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A knowledge graph is made up of three main components: nodes, edges, and labels. Any *object*, *place*, or *person* can be a **node**. An **edge** defines the *relationship* between the nodes. For example, a node could be a client, like IBM, and an agency like, Ogilvy. An edge would be categorize the relationship as a customer relationship between IBM and Ogilvy. A represents the subject, B represents the predicate, C represents the object

What is a knowledge graph?

ibm.com

“I’m sick of writing everything in numbered order,” Tom said, listlessly

For Many Years I’ve Been Collecting Tom Swifties and Croakers...

Adam Sharp

it’s important to realize that **ChatGPT and LaMDA aren’t trained to be correct**. You can train models that are optimized to be correct—but that’s a different kind of model. Models like that are being built now; they tend to be smaller and trained on specialized data sets (O’Reilly Media has a search engine that has been trained on the 70,000+ items in our learning platform). And you could integrate those models with GPT-style language models, so that one group of models supplies the *facts* and the other supplies the *language*.

Sydney and the Bard

Mike Loukides

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