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Turing is a high-level, general purpose programming language developed in 1982 by Ric Holt and James Cordy, at University of Toronto in Ontario, Canada. It was designed to help students taking their first computer science course learn how to code.
The Turing test can provide some evidence of intelligence, but it penalizes non-human intelligent behavior and may incentivize artificial stupidity. [35] Proposed by Alan Turing in his 1950 paper "Computing Machinery and Intelligence," this test involves a human judge engaging in natural language conversations with both a human and a machine ...
The Computer Language Benchmarks Game site warns against over-generalizing from benchmark data, but contains a large number of micro-benchmarks of reader-contributed code snippets, with an interface that generates various charts and tables comparing specific programming languages and types of tests.
More precisely the gap means the difference between ambiguous formulation of contextual knowledge in a powerful language (e.g. natural language) and its sound, reproducible and computational representation in a formal language (e.g. programming language). Semantics of an object depends on the context it is regarded within. For practical ...
The equivalence of unrestricted grammars to Turing machines implies the existence of a universal unrestricted grammar, a grammar capable of accepting any other unrestricted grammar's language given a description of the language. For this reason, it is theoretically possible to build a programming language based on unrestricted grammars (e.g. Thue).
"Computing Machinery and Intelligence" is a seminal paper written by Alan Turing on the topic of artificial intelligence.The paper, published in 1950 in Mind, was the first to introduce his concept of what is now known as the Turing test to the general public.
Turing's a-machine model. Turing's a-machine (as he called it) was left-ended, right-end-infinite. He provided symbols əə to mark the left end. A finite number of tape symbols were permitted. The instructions (if a universal machine), and the "input" and "out" were written only on "F-squares", and markers were to appear on "E-squares".
In the mind of a human being, words and language correspond to things one has experienced. [18] For LLMs, words may correspond only to other words and patterns of usage fed into their training data. [19] [20] [4] Proponents of the idea of stochastic parrots thus conclude that LLMs are incapable of actually understanding language. [19] [4]