以下是为您提供的关于 AI 相关产品规划的回答：
一、插件/工具能力在大模型生态架构中的环节、定位、实现流程
从 2023 年 3 月份 OpenAI 宣布插件计划开始，到 5 月份上线，其中包括联网、代码、画图三个插件。其实现流程大致为：
二、对于搜索团队，插件可以做和应该做的事
目前没有直接针对搜索团队插件具体可做和应做事项的明确内容，但可以参考 OpenAI 的插件计划，例如开发与搜索相关的特定功能插件，或者探索如何将现有的搜索推荐功能与大模型更好地结合。
三、对于大模型无法绕开或高频使用的模块/功能/插件
目前没有直接指出对于大模型无法绕开或高频使用的具体模块、功能或插件。但从相关信息中可以推测，例如与数据获取和处理相关的插件（如联网）、与技术开发相关的插件（如代码）以及与内容生成相关的插件（如画图）可能是较为重要和高频使用的。对于搜索团队来说，可以考虑在这些方向上寻找发力点，结合搜索推荐等传统功能，开发出更具竞争力的插件。
从2023年3月份，OpenAI宣布插件计划开始，到5月份上线，其中包括OpenAI的三个插件：联网、代码、画图。[heading2]二、Function calling函数调用[content]经过对模型的微调，既可以检测何时需要调用函数（取决于用户的输入）也可以使用符合函数签名的JSON进行响应。函数调用使开发人员能够更可靠地从模型中获取结构化数据。在接口层面你就可以声明有哪些工具可以调用1.使用函数和用户输入调用模型2.使用模型响应调用API3.将响应发送回模型进行汇总[heading2]三、插件市场All Tools[content]让全球的开发者主动帮助OpenAI写Function call，允许第三方开发者来开发可调用的Function call限制：只能在OpenAI的ChatGPT Web使用，不能再其他地方复用。Q:有没有一种标准协议，让所有AI应用能使用相同的方式访问工具呢？A:MCP
125 What is the UK constitution?The Constitution Unit,University College London,2023.55A pro-innovation approach to AI regulation1.84.Tools for trustworthy AI like assurance techniques and technical standards can support supply chain risk management.These tools can also drive the uptake and adoption of AI by building justified trust in these systems,giving users confidence that key AI-related risks have been identified,addressed and mitigated across the supply chain.For example,by describing measures that manufacturers should take to ensure the safety of AI systems,technical standards can provide reassurance to purchasers and users of AI systems that appropriate safety-focused measures have been adopted,ultimately encouraging adoption of AI.2.85.Our evaluation of the framework will assess whether the legal responsibility for AI is effectively and fairly distributed.As we implement the framework,we will continue our extensive engagement to gather evidence from regulators,industry,academia,and civil society on its impact on different actors across the AI life cycle.This will allow us to monitor the effects of our framework on actors across the AI supply chain on an ongoing basis.We will need a particular focus on foundation models given the potential challenges they pose to life cycle accountability,especially when available as open-source.By centrally evaluating whether there are adequate measures for AI accountability,we can assess the need for further interventions into AI liability across the whole economy and AI life cycle.Consultation questions:L1.What challenges might arise when regulators apply the principles across different AI applications and systems?How could we address these challenges through our proposed AI regulatory framework?L2.1.Do you agree that the implementation of our principles through existing legal frameworks will fairly and effectively allocate legal responsibility for AI across the life cycle?L.2.2.How could it be improved,if at all?
91.We recognise that industry,academia,research organisations and global partners are looking for ways to address the challenges related to the regulation of foundation models.129 For example,we know that developers of foundation models are exploring ways to embed alignment theory into their models.This is an important area of research,and government will need to work closely with the AI research community to leverage insights and inform our iteration of the regulatory framework.Our collaborative,adaptable framework will draw on the expertise of those researchers and other stakeholders as we continue to develop policy in this evolving area.92.The UK is committed to building its capabilities in foundation models.Our Foundation Model Taskforce announced in the Integrated Review Refresh 2023130 will support government to build UK capability and ensure the UK harnesses the benefits presented by this emerging technology.