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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
...catch up on these, and many more highlights
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