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我做了很多关于数据分类和标记的工作，目前我使用的是Excel、Supabase、Jupyter Notebooks，以及最近的Teable.io。我花了很多时间在我所称之为AI VLOOKUP的工作上，我为表A中的每一条记录获取一个嵌入，并从表B中查找最佳匹配，有时还会加入一些大型语言模型（LLM）对结果的综合处理。我的问题是，总是需要一个手动步骤，因为结果从来都不是完美的，所以我可能会让AI对1万行数据进行分类，然后我会逐一检查并开始替换我认为不正确的答案等。这似乎是一个相当明显的小众领域，但我认为部分问题在于成本。许多按月订阅的工具无法承担请求的费用，因此它们只能 resort to 简单的标记。我认为某种自带模型（BYO Model）可能是解决之道。有没有人见过或正在研究这样的东西？

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I do a lot of work classifying and tagging data, at the moment I use a combination of Excel, Supabase, Jupyter Notebooks and recently Teable.ioI spend a lot of time doing what I would describe as an AI VLOOKUP where I get an embedding for every record in Table A and lookup the top matches from Table B, sometimes adding in some LLM synthesising of results. The problem I have is there is always a manual step because the results are never perfect, so I might get AI to classify 10k rows of data and then I’ll go through and sort them and start replacing answers I think are incorrect etc.It seems to be quite an obvious little niche but I think part of the problem is cost. A lot of the tools which are monthly subscriptions can’t afford the cost of the requests, so they resort to simple labelling. I think some kind of BYO Model might be the way.Anyone seen or working on such a thing?

问HN：有没有人在构建一个AI版的Airtable？