Comparison of Leading AI Models an Analytical Study of ChatGPT Google Bard and Microsoft Bing
I tiakina i:
| I whakaputaina i: | ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal vol. 14 (2025), p. e31857-e31887 |
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| Kaituhi matua: | |
| Ētahi atu kaituhi: | , , |
| I whakaputaina: |
Ediciones Universidad de Salamanca
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| Ngā marau: | |
| Urunga tuihono: | Citation/Abstract Full Text - PDF |
| Ngā Tūtohu: |
Kāore He Tūtohu, Me noho koe te mea tuatahi ki te tūtohu i tēnei pūkete!
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MARC
| LEADER | 00000nab a2200000uu 4500 | ||
|---|---|---|---|
| 001 | 3282913937 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2255-2863 | ||
| 024 | 7 | |a 10.14201/adcaij.31857 |2 doi | |
| 035 | |a 3282913937 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 100 | 1 | |a Adomako, Pascal | |
| 245 | 1 | |a Comparison of Leading AI Models an Analytical Study of ChatGPT Google Bard and Microsoft Bing | |
| 260 | |b Ediciones Universidad de Salamanca |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a This comparative analysis delves into the capabilities of three prominent Conversational AI models: ChatGPT, Google Bard, and Microsoft Bing Chat. The study encompasses a meticulous exploration of their conversational skills, natural language processing abilities, and creative text generation. Methodologically, this study crafts a comprehensive evaluation framework, including complexity levels and tasks for each dimension. Through user-generated responses, key metrics of fluency, coherence, relevance, accuracy, completeness, informativeness, creativity, and relevance were assessed. The results reveal distinctive strengths of the AI models. The theoretical implications lead to recommendations for dynamic learning, ethical considerations, and cross-cultural adaptability. Practically, avenues for future research were proposed, including real-time user feedback integration, multimodal capabilities exploration, and collaborative human-AI interaction studies. The analysis sets the stage for benchmarking and environmental impact assessments, underlining the need for standardized metrics. | |
| 653 | |a Real time | ||
| 653 | |a Natural language processing | ||
| 653 | |a Conversational artificial intelligence | ||
| 653 | |a Chatbots | ||
| 653 | |a Task complexity | ||
| 653 | |a Environmental impact assessment | ||
| 700 | 1 | |a Talha Ali Khan | |
| 700 | 1 | |a Raja Hashim Ali | |
| 700 | 1 | |a Rand Koutaly | |
| 773 | 0 | |t ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal |g vol. 14 (2025), p. e31857-e31887 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3282913937/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3282913937/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |