The following is a summary of a manuscript for a scientific journal of the opportunities and challenges of LLMs in mental health, can you make a list of issues that may have been missed in this manuscript:

The manuscript section titled "Technical Overview" describes the field of Artificial Intelligence (AI) and its evolution. AI, both a scientific discipline and a term for intelligent computer systems, encompasses several subfields such as robotics, computer vision, natural language processing, and safety. AI tools that generate content like text and images have gained significant attention recently, with OpenAI's AI tools attracting 100 million active users by February 2023. The primary technologies behind these tools are artificial neural networks and machine learning, which have been in existence for decades. The progression in this domain occurred with the advent of deep learning and transformer architecture, leading to the development of Generative Pretrained Transformer (GPT) architecture. The term "Generative" implies that these models not only encode information but also generate it, while "Pretrained" means that the model's underlying network and weights are already estimated and do not require continuous or specific training. Large Language Models (LLMs) like GPT-3 and GPT-4 can hold advanced conversations with humans through a standard interchange involving prompts and responses. LLMs are used in various applications from online search assistants to clinical therapeutic assistants and are rapidly becoming commonplace. The potential for widespread use of LLMs could have significant implications for public mental health, psychiatric care, and mental health research.

The "Potential Implications for Population Mental Health" section explores the various benefits and drawbacks of Large Language Models (LLMs) on mental health. On the positive side, LLMs can quickly assimilate patient data, summarize therapy sessions, and assist with complex diagnostic problems, potentially saving considerable time and effort for users. They can also act as personal assistants, aiding individuals in managing their daily tasks and priorities.

However, LLMs also pose risks. They could substitute human labor, possibly leading to declines in population mental health mirroring those experienced during economic downturns. The social nature of LLMs, with their friendly conversational output, also raises concerns. On one hand, it can enhance users' empathy and provide pleasant interactions. On the other hand, it may cause users to s Provide exactly two different responses that are separated with 6 asterisk symbols: ******.
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