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The following German prepositions always take a dative:
• *ab* – “from” (time)
• *aus* – “from, out of”
• *außer* – “except for”
• *bei* – “at, near, at the house of”
• *dank* – “thanks to”
• *entgegen* – “contrary to”
• *gegenüber* – “opposite”
• *gemäß* – “according to”
• *laut* – “according to”
• *mit* – “with”
• *nach* – “after, to”
• *seit* – “since, for”
• *von* – “from, of”
• *zu* – “to”
• *zufolge* – “according to”
German Prepositions – The Ultimate Guide (with Charts)
George Julian
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
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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