Dontopedia

MLX

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

MLX has 15 facts recorded in Dontopedia across 5 references, with 1 live disagreement.

15 facts·9 predicates·5 sources·1 in dispute

Mostly:primary characteristic(3), contextualizes apple silicon inference(1), rdf:type(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (5)

Other subjects in dontopedia point AT this entity as a value. These are inverse relationships — e.g. "X motherOf this subject" — and answer questions the forward facts can't. Grouped by predicate.

assumesExistenceOfAssumes Existence of(1)

attributesOptimizationToAttributes Optimization to(1)

correctForFrameworkCorrect for Framework(1)

describesLimitationOfDescribes Limitation of(1)

referencesAppleMLXLibraryReferences Apple Mlx Library(1)

Other facts (11)

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.

11 facts
PredicateValueRef
Primary Characteristicdense tensor compute[4]
Primary Characteristiclazy graph construction[4]
Primary Characteristicdynamic execution with optional compilation[4]
Contextualizes Apple Silicon Inferencenull[1]
Rdf:typeSoftware Framework[2]
Supports Complex Numberstrue[4]
Supports Sparse Tensorsnot-as-primary-strength[4]
Built Around Dense Arraystrue[4]
Has Lazy Computation Graphtrue[4]
Lazy Graph Is Not Sparse Graph Executiontrue[4]
Execution BackendMetal[4]

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.

contextualizesAppleSiliconInferenceblah/watt-activation/part-170
null
labelblah/watt-activation/34
MLX
typeblah/watt-activation/34
ex:SoftwareFramework
labelblah/watt-activation/78
MLX
labelblah/watt-activation/261
MLX
primaryCharacteristicblah/watt-activation/261
dense tensor compute
primaryCharacteristicblah/watt-activation/261
lazy graph construction
primaryCharacteristicblah/watt-activation/261
dynamic execution with optional compilation
supportsComplexNumbersblah/watt-activation/261
true
supportsSparseTensorsblah/watt-activation/261
not-as-primary-strength
builtAroundDenseArraysblah/watt-activation/261
true
hasLazyComputationGraphblah/watt-activation/261
true
lazyGraphIsNotSparseGraphExecutionblah/watt-activation/261
true
executionBackendblah/watt-activation/261
Metal
labelblah/watt-activation/295
MLX

References (5)

5 references
  1. [1]Part 1701 fact
    ctx:discord/blah/watt-activation/part-170
  2. [2]342 facts
    ctx:discord/blah/watt-activation/34
    • full textwatt-activation-34
      text/plain2 KBdoc:agent/watt-activation-34/d27c3240-c724-48a3-81cc-130cc7f77918
      Show excerpt
      [2026-03-07 00:11] xenonfun: Deep dive LR schedule gene system in symbiogenesis · 14 tool uses · 65.8k tokens │ ⎿  Done └─ Deep dive SymbioGPT training pipeline LR handling · 15 tool uses · 64.4k tokens ⎿  Done ⏺ Now I have ev
  3. [3]781 fact
    ctx:discord/blah/watt-activation/78
    • full textwatt-activation-78
      text/plain2 KBdoc:agent/watt-activation-78/29aa0ca9-9bd7-4e6c-a0f9-62769e7f15b8
      Show excerpt
      [2026-03-07 19:03] xenonfun: ``` 25/25 still passing. Re your points: - 7.1: Added mx.contiguous() before folding in __call__. No need in step() since the squeeze already collapses the length-1 dim, producing contiguous output. - 7.2
  4. [4]26110 facts
    ctx:discord/blah/watt-activation/261
    • full textwatt-activation-261
      text/plain2 KBdoc:agent/watt-activation-261/cff3e001-d69b-4ec5-ad12-55031acbf11e
      Show excerpt
      [2026-03-13 01:44] xenonfun: ``` • Almost all of it is the learned position embedding. Breakdown for the current lohe_spherical + lohe_v3 run at d=832, L=6, vocab=8192, seq=131072: - pos_emb: 109,051,904 params, 87.23% - attention b
  5. [5]2951 fact
    ctx:discord/blah/watt-activation/295
    • full textwatt-activation-295
      text/plain3 KBdoc:agent/watt-activation-295/3934680b-d58b-4c73-8470-2c337c1a045e
      Show excerpt
      [2026-03-14 04:39] xenonfun: ```❯ ⏺ Now I have the full picture. Here's my MLX performance review: Spherical VQ — MLX Performance Review Good patterns: 1. _l2_normalize uses + eps inside sqrt (line 38) — matches lohe_normalize sema

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