在上面这个案例中，AI 精准地还原了上海的地标，并极其自然地处理了巨猫与微缩城市之间的光影和透视关系。
I wanted to test this claim with SAT problems. Why SAT? Because solving SAT problems require applying very few rules consistently. The principle stays the same even if you have millions of variables or just a couple. So if you know how to reason properly any SAT instances is solvable given enough time. Also, it's easy to generate completely random SAT problems that make it less likely for LLM to solve the problem based on pure pattern recognition. Therefore, I think it is a good problem type to test whether LLMs can generalize basic rules beyond their training data.
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var carFleet = function (target, position, speed) {
省、自治区、直辖市人民政府司法行政部门依法指导、监督本行政区域内仲裁工作。
這份報告甚至被提到國會中。當時仍屬保守黨的國會議員丹尼·克魯格（Danny Kruger MP）引用《安靜復興》報告作為證據，聲稱：「世界上正在發生偉大的事情。基督教並未被壓迫、踏扁或擊垮。」