.

lacksTrainingLoopblah/watt-activation/part-105
ex:mlx-training-loop
containsBenchmarkblah/watt-activation/part-105
ex:their-benchmark
containsModelblah/watt-activation/part-105
ex:their-model
incompleteForTrainingblah/watt-activation/part-105
ex:training
lacksMxEvalDisciplineblah/watt-activation/part-105
ex:mx-eval
containsAttentionLayersblah/watt-activation/part-105
ex:attention-layers
containsCodeblah/watt-activation/105
ex:attention-layers
containsCodeblah/watt-activation/105
ex:model-code
containsCodeblah/watt-activation/105
ex:benchmark-code
lacksCodeblah/watt-activation/105
ex:training-loop

References (2)

2 references
  1. [1]Part 1056 facts
    ctx:discord/blah/watt-activation/part-105
  2. [2]1054 facts
    ctx:discord/blah/watt-activation/105
    • full textwatt-activation-105
      text/plain3 KBdoc:agent/watt-activation-105/561920dc-7f65-4ab4-80fa-8e3162aa9046
      Show excerpt
      [2026-03-08 19:26] xenonfun: ``` What They're Leaving on the Table 1. No mx.compile — Their benchmark and model run eagerly. From our experience with AnchorKAN at similar scale, compiled step gives ~1.5-2x throughput improvement on M

See also

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