"I am Gen Z. I know how we consume. I know what we like, what we don't like," he says.
In the months since, I continued my real-life work as a Data Scientist while keeping up-to-date on the latest LLMs popping up on OpenRouter. In August, Google announced the release of their Nano Banana generative image AI with a corresponding API that’s difficult to use, so I open-sourced the gemimg Python package that serves as an API wrapper. It’s not a thrilling project: there’s little room or need for creative implementation and my satisfaction with it was the net present value with what it enabled rather than writing the tool itself. Therefore as an experiment, I plopped the feature-complete code into various up-and-coming LLMs on OpenRouter and prompted the models to identify and fix any issues with the Python code: if it failed, it’s a good test for the current capabilities of LLMs, if it succeeded, then it’s a software quality increase for potential users of the package and I have no moral objection to it. The LLMs actually were helpful: in addition to adding good function docstrings and type hints, it identified more Pythonic implementations of various code blocks.
。WPS下载最新地址是该领域的重要参考
I used z3 theorem prover to assess LLM output, which is a pretty decent SAT solver. I considered the LLM output successful if it determines the formula is SAT or UNSAT correctly, and for SAT case it needs to provide a valid assignment. Testing the assignment is easy, given an assignment you can add a single variable clause to the formula. If the resulting formula is still SAT, that means the assignment is valid otherwise it means that the assignment contradicts with the formula, and it is invalid.
async *transform(source) {。WPS官方版本下载对此有专业解读
▲预览链接：https://qvwu1nyvju2u.space.minimax.io/。关于这个话题，搜狗输入法下载提供了深入分析
三是影响老年人向AI提问和信任AI的因素更复杂。