理解DeepSeek的一些局限性
最近我向deepseek询问了如何使用JavaScript提取和处理教育领域中的Moodle数据。我注意到该程序没有考虑两个关键点：1）答案和评分必须在同一行中，这是至关重要的；2）不要修改学生的答案。在这个案例中，答案是针对十道题目的十个字母。Deepseek使用了HTML的closest方法来查找匹配的元素，这非常不安全；此外，它还用“a”填充了少于10个字母的答案，这是一种可笑的措施。这个简单的问题表明，deepseek无法考虑这两个基本事实的重要性，因此必须引入这两个关键点，以避免代码混淆学生的答案和评分。我认为这清楚地说明了deepseek当前的局限性，以及用户需要为LLM提供的上下文。似乎在编码过程中，deepseek并没有意识到可能发生的错误及其后果。因此，作为deepseek的用户，您必须为这个LLM提供这样的上下文，您需要考虑LLM即将设计的最简单程序，并提醒它特别注意，以避免完全失败，尤其是以最具破坏性的方式。
1） answerCells.forEach(cell => {
const row = cell.closest("tr");
2） return res.padStart(10, "a");
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Recently I asked deepseek about how to use javascript to extract and makes computations with moodle in education. I note that the program did not consider two crucial points: 1) It is of utmost importance that the answer and the grade of the answer should be in the same row. 2) Don't modify the answer of the student. In this case the answer are ten letters in response to a test with ten questions. Deepseek used html closest to look for matching elements what is highly insecure, also it did pack answers with less that 10 letters with "a" what is a ridicule measure. This trivial problem reveals that deepseek is not able to consider the importance of the two trivials facts and that you have to introduce those two crucials points to avoid code that can mix students answers and grades. I think this illustrates clearly the current limitations of deepseek and the kind of context you have to give the LLM to avoid it. It seems that deepseek while coding was not alert to the kind of errors that could happen and their consequences. So you, the user of deepseek must provide this LLM with that context, you must think about the most simple program the LLM is about to design and how you must alert it to have special care to avoid failing completely, that is in the most destructive way.<p>1) answerCells.forEach(cell => {
const row = cell.closest("tr");<p>2) return res.padStart(10, "a");