Dontopedia

Symbiogenesis

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

Symbiogenesis has 207 facts recorded in Dontopedia across 38 references, with 13 live disagreements.

207 facts·178 predicates·38 sources·13 in dispute

Mostly:rdf:type(6), has per seed margins vs fedprox ft(5), analogous to(3)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (51)

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.

comparesCompares(4)

containsTermContains Term(3)

inspiredByInspired by(2)

usedByUsed by(2)

advocatesForAdvocates for(1)

affiliatedWithTeamDevelopingAffiliated With Team Developing(1)

appliesToModuleApplies to Module(1)

appliesToModulesApplies to Modules(1)

attemptedInformationRetrievalAttempted Information Retrieval(1)

behindFeatureFlagBehind Feature Flag(1)

canJoinPopulationAtAnyTimeInCan Join Population at Any Time in(1)

claimsClaims(1)

comparesToConceptCompares to Concept(1)

conductsReplicationStudyConducts Replication Study(1)

confirmsInsightConfirms Insight(1)

cooccursWithCooccurs With(1)

decouplesDecouples(1)

derivedFromLibraryDerived From Library(1)

developingDeveloping(1)

emphasizesInsightEmphasizes Insight(1)

firstExplainedInDarwinianTermsFirst Explained in Darwinian Terms(1)

focusesOnTopicFocuses on Topic(1)

hasResearchFocusOnHas Research Focus on(1)

implicatesEvolutionaryProcessImplicates Evolutionary Process(1)

includeInclude(1)

includesIncludes(1)

involvesDecouplingOfInvolves Decoupling of(1)

isFarSlowerThanIs Far Slower Than(1)

isGenuinelyIs Genuinely(1)

isInspiredByIs Inspired by(1)

isOperationalDomainOfIs Operational Domain of(1)

isRepositoryForIs Repository for(1)

isSpeedInBetweenIs Speed in Between(1)

isSuitableForScalingIs Suitable for Scaling(1)

isUsedInIs Used in(1)

makesPitchMakes Pitch(1)

neverSeeEachOthersDataInNever See Each Others Data in(1)

neverSeesRawDataInNever Sees Raw Data in(1)

presupposesExistenceOfPresupposes Existence of(1)

presupposesSymbiogenesisViabilityPresupposes Symbiogenesis Viability(1)

readyNowReady Now(1)

slowerThanSlower Than(1)

structureStructure(1)

usesAsMetaphorUses As Metaphor(1)

Other facts (199)

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.

