Dontopedia

multimodal model

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

multimodal model has 34 facts recorded in Dontopedia across 4 references, with 2 live disagreements.

34 facts·28 predicates·4 sources·2 in dispute

Mostly:handles data type(5), rdf:type(2), after6 7k steps mixed runs has ppl100 105(1)

Maturity scale raw canonical shape-checked rule-derived certified

Inbound mentions (1)

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statesCapabilityStates Capability(1)

Other facts (33)

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.

33 facts
PredicateValueRef
Handles Data TypeWave Forms[3]
Handles Data TypeText[3]
Handles Data TypeVideo[3]
Handles Data TypeImage[3]
Handles Data TypeWav File[3]
Rdf:typeAI Model[3]
Rdf:typeModel[4]
After6 7k Steps Mixed Runs Has Ppl100 105null[1]
Both Workingnull[1]
Compares to Base Modelnull[1]
Has Identical Inference Speed to Basenull[1]
Has Only2k Text Steps Out Of6 7k Totalnull[1]
Inference Overhead Zeronull[1]
Maintains Text Ability While Learning Image Audionull[1]
Shares Architecture With Basenull[1]
Trains on Text Image Audionull[1]
Uses Same Block Stack As Basenull[1]
Handles Single ModalityTraining on One Modality[2]
Already HandlesSingle Modality[2]
Eliminates ConceptToken[3]
Data FormatByte Qkps Wave[3]
Has CapabilityDynamic Input Addition[3]
Data CharacteristicsUnlabeled Bits[3]
Has PropertySelf Organizing Learning[3]
Text Qualitygarbled[4]
Compared toBase Model[4]
Statusexpected[4]
Text Step Count2000[4]
Total Step Count6700[4]
Perplexity Range100-105[4]
Performance Assessmentslightly worse but maintaining text ability while learning image/audio[4]
Inference Speed169[4]
UsesBlock Stack[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.

after6-7kStepsMixedRunsHasPpl100-105blah/watt-activation/part-244
null
bothWorkingblah/watt-activation/part-244
null
comparesToBaseModelblah/watt-activation/part-244
null
hasIdenticalInferenceSpeedToBaseblah/watt-activation/part-244
null
hasOnly2kTextStepsOutOf6-7kTotalblah/watt-activation/part-244
null
inferenceOverheadZeroblah/watt-activation/part-244
null
maintainsTextAbilityWhileLearningImageAudioblah/watt-activation/part-244
null
sharesArchitectureWithBaseblah/watt-activation/part-244
null
trainsOnTextImageAudioblah/watt-activation/part-244
null
usesSameBlockStackAsBaseblah/watt-activation/part-244
null
handlesSingleModalityblah/watt-activation/part-246
ex:training-on-one-modality
alreadyHandlesblah/watt-activation/part-246
ex:single-modality
eliminatesConceptblah/papers/8
ex:token
dataFormatblah/papers/8
ex:byte-qkps-wave
hasCapabilityblah/papers/8
ex:dynamic-input-addition
handlesDataTypeblah/papers/8
ex:wave-forms
handlesDataTypeblah/papers/8
ex:text
handlesDataTypeblah/papers/8
ex:video
handlesDataTypeblah/papers/8
ex:image
handlesDataTypeblah/papers/8
ex:wav-file
dataCharacteristicsblah/papers/8
ex:unlabeled-bits
hasPropertyblah/papers/8
ex:self-organizing-learning
typeblah/papers/8
ex:AI-Model
labelblah/papers/8
multimodal model
typeblah/watt-activation/243
ex:Model
textQualityblah/watt-activation/243
garbled
comparedToblah/watt-activation/243
ex:base-model
statusblah/watt-activation/243
expected
textStepCountblah/watt-activation/243
2000
totalStepCountblah/watt-activation/243
6700
perplexityRangeblah/watt-activation/243
100-105
performanceAssessmentblah/watt-activation/243
slightly worse but maintaining text ability while learning image/audio
inferenceSpeedblah/watt-activation/243
169
usesblah/watt-activation/243
ex:block-stack

References (4)

4 references
  1. [1]Part 24410 facts
    ctx:discord/blah/watt-activation/part-244
  2. [2]Part 2462 facts
    ctx:discord/blah/watt-activation/part-246
  3. [3]812 facts
    ctx:discord/blah/papers/8
    • full textpapers-8
      text/plain3 KBdoc:agent/papers-8/6fb41b21-3cff-4525-91b8-47c46c7190e4
      Show excerpt
      [2026-03-27 03:25] traves_theberge: are you talking about neural oscillations? [2026-03-27 03:25] lisamegawatts: yes, the theta gamma etc [2026-03-27 03:26] lisamegawatts: og oscillator [2026-03-27 03:27] lisamegawatts: (files: message.txt
  4. [4]24310 facts
    ctx:discord/blah/watt-activation/243
    • full textwatt-activation-243
      text/plain3 KBdoc:agent/watt-activation-243/14f8ddd1-c20c-4aa1-99ee-73dc849eba12
      Show excerpt
      [2026-03-12 05:04] xenonfun: ⏺ While we wait for the image data to re-prep, let me summarize the issues found and fixed: Problems found: 1. tok/s inflated — was averaging all modality step times but computing tokens as bs*seq which onl

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