Rapid Mobile App Development for Generative AI Agents on MIT App Inventor
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arXiv
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| Main Authors: | , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866913339618099200 |
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| author | Gao, Jaida Su, Calab Miller, Etai Lu, Kevin Meng, Yu |
| author_facet | Gao, Jaida Su, Calab Miller, Etai Lu, Kevin Meng, Yu |
| contents | The evolution of Artificial Intelligence (AI) stands as a pivotal force shaping our society, finding applications across diverse domains such as education, sustainability, and safety. Leveraging AI within mobile applications makes it easily accessible to the public, catalyzing its transformative potential. In this paper, we present a methodology for the rapid development of AI agent applications using the development platform provided by MIT App Inventor. To demonstrate its efficacy, we share the development journey of three distinct mobile applications: SynchroNet for fostering sustainable communities; ProductiviTeams for addressing procrastination; and iHELP for enhancing community safety. All three applications seamlessly integrate a spectrum of generative AI features, leveraging OpenAI APIs. Furthermore, we offer insights gleaned from overcoming challenges in integrating diverse tools and AI functionalities, aiming to inspire young developers to join our efforts in building practical AI agent applications. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_01561 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Rapid Mobile App Development for Generative AI Agents on MIT App Inventor Gao, Jaida Su, Calab Miller, Etai Lu, Kevin Meng, Yu Software Engineering Artificial Intelligence Computers and Society The evolution of Artificial Intelligence (AI) stands as a pivotal force shaping our society, finding applications across diverse domains such as education, sustainability, and safety. Leveraging AI within mobile applications makes it easily accessible to the public, catalyzing its transformative potential. In this paper, we present a methodology for the rapid development of AI agent applications using the development platform provided by MIT App Inventor. To demonstrate its efficacy, we share the development journey of three distinct mobile applications: SynchroNet for fostering sustainable communities; ProductiviTeams for addressing procrastination; and iHELP for enhancing community safety. All three applications seamlessly integrate a spectrum of generative AI features, leveraging OpenAI APIs. Furthermore, we offer insights gleaned from overcoming challenges in integrating diverse tools and AI functionalities, aiming to inspire young developers to join our efforts in building practical AI agent applications. |
| title | Rapid Mobile App Development for Generative AI Agents on MIT App Inventor |
| topic | Software Engineering Artificial Intelligence Computers and Society |
| url | https://arxiv.org/abs/2405.01561 |