199 facts
PredicateValueRef
Rdf:typeAlgorithm[30]
Rdf:typeAlgorithm[31]
Rdf:typeSearch Term[33]
Rdf:typeLibrary[34]
Rdf:typeDependency[37]
Rdf:typeSoftware Module[38]
Has Per Seed Margins Vs Fedprox Ft+1.2pp[25]
Has Per Seed Margins Vs Fedprox Ft+2.1pp[25]
Has Per Seed Margins Vs Fedprox Ft+1.1pp[25]
Has Per Seed Margins Vs Fedprox Ft+2.7pp[25]
Has Per Seed Margins Vs Fedprox Ft+1.8pp[25]
Analogous toContinual Learning in AI[2]
Analogous toMitochondria[9]
Analogous toMitochondria[27]
Avoidsmulti-round synchronization[25]
Avoidswaiting for stragglers[25]
Avoidsproximal term requiring the global model broadcast back[25]
Contrasts WithGradual Mutations and Individual Competition[3]
Contrasts WithStandard Methods[9]
Has Alternative NameSerial Endosymbiotic Theory[3]
Has Alternative NameEndosymbiotic Theory[3]
OutperformsNeat Style Nas Baseline[13]
OutperformsTensorneat Hybrid[23]
Avoids Need torestart training[25]
Avoids Need tosynchronize rounds[25]
Benefits FromClient Diversity[25]
Benefits FromDiversity[31]
Exceeds Capabilities ofFedprox[25]
Exceeds Capabilities ofScaffold[25]
Faster ThanNeat in Unit[29]
Faster ThanNeat Algorithm[30]
Has Comparison Advantage OverFedprox[31]
Has Comparison Advantage OverScaffold[31]
In Neural NetworksNeural Networks[1]
Commits toBio Inspired AI Ontology[1]
Has Git Hubgithub.com/MonumentalSystems/Symbiogenesis[1]
ExploresIndependent Neural Modules Merging[1]
AddressesCatastrophic Forgetting[1]
Is Novel Framework forContinual Learning[1]
Is Noveltrue[1]
Preserves Previously Learned CapabilitiesCo Adapting Neural Modules[1]
PresupposesBiological Symbiogenesis Exists[1]
Inspired byBiological Symbiogenesis[1]
Is Evaluated Asnovel metaphor[2]
Is Novel Metaphor forSolving Catastrophic Interference[2]
Embodies Teleological PreservationFunction[2]
IsContinual Learning[2]
Provides Biological Inspiration forEvolving AI Project[2]
InvolvesMerger of Organisms[2]
Presupposes Existence ofEndosymbiosis Events[3]
Superior toNatural Selection Alone[3]
Draws From Historical Context ofEarly 20th Century Biology[3]
Demonstrates ThatMajor Evolutionary Advancements From Symbiotic Mergers[3]
Inspires Continual Learning SolutionLisa Watts AI Research[3]
Is Possible forOther Organelles[3]
Is Evaluated As Leadingtrue[3]
Positively Evaluated byText[3]
Is Leading Evolutionary Theory ofOrigin of Eukaryotic Cells From Prokaryotic Organisms[3]
Ontologically Commits toSymbiosis As Evolutionary Driver[3]
Axiological Value ofCooperation Over Competition[3]
Is Metaphor forContinual Learning in AI[3]
Models Biological Processsymbiogenesis[4]
Commits to Evolutionary Paradigmnull[5]
Is Ongoing Processnull[6]
Achieves Convergence in Less Timetrue[7]
Uses Fusion in Distillationtrue[7]
Uses Dynamic Lrtrue[7]
Biologically InspiredEndosymbiosis[7]
Lacks Optimizationstrue[7]
Achieves Convergence in Less Computetrue[7]
Never Overfits Due toGelation Signal[7]
Performs Better Wide Than Deeptrue[7]
Superior to Standard Training on Some Taskstrue[7]
Close Replication on Cifar10~CLOSE[7]
Is Nas Methodtrue[7]
Achieves Convergence in Less Paramstrue[7]
Replicates Paper on MnistYES[7]
Uses Fusion in Moetrue[7]
Related toSymbio[8]
Has BranchMetalverificationreplication[8]
Connects Tasks atBoundary[9]
Implies Modular ArchitectureStructural Territory[9]
Teleologically Separates TasksTask[9]
Is Key Insightconfirmed[9]
Protects Knowledge by SeparationOld Knowledge[9]
Gives to Each TaskStructural Territory[9]
Provides Ga ResultsPer Layer Lr Multipliers[10]
Compared toSymbiogpt[11]
Superior in SpeedNeat in Unit[12]
Has Mean Wall Time Per Seed2.7s[12]
Is Much Faster Per Seed ThanNeat in Unit[12]
Completes Tasks in Time1-2 seconds of log time[12]
Has Efficiency AdvantageNeat in Unit[12]
Is Slightly Ahead onFinal Combined Accuracy[12]
Is Faster by Factor357x[12]
Processes Num Tasks5[12]
Starts ConditionFast Phase[12]
Is Fusion Based Evolutionary Searchnull[13]
Is Often Stronger Than Differentiable Nas Baselinesnull[13]
Used Less Wall Clock Time on Average ThanTensorneat Hybrid Search[13]

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.

