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Neuro-Symbolic GRAPH REASONING  

Discover AI
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11 окт 2024

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Комментарии : 17   
@olegt3978
@olegt3978 2 дня назад
Openai,anthropic should integrate symbolic methods into their neuro systems. its obvious that neurosymbilic ai can be much more powerful than pure neuro.
@En1Gm4A
@En1Gm4A 2 дня назад
Finally it's happening - infinite knowledge expansion soon
@olegt3978
@olegt3978 2 дня назад
Prose(flashfill) framework from Microsoft for program synthesis could be used with llms. Program synthesis methods are extremely sample efficient - one example is often enough to infere program which makes this transformation/extraction/execution. And llm could generate such DSL or examples for prose. This would give a loop between neuro llm and symbolic program synthesis prose.
@En1Gm4A
@En1Gm4A 2 дня назад
Strong strawberry taste 🍓🍓
@깐돌엄마-g9e
@깐돌엄마-g9e 2 дня назад
Building decent and informative knowledge graphs is becoming increasingly important!!! Thanks again for sharing these papers :)
@ramitube21
@ramitube21 2 дня назад
Excellent video. Thanks for sharing. Can you please share the prompts that you made to o1 and o4-canvas?
@student7261
@student7261 2 дня назад
This is crazy dodo. Love it. But what's even more crazy is this pretty much sums up my mind at the moment...🤪. I am sending you a PM. Hope that's ok...K
@En1Gm4A
@En1Gm4A 2 дня назад
Like all other AI videos beforehand where just noise 😂🤯
@timeflex
@timeflex День назад
Soon they will use weights and biases of multiple LLMs as input data to train an AI of a higher dimension. And then they will loop it onto itself. And this will be it.
@Isaacmellojr
@Isaacmellojr 2 дня назад
For here, outside academia, I think this is the way to acheive AGI. And emulate a real artificial inteligente being.
@En1Gm4A
@En1Gm4A 2 дня назад
Cant state might hype reasonably
@freeideas
@freeideas День назад
The vague part for me, is the last step, "symbolic rule application". Not sure how to ask an LLM to do that. Let's say I have "Jane runs-faster-than John", and "John runs-faster-than Mark" in my database. If the user specifically asks, "Does Jane run faster than Mark", then I can see how the LLM could query the database, pull the relevant connections, and figure out the correct answer. BUT I don't know how I would ask the LLM to "please look for new connections that are suggested by existing connections" unless the entire graph database fits into one context window. Anyone else in the audience have any ideas about that last step?
@code4AI
@code4AI День назад
For symbolic (rule-based) reasoning try Prolog.
@freeideas
@freeideas День назад
@@code4AI right. i did some prolog in college during the ai winter; not saying i am any good at it, but i know enough to believe (perhaps mistakenly) that prolog was always able to take a graph of this-relates-to-that plus some rules, and find (through exhaustive measures) more this-relates-to-that connections, no LLM and no NN needed. are you trying to take me back to the 1990's? ;) Even if this is as good as it gets, it is still good because the LLM makes steps 1 and 2 relatively easy, compared to the 1990's when it was nearly impossible.
@LeonardoRocha0
@LeonardoRocha0 2 дня назад
Is there any chance to share the generated code at the end of vídeo?
@alaetaouab4740
@alaetaouab4740 2 дня назад
Can you please share with me the link to this chatgpt page ?
@imaspacecreature
@imaspacecreature 2 дня назад
YVHW created everything with a divine code they created, which formed the highest order of this plane, symbols. With that in mind, and man's technological advancements, man still hasn't created anything close to a seed.
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