【day60】

有n（2≤n≤20）块芯片，有好有坏，已知好芯片比坏芯片多。

每个芯片都能用来测试其他芯片。用好芯片测试其他芯片时，能正确给出被测试芯片是好还是坏。而用坏芯片测试其他芯片时，会随机给出好或是坏的测试结果（即此结果与被测试芯片实际的好坏无关）。

给出所有芯片的测试结果，问哪些芯片是好芯片。

#include<iostream>
#include<vector>
using namespace std;
vector<int>ans;
int n;
int a[20][20];
bool found;
bool rightchip(int row) {
	if (ans.empty())return true;
	for (int i = 0; i < n; i++) {
			if (a[ans[0]][i] != a[row][i])return false;
	}
	return true;
}
void dfs(int cur,int target) {
	if (found)return;
	if (target == 0) {
		for (int c : ans)cout << c+1 << " ";
		cout << endl;
		found = true;
		return;
	}
	//1、剩余的芯片小于还需要达成的目标数
	//2、最后一块芯片已经检查完了
	if (n - cur < target || cur == n)return;
	//不选
	if (!found)dfs(cur + 1, target);
	//选
	if (rightchip(cur)) {
		ans.push_back(cur);
		dfs(cur + 1, target - 1);
		ans.pop_back();
	}
}
int main() {
	cin >> n;
	for (int i = 0; i < n; i++) {
		for (int j = 0; j < n; j++) {
			cin >> a[i][j];
		}
	}
	for (int i = n; i > n / 2; i--) {
		ans.clear();
		found = false;
		dfs(0, i);
		if (found)break;
	}
	return 0;
}

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生成式人工智能是AI科技的一种分类，能生成新内容，比如文本、图像和音频。与传统分类模型不同，生成式模型学习数据的分布情况，然后生成以已学习的模式为基础的新样本。在近些年，随着深度学习技术的进步，生成式模型在许多领域已达到非凡的成就。生成式对抗网络和大型语言模型能生成高质量图像和自然语言文本。这些技术拓宽了许多领域的应用前景，比如文本创造、智能助手和虚拟现实。生成式AI同样带来许多挑战，比如不实信息的扩散和版权保护议题。因此，如何去加强。管理当推动科技进步已经成为重要的研究主题。

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