inNeuralNetworkslisa-watts/resume-professional-profile
ex:neural-networks
commitsTolisa-watts/resume-professional-profile
ex:bio-inspired-ai-ontology
hasGitHublisa-watts/resume-professional-profile
github.com/MonumentalSystems/Symbiogenesis
exploreslisa-watts/resume-professional-profile
ex:independent-neural-modules-merging
addresseslisa-watts/resume-professional-profile
ex:catastrophic-forgetting
isNovelFrameworkForlisa-watts/resume-professional-profile
ex:continual-learning
isNovellisa-watts/resume-professional-profile
true
preservesPreviouslyLearnedCapabilitieslisa-watts/resume-professional-profile
ex:co-adapting-neural-modules
presupposeslisa-watts/resume-professional-profile
ex:biological-symbiogenesis-exists
inspiredBylisa-watts/resume-professional-profile
ex:biological-symbiogenesis
isEvaluatedAslisa-watts/research-catastrophic-forgetting
novel metaphor
isNovelMetaphorForlisa-watts/research-catastrophic-forgetting
ex:solving-catastrophic-interference
embodiesTeleologicalPreservationlisa-watts/research-catastrophic-forgetting
ex:function
islisa-watts/research-catastrophic-forgetting
ex:continual-learning
providesBiologicalInspirationForlisa-watts/research-catastrophic-forgetting
ex:evolving-ai-project
involveslisa-watts/research-catastrophic-forgetting
ex:merger-of-organisms
analogousTolisa-watts/research-catastrophic-forgetting
ex:continual-learning-in-ai
presupposesExistenceOflisa-watts/research-symbiogenesis
ex:endosymbiosis-events
superiorTolisa-watts/research-symbiogenesis
ex:natural-selection-alone
drawsFromHistoricalContextOflisa-watts/research-symbiogenesis
ex:early-20th-century-biology
contrastsWithlisa-watts/research-symbiogenesis
ex:gradual-mutations-and-individual-competition
demonstratesThatlisa-watts/research-symbiogenesis
ex:major-evolutionary-advancements-from-symbiotic-mergers
inspiresContinualLearningSolutionlisa-watts/research-symbiogenesis
ex:lisa-watts-ai-research
isPossibleForlisa-watts/research-symbiogenesis
ex:other-organelles
isEvaluatedAsLeadinglisa-watts/research-symbiogenesis
true
hasAlternativeNamelisa-watts/research-symbiogenesis
ex:serial-endosymbiotic-theory
hasAlternativeNamelisa-watts/research-symbiogenesis
ex:endosymbiotic-theory
positivelyEvaluatedBylisa-watts/research-symbiogenesis
ex:text
isLeadingEvolutionaryTheoryOflisa-watts/research-symbiogenesis
ex:origin-of-eukaryotic-cells-from-prokaryotic-organisms
ontologicallyCommitsTolisa-watts/research-symbiogenesis
ex:symbiosis-as-evolutionary-driver
axiologicalValueOflisa-watts/research-symbiogenesis
ex:cooperation-over-competition
isMetaphorForlisa-watts/research-symbiogenesis
ex:continual-learning-in-ai
modelsBiologicalProcessblah/training-and-evals/part-16
symbiogenesis
commitsToEvolutionaryParadigmblah/training-and-evals/part-20
null
isOngoingProcessblah/training-and-evals/part-22
null
achievesConvergenceInLessTimeblah/watt-activation/part-1
true
usesFusionInDistillationblah/watt-activation/part-1
true
usesDynamicLrblah/watt-activation/part-1
true
biologicallyInspiredblah/watt-activation/part-1
ex:endosymbiosis
lacksOptimizationsblah/watt-activation/part-1
true
achievesConvergenceInLessComputeblah/watt-activation/part-1
true
neverOverfitsDueToblah/watt-activation/part-1
ex:gelation-signal
performsBetterWideThanDeepblah/watt-activation/part-1
true
superiorToStandardTrainingOnSomeTasksblah/watt-activation/part-1
true
closeReplicationOnCifar10blah/watt-activation/part-1
~CLOSE
isNasMethodblah/watt-activation/part-1
true
achievesConvergenceInLessParamsblah/watt-activation/part-1
true
replicatesPaperOnMnistblah/watt-activation/part-1
YES
usesFusionInMoeblah/watt-activation/part-1
true
relatedToblah/watt-activation/part-2
ex:symbio
hasBranchblah/watt-activation/part-2
ex:metalverificationreplication
connectsTasksAtblah/watt-activation/part-12
ex:boundary
impliesModularArchitectureblah/watt-activation/part-12
ex:structural-territory
teleologicallySeparatesTasksblah/watt-activation/part-12
ex:task
isKeyInsightblah/watt-activation/part-12
confirmed
analogousToblah/watt-activation/part-12
ex:mitochondria
protectsKnowledgeBySeparationblah/watt-activation/part-12
ex:old-knowledge
givesToEachTaskblah/watt-activation/part-12
ex:structural-territory
contrastsWithblah/watt-activation/part-12
ex:standard-methods
providesGaResultsblah/watt-activation/part-34
ex:per-layer-lr-multipliers
comparedToblah/watt-activation/part-33
ex:symbiogpt
superiorInSpeedblah/watt-activation/part-308
ex:neat-in-unit
hasMeanWallTimePerSeedblah/watt-activation/part-308
2.7s
isMuchFasterPerSeedThanblah/watt-activation/part-308
ex:neat-in-unit
completesTasksInTimeblah/watt-activation/part-308
1-2 seconds of log time
hasEfficiencyAdvantageblah/watt-activation/part-308
ex:neat-in-unit
isSlightlyAheadOnblah/watt-activation/part-308
ex:final-combined-accuracy
isFasterByFactorblah/watt-activation/part-308
357x
processesNumTasksblah/watt-activation/part-308
5
startsConditionblah/watt-activation/part-308
ex:fast-phase
isFusionBasedEvolutionarySearchblah/watt-activation/part-307
null
isOftenStrongerThanDifferentiableNasBaselinesblah/watt-activation/part-307
null
usedLessWallClockTimeOnAverageThanblah/watt-activation/part-307
ex:tensorneat-hybrid-search
outperformedDartsByOnMnistblah/watt-activation/part-307
2.8
outperformsblah/watt-activation/part-307
ex:neat-style-nas-baseline
commitsToOntologicalSuperiorityOverblah/watt-activation/part-307
ex:neat
superiorInWallClockTimeblah/watt-activation/part-307
null
consistentlyOutperformedblah/watt-activation/part-307
ex:standard-baselines
hasAverageTimeInSecondsblah/watt-activation/part-307
34.3
wonAllFiveSeedsAgainstblah/watt-activation/part-307
ex:tensorneat-hybrid-search
hasMeanTestGapOverNeatblah/watt-activation/part-307
0.0990
winsAll5SeedsAgainstblah/watt-activation/part-307
ex:neat
achievedTestAccuracyOnCifar10blah/watt-activation/part-307
34.66 ± 2.32 %
beatsblah/watt-activation/part-307
ex:darts
isCompetitiveWithNeuroevolutionBaselinesblah/watt-activation/part-307
null
isFasterOnAverageThanblah/watt-activation/part-307
ex:neat
isProjectNameblah/watt-activation/part-347
ex:wandb
cooccursWithFusionblah/watt-activation/part-441
null
drawsFromBiologyblah/watt-activation/part-461
horizontal gene transfer
canRunNowblah/watt-activation/part-466
ex:cnn-benchmark
readyForCnnBenchmarkblah/watt-activation/part-466
now
partOfReplicationblah/watt-activation/part-466
ex:cnn-benchmark
isIntertextualSubjectblah/watt-activation/part-469
ex:original-paper
involvesGelationblah/watt-activation/part-469
null
beingPortedToblah/watt-activation/part-488
ex:rust
implementedInblah/watt-activation/part-488
ex:python
