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Hutchins, John

doi:10.1023/a:1007969630568

Cited by 30 publications

(2 citation statements)

References 25 publications

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“…Early developments that lead to current generative models started since 1954, with IBM and Georgetown University laying the background for natural language processing (NLP) through automating language translation [8]. In 1966 MIT researcher Joseph Weizenbaum created ELIZA, the chatbot that used pattern recognition and predefined rules to simulate human conversation, marking the beginning of NLP research [9].…”

Section: B Generative Models Evolutionmentioning

confidence: 99%

Roadmap for Generative Models Redefining Learning in Egyptian Higher Education

ElFangary

2024

IJACSA

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Artificial Intelligence (AI) Generative models have become powerful tools in all sciences, research, academia, and businesses. Egyptian Universities need to leverage those models while using them ethically and responsibly to survive in the current global market. This paper explains the evolution of those models, from basic natural language processing by IBM in 1954 to the current powerful revolutionary generative models. The paper presents research that helps us get desired outputs or behaviors from generative models through prompt engineering, chain of thought prompting and ReAct. The paper presents Egypt and Egyptian Universities readiness and steps taken to get advantage of the latest AI technologies. The paper examines the training of those models to identify their advantages and disadvantages for university members focusing on the Egyptian context. The roadmap for Egyptian Universities use of generative models consists of a SWOT analysis; an infographic of policies and guidelines with regard to faculty and students use of generative models at Egyptian Universities promoting academic integrity and innovation, while minimizing the risks associated with this technology; A table of types and severities of penalties for policy violations by students using generative models is specified and finally a framework for nontechnical users of generative models of reusable patterns to get the optimal desired output of the models is developed.

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Section: B Generative Models Evolutionmentioning

confidence: 99%

Roadmap for Generative Models Redefining Learning in Egyptian Higher Education

ElFangary

2024

IJACSA

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“…The inseparability of culture and language has led researchers to carry out studies on the subject of translating the cultural context of African languages into the English language by using machine translation [2]. Machine Translation (MT) was one of the first applications thought to be computer-solvable; a word-for-word translation system was developed in 1954 [4]. MT is the task of automatically converting source text in one language to text in another language.…”

Section: Introductionmentioning

confidence: 99%

Masakhane Web: A Machine Translation Platform for African Languages

Gitau

Kabongo

Modupe

et al. 2023

Preprint

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Low-resource languages pose a particularly difficult challenge to neu-ral machine translation (NMT), and there appears to be insufficient machine translation (MT) systems to support African language accessibility. Masakhane Web, an NMT system for African languages, is proposed in this paper. Our approach is an open-source platform that is free, flexible, and produces reasonably accurate translations for African languages. The platform makes use of Masakhane community-trained MT models. It enables users to generate new data by providing feedback on translations, which is then used to retrain the models to improve them. Ultimately, our goal is to create a platform that can provide accurate translations for African languages and make the process of creating MT models easier for those who lack the technical expertise. Furthermore, we include strategies for domain experts to evaluate the system and explain how the platform can be used as a data collection source to improve MT for African languages.

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Trujillo¹

1999

Translation Engines: Techniques for Machine Translation

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Untitled

Cited by 30 publications

References 25 publications

Roadmap for Generative Models Redefining Learning in Egyptian Higher Education

Roadmap for Generative Models Redefining Learning in Egyptian Higher Education

Masakhane Web: A Machine Translation Platform for African Languages

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