Computing Machinery and Intelligence A.M. Turing
By A. Turing. 2007
133 citations recorded by the source corpus.
Subfields: Philosophy
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Philosophy
- Ana-Elena Guerrero-Roldán
- Saif M. Mohammad
- Bo Pang
- M. Elena Rodríguez
- David Bañeres
- Aras Bozkurt
- Abdulkadir Karadeniz
Citations in the corpus
- Artificial Intelligence and Reflections from Educational Landscape: A Review of AI Studies in Half a Century (2021, methodology): “The paper entitled “Computing Machinery and Intelligence” by Turing [1] was published to propose a method for evaluating whether machines are able to think, which can be referred to as the beginning of AI.”
- Towards Holistic and Automatic Evaluation of Open-Domain Dialogue Generation (2020, background): “Research on enabling a machine to have meaningful and natural conversations with humans plays a fundamental role in developing artificial general intelligence, as can be seen in the formulation of Turing test (Turing, 1950).”
- Examining Citations of Natural Language Processing Literature (2020, background): “The origins of Natural Language Processing (NLP) go back to the earliest work in Computer Science— when Alan Turing published his seminal paper exploring whether machines can think, and proposed what is now known as the Turing test (Turing, 1950, 2009).”
- Aligning Cyber Space With Physical World: A Comprehensive Survey on Embodied AI (2024, unknown): “E MBODIED artificial intelligence (AI) was initially proposed from the embodied turing test by Alan Turing in 1950 [1] and has wide applications including robotics, health-care, and smart manufacturing.”
- Judge the Judges: A Large-Scale Evaluation Study of Neural Language Models for Online Review Generation (2019, background): “…the most natural way to evaluate the quality of a generator is to involve humans as judges, either through some type of Turing test (Machinery, 1950) to distinguish generated text from human input texts, or to directly compare the texts generated by different generators (Mel-lish and Dale,…”