involvesEvolutionblah/watt-activation/part-488
true
integratesCliffordModulesblah/watt-activation/part-507
true
postAdditionTestsblah/watt-activation/part-507
916
hadPriorTestsblah/watt-activation/part-507
872
rustProjectblah/watt-activation/part-507
true
previouslyExistedblah/watt-activation/part-507
true
wasPreviouslyCoupledblah/watt-activation/part-537
null
hasStandardVersionblah/watt-activation/part-584
ex:standard-symbiogenesis
priorArtInDomainblah/watt-activation/part-584
ex:chimera-governor
achievedScoreblah/watt-activation/part-306
0.537
achievedScoreOnSeed123blah/watt-activation/part-306
0.528
outperformsblah/watt-activation/part-306
ex:tensorneat-hybrid
biologicalTermAppliedblah/watt-activation/part-438
ex:proposed-approach
analogousToProposedApproachblah/watt-activation/part-438
ex:proposed-approach
involvesOrganismsWithDifferentSpectralCapabilitiesblah/watt-activation/part-438
ex:organisms
isStatisticallySuperiorByWilcoxonblah/watt-activation/part-434
ex:null
avoidsblah/watt-activation/part-434
multi-round synchronization
avoidsblah/watt-activation/part-434
waiting for stragglers
avoidsblah/watt-activation/part-434
proximal term requiring the global model broadcast back
avoidsNeedToblah/watt-activation/part-434
restart training
avoidsNeedToblah/watt-activation/part-434
synchronize rounds
benefitsFromblah/watt-activation/part-434
ex:client-diversity
embracesNonIidDiversityblah/watt-activation/part-434
ex:null
enablesClientsToblah/watt-activation/part-434
upload their model once and go offline
ensuresZeroDataSharingblah/watt-activation/part-434
ex:null
exceedsCapabilitiesOfblah/watt-activation/part-434
ex:fedprox
exceedsCapabilitiesOfblah/watt-activation/part-434
ex:scaffold
feedsOnblah/watt-activation/part-434
ex:heterogeneity
fusesModelsViablah/watt-activation/part-434
block-diagonal + compression
hasBiggestStrengthblah/watt-activation/part-434
diverse population for evolutionary search
hasMaximumMarginVsFedproxFtblah/watt-activation/part-434
+2.7pp
hasMeanAccuracyIn50ClientFinalblah/watt-activation/part-434
87.5%
hasMinimumMarginVsFedproxFtblah/watt-activation/part-434
+1.1pp
hasPerSeedMarginsVsFedproxFtblah/watt-activation/part-434
+1.2pp
hasPerSeedMarginsVsFedproxFtblah/watt-activation/part-434
+2.1pp
hasPerSeedMarginsVsFedproxFtblah/watt-activation/part-434
+1.1pp
hasPerSeedMarginsVsFedproxFtblah/watt-activation/part-434
+2.7pp
hasPerSeedMarginsVsFedproxFtblah/watt-activation/part-434
+1.8pp
hasStdDevAccuracyIn50ClientFinalblah/watt-activation/part-434
0.85
isAsynchronousByDesignblah/watt-activation/part-434
ex:null
isProvenSuperiorblah/watt-activation/part-434
ex:null
isStatisticallySuperiorByTTestblah/watt-activation/part-434
ex:null
isUniquelySuitedToblah/watt-activation/part-434
ex:federated-learning
leveragesDiversityAsStrengthblah/watt-activation/part-434
ex:null
neverLosesToblah/watt-activation/part-434
ex:fedprox-ft
operatesFuseCompressEvolveLoopInblah/watt-activation/part-434
weight space
outperformsFedProxFtIn50Clientsblah/watt-activation/part-434
ex:null
provesAdvantageGrowsWithblah/watt-activation/part-434
more clients (5→50: -1.2pp→+1.5pp)
providesHugeBenefitInblah/watt-activation/part-434
ex:cross-device-federated-learning
supportsHeterogeneousArchitecturesblah/watt-activation/part-434
ex:null
turnsWeaknessIntoStrengthOfblah/watt-activation/part-434
