TY - GEN
T1 - Imperfectly Perfect AI Chatbots: Limitations of Generative AI, Large Language Models and Large Multimodal Models
AU - Naik, Dishita
AU - Naik, Ishita
AU - Naik, Nitin
PY - 2024/12/20
Y1 - 2024/12/20
N2 - Generative AI has transformed the landscape of AI chatbots in a way that they are increasingly becoming human-like in their understanding and working. Generative AI is used for creating new contents, and most modern AI chatbots are designed using two types of generative AI models: Large Language Models (LLMs) and Large Multimodal Model (LMMs). LLMs deal with the text, whereas LMMs deal with more modalities including text, image, audio and video. This continuous enhancement of generative AI models is bringing AI chatbots closer to the human working. Nonetheless, these AI chatbots are not perfect, as they have several limitations, and their users should comprehend before fully relying on these imperfectly perfect AI chatbots. Depending on the type of use of AI chatbots, these limitations may or may not impact them significantly. This paper will organise the limitations of AI chatbots into six main categories: intelligence and understanding related limitations; accuracy and credibility related limitations; ethics and regulations related limitations; accountability, transparency and consistency related limitations; design, coding and training related limitations; and human, machine and vender related limitations. The aim of this paper is to emphasise, organise and analyse numerous limitations of AI chatbots into the proposed categories; accordingly, users should become more cognisant about all these limitations in deciding their suitability or unsuitability for the specific use cases.
AB - Generative AI has transformed the landscape of AI chatbots in a way that they are increasingly becoming human-like in their understanding and working. Generative AI is used for creating new contents, and most modern AI chatbots are designed using two types of generative AI models: Large Language Models (LLMs) and Large Multimodal Model (LMMs). LLMs deal with the text, whereas LMMs deal with more modalities including text, image, audio and video. This continuous enhancement of generative AI models is bringing AI chatbots closer to the human working. Nonetheless, these AI chatbots are not perfect, as they have several limitations, and their users should comprehend before fully relying on these imperfectly perfect AI chatbots. Depending on the type of use of AI chatbots, these limitations may or may not impact them significantly. This paper will organise the limitations of AI chatbots into six main categories: intelligence and understanding related limitations; accuracy and credibility related limitations; ethics and regulations related limitations; accountability, transparency and consistency related limitations; design, coding and training related limitations; and human, machine and vender related limitations. The aim of this paper is to emphasise, organise and analyse numerous limitations of AI chatbots into the proposed categories; accordingly, users should become more cognisant about all these limitations in deciding their suitability or unsuitability for the specific use cases.
UR - https://www.techrxiv.org/users/845749/articles/1237242-imperfectly-perfect-ai-chatbots-limitations-of-generative-ai-large-language-models-and-large-multimodal-models?commit=cc353b09433e0298d4e369d418681d223ed4fb62
UR - https://link.springer.com/chapter/10.1007/978-3-031-74443-3_3
U2 - 10.1007/978-3-031-74443-3_3
DO - 10.1007/978-3-031-74443-3_3
M3 - Conference publication
SN - 978-3-031-74442-6
T3 - Lecture Notes in Networks and Systems (LNNS)
SP - 43
EP - 66
BT - Contributions Presented at The International Conference on Computing, Communication, Cybersecurity and AI, July 3–4, 2024, London, UK: The C3AI 2024
A2 - Naik, Nitin
A2 - Jenkins, Paul
A2 - Prajapat, Shaligram
A2 - Grace, Paul
ER -