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- in short [[knowledge graph]] advantage is
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- easy to understand and structure as they are more about [[explicit knowledge]]
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- possible to evolve because they are based on widely accepted [[triples]]
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- - essential to plan, make decisions and reason:
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+ - essential to plan, make decisions and reason
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+ - that is why knowledge graph is foundation for [symbolic part](https://arxiv.org/pdf/2002.06177) in [[neuro-symbolic]] movement
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- so the claim is simple
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- - [[knowledge graphs]] coupled with [[graph neural networks]] are essential
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- - for the next generation of architectures and
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+ - [[knowledge graphs]] coupled with [[graph neural networks]] are [ essential](https://huggingface.co/blog/intro-graphml) for [[deep understanding]]
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+ - by a next generation of architectures and
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- by this article we propose example of such architecture
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- ## cryptographic proofs and llms
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- we believe that authenticity of models is a serious bottleneck for ai alignment and more
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- you can boost the power of your models using real cryptographic [[tokens]]
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- not tokens you use
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- 
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- - tokens you use in [[cyberverse ]] are [[particles ]]
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+ - tokens you use we call [[particles ]] in [[cyberverse ]]
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- and [[tokens]] are units of [[value]]
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- ## cybergraph
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- the core of the idea is [[cybergraph]]
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+ - the study of meaning
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+ - is inherently relative concept
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+ - [[ cybergraph]] define meaning by [[ cyberlinks]]
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+ - more
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+ - [[semantic convention]]
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+ - [[semantic neural proofs]]
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+ - [[semantic core]]
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+ - [[semantic cosmwasm]]
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