ex:federated-learning
welcomesblah/watt-activation/part-434
ex:heterogeneous-clients
winsEverySingleSeedblah/watt-activation/part-434
ex:null
winsSeedsIn50ClientAgainstFedproxFtblah/watt-activation/part-434
5/5
isProjectModuleblah/watt-activation/part-543
true
givesEachTaskblah/watt-activation/12
ex:own-structural-territory
connectionMethodblah/watt-activation/12
ex:boundary-connection
analogousToblah/watt-activation/12
ex:mitochondria
labelblah/watt-activation/33
Symbiogenesis
labelblah/watt-activation/306
symbiogenesis
fasterThanblah/watt-activation/306
ex:neat_in_unit
completesTasksDurationblah/watt-activation/306
1-2 seconds
completesTaskCountblah/watt-activation/306
5
hasSlightlyHigherAccuracyThanblah/watt-activation/306
ex:neat_in_unit
hasSpeedMultiplierOverblah/watt-activation/306
ex:neat_in_unit
hasMeanWallTimeblah/watt-activation/306
2.7
typeblah/watt-activation/305
ex:Algorithm
labelblah/watt-activation/305
symbiogenesis
winsAllSeedsblah/watt-activation/305
5
hasMeanTestGapblah/watt-activation/305
0.099
favoredByMeanTestGapblah/watt-activation/305
true
averageRuntimeblah/watt-activation/305
34.3
fasterThanblah/watt-activation/305
ex:neat-algorithm
outperformedblah/watt-activation/305
standard baselines
achievedTestAccuracyblah/watt-activation/305
34.66%
testAccuracyStdDevblah/watt-activation/305
2.32
usedLessWallClockTimeblah/watt-activation/305
true
outperformedByPercentagePointsblah/watt-activation/305
2.8
typeblah/watt-activation/432
ex:Algorithm
labelblah/watt-activation/432
symbiogenesis
suitedForFederatedLearningblah/watt-activation/432
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hasComparisonAdvantageOverblah/watt-activation/432
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hasComparisonAdvantageOverblah/watt-activation/432
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featureblah/watt-activation/432
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privacyFeatureblah/watt-activation/432
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operationalLocationblah/watt-activation/432
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processLoopblah/watt-activation/432
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designFeatureblah/watt-activation/432
ex:asynchronous-by-design
clientJoinBehaviorblah/watt-activation/432
ex:join-any-time
clientJoinMethodblah/watt-activation/432
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fusionMethodblah/watt-activation/432
ex:block-diagonal-plus-compression
scalingBehaviorblah/watt-activation/432
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scalingTrendblah/watt-activation/432
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benefitsFromblah/watt-activation/432
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turnsWeaknessIntoStrengthblah/watt-activation/432
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actionblah/watt-activation/432
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accuracyMetricblah/watt-activation/432
87.5
accuracyErrorblah/watt-activation/432
0.85
winCountblah/watt-activation/432
5
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symbiogenesis
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typeblah/watt-activation/439
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typeblah/watt-activation/440
ex:Library

