## 4 Comparative Analysis of AI Language Models Based on Scholarly Literature
### Reported Limitations from Scholarly Analysis  
Despite the remarkable capabilities of each chatbot, scholarly analysis has revealed inherent limitations that necessitate careful consideration in their application. A prevalent concern across all models is the potential cybersecurity risks that they introduce [40]. THe inadvertent input of sensitive or classified information into these systems could expose such data to human reviewers or, more alarmingly, to cybercriminals who may exploit AI tools to orchestrate attacks, including hacking and phishing [41]. Furthermore, AI often faces scrutiny for its potential to be invasive, biased, and manipulative [42]. For instance, ChatGPT has been criticised for exhibiting a perceived political bias, which can distort its outputs [43]. These findings underscore the crucial importance of adhering to ethical principles to ensure secure, safe, and responsible AI deployment.  
Focusing on ChatGPT, despite its proficiency in delivering educational content and medical information, it is not infallible. Inconsistencies in information accuracy and limitations in displaying graphical content have been identified as notable challenges [26]. Instances where ChatGPT provided inconsistent responses under identical conditions have raised concerns about its reliability [24]. Additionally, academic integrity, context comprehension, and safety have been highlighted as areas requiring attention [44]. Significantly, neither ChatGPT 3.5 nor 4.0 has demonstrated the capability to generate original scientific contributions [39], and there have been documented cases of these models failing to accurately predict drug interactions [1]. In the educational domain, evidence suggests that the overreliance on ChatGPT 3.5 may lead to suboptimal academic performance [33]. Moreover, the knowledge base of these models is constrained to a specific point in time, thus limiting their ability to provide up-to-date information [38]. It is also noteworthy that, currently, both ChatGPT 3.5 and 4.0 are not open source, thus potentially restricting their accessibility and opportunities for collaborative enhancement.  
Bard, while offering real-time internet access, has been observed to generate inconsistent answers and struggle with email consistency [27; 45]. Its performance in anatomy writing and generating original scientific contributions has also been questioned [46]. Similarly, Llama's suitability for advanced mathematical topics like calculus and statistics has been found to be limited, and it requires substantial computational resources [26].  
Ernie, being primarily focused on mainland China, may face challenges in terms of international accessibility and the impact of strict Chinese policies on its performance [4]. Its biennial knowledge updates also suggest potential limitations in staying current with rapidly evolving information.  
Grok, although showing promise in real-time information processing and humour, is still in its early stages of development. Its current exclusivity to X premium subscribers and the presence of biased or inaccurate information are notable drawbacks [30]  
Recognising these limitations, users and developers must approach the utilisation of AI models with a balanced understanding of their capabilities and an awareness of the potential risks. Prudent use of these technologies is essential to harness their benefits while mitigating their drawbacks. As the field of AI continues to evolve, ongoing research and development efforts should focus on addressing these limitations and enhancing the robustness, reliability, and ethical alignment of these powerful tools.  
These are our suggestions for rewriting the section on the real-world applications of AI chatbots to better integrate them with the rest of the content available and to improve their flow and cohesiveness.