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mention of neurosymbolic ai in bostrom introduction
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Diff for: pages/cyberverse.md

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Diff for: pages/introduction to bostrom for ai geeks.md

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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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- ![](https://emerald-raw-leopon-384.mypinata.cloud/ipfs/QmQTvZLqTxJNK7K7cFJTeBbKDDWTecXXeExHz4otJkjjfe)
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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]]

Diff for: pages/neuro-symbolic.md

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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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