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It seems that Automated Knowledge Base Construction would be unfavorable.

As Matt Gardner noted in NLP Highlights in 2019 that:

Um, but I know that Google, for instance, canceled their knowledge base construction project because there wasn’t high enough precision to actually be useful in their product.

The canceled project Knowledge Vault is an Automated Knowledge Base Construction(AKBC) project launched in August 2014.

There are two main methods to integrate knowledge into the neural networks: 1) pre-trained models like BERT, ELECTRA; 2) retrieval-augmented generative model.

In a 2020 paper REALM: Integrating Retrieval into Language Representation Models, they utilized a retrieval rather than a knowledge base to enrich neural networks. And the best systems in the NeurIPS 2020 EfficientQA competition all relied on retrieval.

Knowledge bases that are actively being maintained receive a lot of annotation and curation, as stated in that podcast. If curation and annotation are not sufficient, knowledge base would cannot apply in AI.

It seems that Automated Knowledge Base Construction would be unfavorable.

As Matt Gardner noted in NLP Highlights in 2019 that:

Um, but I know that Google, for instance, canceled their knowledge base construction project because there wasn’t high enough precision to actually be useful in their product.

The canceled project Knowledge Vault is an Automated Knowledge Base Construction(AKBC) project launched in August 2014.

There are three methods to integrate knowledge into the neural networks: 1) pre-trained models like BERT, ELECTRA; 2) retrieval-augmented generative model; 3) flesh out the triples into natural text as that in KELM.

In a 2020 paper REALM: Integrating Retrieval into Language Representation Models, they utilized a retrieval rather than a knowledge base to enrich neural networks. And the best systems in the NeurIPS 2020 EfficientQA competition all relied on retrieval.

Knowledge bases that are actively being maintained receive a lot of annotation and curation, as stated in that podcast. If curation and annotation are not sufficient, the knowledge base maybe cannot apply in AI.

It seems that Automated Knowledge Base Construction would be unfavorable.

As Matt Gardner noted in NLP Highlights in 2019 that:

Um, but I know that Google, for instance, canceled their knowledge base construction project because there wasn’t high enough precision to actually be useful in their product.

The canceled project Knowledge Vault is an Automated Knowledge Base Construction(AKBC) project launched in August 2014.

There are two main methods to integrate knowledge into the neural networks: 1) pre-trained models like BERT, ELECTRA; 2) retrieval-augmented generative model.

In a 2020 paper REALM: Integrating Retrieval into Language Representation Models, they utilized a retrieval rather than a knowledge base to enrich neural networks.

Knowledge bases that are actively being maintained receive a lot of annotation and curation, as stated in that podcast. If curation and annotation are not sufficient, knowledge base would cannot apply in AI.

It seems that Automated Knowledge Base Construction would be unfavorable.

As Matt Gardner noted in NLP Highlights in 2019 that:

Um, but I know that Google, for instance, canceled their knowledge base construction project because there wasn’t high enough precision to actually be useful in their product.

The canceled project Knowledge Vault is an Automated Knowledge Base Construction(AKBC) project launched in August 2014.

There are two main methods to integrate knowledge into the neural networks: 1) pre-trained models like BERT, ELECTRA; 2) retrieval-augmented generative model.

In a 2020 paper REALM: Integrating Retrieval into Language Representation Models, they utilized a retrieval rather than a knowledge base to enrich neural networks. And the best systems in the NeurIPS 2020 EfficientQA competition all relied on retrieval.

Knowledge bases that are actively being maintained receive a lot of annotation and curation, as stated in that podcast. If curation and annotation are not sufficient, knowledge base would cannot apply in AI.

It seems that Automated Knowledge Base Construction would be unfavorable.

As Matt Gardner noted in NLP Highlights in 2019 that:

Um, but I know that Google, for instance, canceled their knowledge base construction project because there wasn’t high enough precision to actually be useful in their product.

The canceled project Knowledge Vault is an Automated Knowledge Base Construction(AKBC) project launched in August 2014.

There are two main methods to integrate knowledge into the neural networks: 1) pre-trained models like BERT, ELECTRA; 2) retrieval-augmented generative model.

In a 2020 paper REALM: Integrating Retrieval into Language Representation Models, they utilized a retrieval rather than a knowledge base to enhance the neural network.

Knowledge bases that are actively being maintained receive a lot of annotation and curation, as stated in that podcast. If curation and annotation are not sufficient, knowledge base would cannot apply in AI.

It seems that Automated Knowledge Base Construction would be unfavorable.

As Matt Gardner noted in NLP Highlights in 2019 that:

Um, but I know that Google, for instance, canceled their knowledge base construction project because there wasn’t high enough precision to actually be useful in their product.

The canceled project Knowledge Vault is an Automated Knowledge Base Construction(AKBC) project launched in August 2014.

There are two main methods to integrate knowledge into the neural networks: 1) pre-trained models like BERT, ELECTRA; 2) retrieval-augmented generative model.

In a 2020 paper REALM: Integrating Retrieval into Language Representation Models, they utilized a retrieval rather than a knowledge base to enrich neural networks.

Knowledge bases that are actively being maintained receive a lot of annotation and curation, as stated in that podcast. If curation and annotation are not sufficient, knowledge base would cannot apply in AI.