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A graph can be considered a collection of paths of the form node, predicate arc, node, predicate arc, node, predicate arc, ... node which cover the entire graph. In RDF/XML these turn into sequences of elements inside elements which alternate between elements for nodes and predicate arcs. This has been called a series of node/arc stripes. The node at the start of the sequence turns into the outermost element, the next predicate arc turns into a child element, and so on. The stripes generally start at the top of an RDF/XML document and always begin with nodes.

The RDF Concepts and Abstract Syntax [RDF-CONCEPTS] defines the RDF Graph data model (Section 3.1) and the RDF Graph abstract syntax (Section 6). Along with the RDF Semantics [RDF-SEMANTICS] this provides an abstract syntax with a formal semantics for it. The RDF graph has nodes and labeled directed arcs that link pairs of nodes and this is represented as a set of RDF triples where each triple contains a subject node, predicate and object node. Nodes are RDF URI references, RDF literals or are blank nodes. Blank nodes may be given a document-local, non-RDF URI references identifier called a blank node identifier. Predicates are RDF URI references and can be interpreted as either a relationship between the two nodes or as defining an attribute value (object node) for some subject node.

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But there's a catch: the AI needed to train these vehicles requires immense computing power. For example, 1 petaflop (one quadrillion calculations) needs over 11,000 GPUs, which is energy-intensive and costly.