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Personally feel that knowledge graphs will disappear. Currently work on a large knowledge graph at FAANG. Feels like working on an antiquated abstraction layer

Personally feel that knowledge graphs will disappear. Currently work on a large knowledge graph at FAANG. Feels like working on an antiquated abstraction layer that needed to exist due to lack of ML sophistication. With LLMs, I think knowledge graphs are obsolete. The LLM builds the knowledge graph itself inside the network layers. Anytime you have an ML system where humans are designing how the information is organized (feature engineering, linking, graph building), it will work poorly. The algorithm needs full control over the information at the lowest level (characters, words). Only then can something that truly works be built.

mattlutze 4y ago
LLMs have a very clear issue of making false predictions, versus knowledge graphs that represent the information mapped within them. We should be careful to not treat the current hot thing as a hammer. > Anytime you have an ML system where humans are designing how the information is organized (feature engineering, linking, graph building), it will work poorly. This is a very broad assertion that I think is not accurate. > The algorithm needs full control over the information at the lowest level (characters, words). Only then can something that truly works be built. But data preparation and management is fundamentally important which means there's a human shaping the information at the lowest levels. There's no single ring to rule them all. This is also just fundamentally erasing the utility of any supervised model or hybrid system which is a bit silly.
vimax 4y ago
I feel like you’re thinking about this wrong. Knowledge graphs are incredibly useful in combining language and structure, but often not worth the expense to build. Future language models will build knowledge graphs for us with little expense, and for most applications that are not directly at the human interface level, a vectorized knowledge graph will be more useful than a blob of text.
0xbadcafebee 4y ago
Curated knowledge graphs are the only way to accurately map knowledge. Essential for things like medical KGs. You don't want to kill patients because the magical numbers used to hone the algorithm weren't magic enough.
- melagonster 4y ago
  so in anyway expert had read the articles following reference link.

mattlutze 4y ago

LLMs have a very clear issue of making false predictions, versus knowledge graphs that represent the information mapped within them. We should be careful to not treat the current hot thing as a hammer. > Anytime you have an ML system where humans are designing how the information is organized (feature engineering, linking, graph building), it will work poorly. This is a very broad assertion that I think is not accurate. > The algorithm needs full control over the information at the lowest level (characters, words). Only then can something that truly works be built. But data preparation and management is fundamentally important which means there's a human shaping the information at the lowest levels. There's no single ring to rule them all. This is also just fundamentally erasing the utility of any supervised model or hybrid system which is a bit silly.

vimax 4y ago

I feel like you’re thinking about this wrong. Knowledge graphs are incredibly useful in combining language and structure, but often not worth the expense to build. Future language models will build knowledge graphs for us with little expense, and for most applications that are not directly at the human interface level, a vectorized knowledge graph will be more useful than a blob of text.

0xbadcafebee 4y ago

Curated knowledge graphs are the only way to accurately map knowledge. Essential for things like medical KGs. You don't want to kill patients because the magical numbers used to hone the algorithm weren't magic enough.

melagonster 4y ago
so in anyway expert had read the articles following reference link.