The concept of parallelism is applied to instructional programs to fetch a lot of instructions and determine the dependency graph in order to issue instructions faster, but it is important to recognize sentences that can be read in any order without changing the intended meaning.
Turning commonly occurring types or schemas of rules into new predicates speeds up inference processes by avoiding the need for complicated graph walks or theorem proving. Redundantly storing the transitive closure of transitive relations in a table can also speed up the process significantly.
This podcast episode explores the concept of coarse-graining and assembly index and how they can help measure the ordering of all the possible things that can happen.
In order to communicate with possible extraterrestrial life, assembly theory may help us infer their language and technology, even if there is no shared causal graph. Machines are not important in this theory's construction as it focuses on the existence of things rather than the mechanisms behind them.
The entanglement, translation between different description languages and physical universe computations is connected to the notion of energy in computation theory. The maximum speed of information transmission varies in physical, brachial and ruellial space and is different from the way things work in while proving in mathematics.
The hosts discuss the utilization of bots and scraping in media with a guest who explains the difference between off-the-shelf services and a coded scraping option.