Deploy from jjohare/logseq @ 307ae2b0d9f2380a3a4cb556b5cdd5604060c833 jjohare/logseq@307ae2b

Author: jjohare

api/markdown/3D and 4D.md

@@ -5,10 +5,10 @@
   - ontology:: true
   - public-access:: true
   - term-id:: AI-7972
-  - preferred-term:: 3D and 4D
+  - preferred-term:: 3dAnd4d
   - source-domain:: ai
   - status:: draft
-  - owl:class:: ai:twitterHttpstwittercomcocktailpeanutstatus1765462787046686968
+  - owl:class:: ai:3dAnd4d
 
 
 ### Relationships

api/markdown/AI Video.md

@@ -6,8 +6,8 @@ While groundbreaking, and crucially, "available", Luma Dream Machine...
   - public-access:: true
   - term-id:: MV-9731
   - preferred-term:: AI Video
-  - source-domain:: mv
-  - owl:class:: mv:WhileGroundbreakingAndCruciallyAvailableLumaDreamMachine
+  - source-domain:: ai
+  - owl:class:: ai:AiVideo
   - status:: draft
 
 ### Pika Labs

api/markdown/Avatar Behavior.md

@@ -7,7 +7,7 @@ Avatar Behaviour encompasses the programmatic and AI-driven behavioral patterns
   - term-id:: MV-9719
   - preferred-term:: Avatar Behavior
   - source-domain:: mv
-  - owl:class:: mv:AvatarBehaviourEncompassesTheProgrammaticAndAidrivenBehavioral
+  - owl:class:: mv:AvatarBehavior
   - status:: draft
 
 ### Relationships

api/markdown/Avatar Wearable.md

@@ -7,7 +7,7 @@ Avatar Wearables constitute digital fashion items, accessories, cosmetic enhance
   - term-id:: MV-9704
   - preferred-term:: Avatar Wearable
   - source-domain:: mv
-  - owl:class:: mv:AvatarWearablesConstituteDigitalFashionItemsAccessoriesCosmetic
+  - owl:class:: mv:AvatarWearable
   - status:: draft
 
 ### Definition

api/markdown/Bitcoin Mining.md

@@ -7,7 +7,7 @@ Several innovative projects are using the financial incentive...
   - term-id:: BC-9925
   - preferred-term:: Bitcoin Mining
   - source-domain:: bc
-  - owl:class:: bc:SeveralInnovativeProjectsAreUsingTheFinancialIncentive
+  - owl:class:: bc:BitcoinMining
   - status:: draft
 
 ### Mining process overview (this is a repeat of above?)

api/markdown/Cashu.md

@@ -7,7 +7,7 @@
   - term-id:: BC-9876
   - preferred-term:: Cashu
   - source-domain:: bc
-  - owl:class:: bc:TwitterHttpstwittercomcallebtcstatus1777598819355496587
+  - owl:class:: bc:Cashu
   - status:: draft
 
 ### Core Privacy Mechanism

api/markdown/Client side DCO.md

@@ -8,7 +8,7 @@ This ensures relevant and engaging marketing content within...
   - preferred-term:: Client side DCO
   - source-domain:: ai
   - status:: draft
-  - owl:class:: ai:ThisEnsuresRelevantAndEngagingMarketingContentWithin
+  - owl:class:: ai:ClientSideDco
 
 
 ### Relationships

api/markdown/DAO.md

@@ -9,7 +9,7 @@ The most interesting thing about DAOs is that...
   - term-id:: BC-9885
   - preferred-term:: DAO
   - source-domain:: bc
-  - owl:class:: bc:TheMostInterestingThingAboutDaosIsThat
+  - owl:class:: bc:Dao
   - status:: draft
 
 The most interesting thing about DAOs is that they belong more in this money chapter than they do in blockchain. As we have seen they're finding most success as loosely regulated crowd funding platforms. If a small company did find itself wishing to explore this fringe mechanism for raising capital, then we would certainly recommend keeping a global eye on evolving regulation and the onward legal exposure of the company.

api/markdown/Dall-e.md

@@ -10,7 +10,7 @@ DALL-E is OpenAI's groundbreaking text-to-image generative AI system that uses d
   - preferred-term:: Dall-e
   - source-domain:: ai
   - status:: draft
-  - owl:class:: ai:DalleIsOpenaisGroundbreakingTexttoimageGenerativeAiSystem
+  - owl:class:: ai:DallE
 
 DALLE is OpenAI's groundbreaking texttoimage generative AI system that uses diffusion models and transformer architectures to create photorealistic images from natural language descriptions. Named after artist Salvador Dalí and Pixar's WALLE, the system represents a major advancement in multimodal AI, combining natural language understanding with visual synthesis. DALLE 2, released in April 2022, introduced hierarchical textconditional image generation using CLIP (Contrastive LanguageImage Pretraining) latents, enabling unprecedented semantic accuracy and artistic control. The architecture employs a twostage process: a prior network maps text embeddings to image embeddings, then a decoder diffusion model generates images from these representations.