References (38)

38 references
  1. ctx:genes/lisa-watts/resume-professional-profile
  2. ctx:genes/lisa-watts/research-catastrophic-forgetting
  3. ctx:genes/lisa-watts/research-symbiogenesis
  4. [4]Part 161 fact
    ctx:discord/blah/training-and-evals/part-16
  5. [5]Part 201 fact
    ctx:discord/blah/training-and-evals/part-20
  6. [6]Part 221 fact
    ctx:discord/blah/training-and-evals/part-22
  7. [7]Part 114 facts
    ctx:discord/blah/watt-activation/part-1
  8. [8]Part 22 facts
    ctx:discord/blah/watt-activation/part-2
  9. [9]Part 128 facts
    ctx:discord/blah/watt-activation/part-12
  10. [10]Part 341 fact
    ctx:discord/blah/watt-activation/part-34
  11. [11]Part 331 fact
    ctx:discord/blah/watt-activation/part-33
  12. [12]Part 3089 facts
    ctx:discord/blah/watt-activation/part-308
  13. [13]Part 30716 facts
    ctx:discord/blah/watt-activation/part-307
  14. [14]Part 3471 fact
    ctx:discord/blah/watt-activation/part-347
  15. [15]Part 4411 fact
    ctx:discord/blah/watt-activation/part-441
  16. [16]Part 4611 fact
    ctx:discord/blah/watt-activation/part-461
  17. [17]Part 4663 facts
    ctx:discord/blah/watt-activation/part-466
  18. [18]Part 4692 facts
    ctx:discord/blah/watt-activation/part-469
  19. [19]Part 4883 facts
    ctx:discord/blah/watt-activation/part-488
  20. [20]Part 5075 facts
    ctx:discord/blah/watt-activation/part-507
  21. [21]Part 5371 fact
    ctx:discord/blah/watt-activation/part-537
  22. [22]Part 5842 facts
    ctx:discord/blah/watt-activation/part-584
  23. [23]Part 3063 facts
    ctx:discord/blah/watt-activation/part-306
  24. [24]Part 4383 facts
    ctx:discord/blah/watt-activation/part-438
  25. [25]Part 43439 facts
    ctx:discord/blah/watt-activation/part-434
  26. [26]Part 5431 fact
    ctx:discord/blah/watt-activation/part-543
  27. [27]123 facts
    ctx:discord/blah/watt-activation/12
    • full textwatt-activation-12
      text/plain3 KBdoc:agent/watt-activation-12/2b226561-3075-47ab-89b3-591d7663c93b
      Show excerpt
      [2026-02-27 14:42] xenonfun: the codebase already computes SVD in model.py:effective_rank (files: Screenshot_2026-02-27_at_9.41.31_AM.png) [2026-02-27 15:41] xenonfun: (files: Screenshot_2026-02-27_at_10.41.22_AM.png) [2026-02-27 15:44] xe
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      [2026-03-06 22:35] xenonfun: Evaluation at iteration 65000 ====================================================================== Prompt: 'virtue is' Generated: 'the new york yankees for the two thousand two-five season: the first time, in
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      [2026-03-14 13:10] ajaxdavis: it stores that psyche profile everyday, might be funny to analyze a year from now [2026-03-14 13:11] ajaxdavis: maybe i should just see a therapist though [2026-03-14 13:12] foxhop.: lmao [2026-03-14 13:13] fox
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      [2026-03-14 12:17] lisamegawatts: well we still crushing neat, but apparently that under compute matched baseline so we going to do yet another 5 seed for conclusive apples to apples neat vs symbio at NAS [2026-03-14 12:27] xenonfun: (file
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      [2026-03-20 06:16] lisamegawatts: It means symbiogenesis is uniquely suited to federated in ways FedProx/Scaffold can't match: Communication: Clients upload their model once and go offline. No multi-round synchronization, no waiting for st
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      [2026-03-20 07:02] xenonfun: ⏺ That's a sharper take. Strip it to the essentials: Basic oscillators with natural frequencies on S^{d-1}. No Lohe sync, no coupling dynamics. The combinatorics of mixing groups from different clients IS the
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      [2026-03-20 15:36] omega [bot]: 🔧 1/3: search ✅ Success **Args:** ```json { "query": "Lohe-Native FedSym oscillator group fusion FedSym PR #7 FedSym experiments symbiogenesis Kuramoto population Fashion-MNIST MNIST" } ``` **Result:** ```j
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      [2026-03-20 15:36] omega [bot]: Here’s an overview of the recent discussion and key points in your FedSym and symbiogenesis experiments: --- ### Overview - The main goal is to apply a novel federated learning approach called **FedSym** u
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      [2026-03-21 18:08] xenonfun: ``` Key observations: - Rust achieves significantly higher accuracy (99.1% vs 89.5% best) — the GPU-accelerated training does more effective optimization per epoch - Gelation detected at the same step (12)
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      [2026-03-21 18:44] xenonfun: ``` Experiment 1a: MNIST (5k/1k, 200 iter) ┌────────────────┬─────────────────────────────┬─────────┐ │ │ Python │ Rust │ ├────────────────┼───────────────────────
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      [2026-03-23 03:50] xenonfun: ``` ─────────────────────────────────────────┬────────────────────────────────────────────────────┐ │ File │ Action │ ├───────────
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      [2026-04-16 00:04] xenonfun: ``` 3. "Eval still all CPU" — you're right The metal-gpu feature compiles the Metal backend for other modules (bivector field, symbiogenesis, lohe_delta GPU dispatch, etc.) but WaveNativeLM has no Metal pat

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