Dontopedia

reference implementation

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reference implementation has 12 facts recorded in Dontopedia across 6 references, with 1 live disagreement.

12 facts·10 predicates·6 sources·1 in dispute

Mostly:uses whole model conversion(2), upcasts loss to float32(1), lacks per layer dtype param(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (8)

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.

comparisonComparison(1)

hadBugsFromReferenceHad Bugs From Reference(1)

intendedAsIntended As(1)

originatesFromOriginates From(1)

presupposesBugsExistedPresupposes Bugs Existed(1)

providesKeyPatternsProvides Key Patterns(1)

servesAsServes As(1)

usesDtypeFlowFromWeightsUses Dtype Flow From Weights(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
Uses Whole Model ConversionConvert Model to Bf16[1]
Uses Whole Model ConversionConvert Model to Fp16[1]
Upcasts Loss to Float32Gradient Precision[1]
Lacks Per Layer Dtype ParamDtype Flows From Weights[1]
Achieved Whenbehavior and performance are proven[2]
Contingent onproven behavior and performance[2]
Used for Checkingtrue[3]
Has Same IssueHarmonic Gpt[4]
Rdf:typeSoftware Artifact[6]
Becomes Statusreference implementation[6]
Condition for StatusBehavior and Performance Proof[6]

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.

upcastsLossToFloat32blah/watt-activation/part-107
ex:gradient-precision
lacksPerLayerDtypeParamblah/watt-activation/part-107
ex:dtype-flows-from-weights
usesWholeModelConversionblah/watt-activation/part-107
ex:convert-model-to-bf16
usesWholeModelConversionblah/watt-activation/part-107
ex:convert-model-to-fp16
achievedWhenblah/watt-activation/part-461
behavior and performance are proven
contingentOnblah/watt-activation/part-461
proven behavior and performance
usedForCheckingblah/watt-activation/part-540
true
hasSameIssueblah/watt-activation/106
ex:harmonic-gpt
labelblah/watt-activation/107
reference implementation
typeblah/watt-activation/459
ex:SoftwareArtifact
becomesStatusblah/watt-activation/459
reference implementation
conditionForStatusblah/watt-activation/459
ex:behavior-and-performance-proof

References (6)

6 references
  1. [1]Part 1074 facts
    ctx:discord/blah/watt-activation/part-107
  2. [2]Part 4612 facts
    ctx:discord/blah/watt-activation/part-461
  3. [3]Part 5401 fact
    ctx:discord/blah/watt-activation/part-540
  4. [4]1061 fact
    ctx:discord/blah/watt-activation/106
    • full textwatt-activation-106
      text/plain3 KBdoc:agent/watt-activation-106/1cc0dbfa-458e-4f02-b7b6-1c37e3d3a7f8
      Show excerpt
      [2026-03-08 19:52] xenonfun: ``` total used free wired compressed 98304Mi 88429Mi 8982Mi 59988Mi 100Mi ``` (files: Screenshot_2026-03-08_at_3.52.13_PM.png) [2026-03-08 19:57] xenon
  5. [5]1071 fact
    ctx:discord/blah/watt-activation/107
    • full textwatt-activation-107
      text/plain2 KBdoc:agent/watt-activation-107/7f46d3a6-a9e5-4ccd-b3ab-17637a2a1afc
      Show excerpt
      [2026-03-08 20:49] xenonfun: performance impact? ⏺ Negligible. The current forward already does heavy _gated_cumsum on (B,T,H,K,d_h) tensors. The fix just adds one extra cumsum on a (T,K) ones tensor to get position-dependent effective cou
  6. [6]4593 facts
    ctx:discord/blah/watt-activation/459
    • full textwatt-activation-459
      text/plain2 KBdoc:agent/watt-activation-459/5a24a4b5-2967-488c-8337-25c0e0516514
      Show excerpt
      [2026-03-21 16:37] xenonfun: ``` FedSym Port: symbiogenesis → HarmonicRust Context The Python symbiogenesis project (github.com/MonumentalSystems/symbiogenesis) implements a population-based neural architecture evolution framework. Neur

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