Facebook's executives say it's not their place to decide whether an ad is true or false and supporters of the policy say that's the job of journalists anyway.

脸书高管表示他们没有义务判别广告真假，而支持这项政策人则认为，无论如何这是新闻记者责任。

We also have impressive gaze direction networks inside our brains, containing individual neurons that fire when someone is staring directly at us.

我们大脑中有着令人惊异注视方向判别系统，包括许多神经元个体 并会在我们被人注视时候发。

For expert men can execute, and perhaps judge of particulars, one by one; but the general counsels, and the plots and marshalling of affairs, come best from those that are learned.

练达之士虽能分别处理细亊或一一判别枝节，然纵观统筹、全局策划，则舍好学深思者莫属。

The generator network tries to create more and more realistic images, and these are passed to the discriminator network which tries to learn the difference between real photographs and fake, forged images.

这个成网络旨在成出更加真实相片，然后交由判别网络去找出成假片与真实片区别。

Tragic? Oh, I don't know. Her physician said to me: " If I could stretch out my hand and restore her sanity, I wouldn't do it. She's much happier as she is" .

这是人悲剧吗？ 我无法判别。 她主治医如是说：就算我可以伸出援手帮助她恢复常态，我也不会那样做。 这会儿她比神经正常她还要快乐得多。

But gradually, it was disclosed to me that the line separating good and evil passes not through states, nor between classes, nor between political parties either, but right through every human heart.

但我渐渐发现，判别善绳不是国家不是阶级，也不是政党，而是每个人内心。

They view the courses as an expensive but necessary add-on, and judge their quality by how much private investment they attract.

他们认为这种课程虽然价格高昂，却是不可缺附加课程，并且他们会根据这类课程所吸引学投资多少来判别其教学质量。

And some of them are so badly decomposed that one coast guard investigator told me he couldn't even identify their genders.

一些尸体严重腐烂，一名海岸警卫队调查人员告诉我，有一具尸体甚至无法判别性别。

And this is the judgment, that the light has come into the world.

这就是判别：光明已经来到世界上。

This is a machine-learning model with two networks: a discriminator, whose job it is to determine whether something is true or false, and a generator, whose job it is to generate synthetic media.

这是一种包含两个网络机器学习模型：一个判别器， 其任务是判断某事物是真是假； 一个成器，其任务是成合成媒体。

And this kind of gets back to this question of how generative AI is a little bit different than some of the predictive or discriminative models we've dealt with in the past.

这又回到了成式AI与过去我们处理一些预测性或判别性模型有所不同核心问题。

What are the key results, insights in this paper, and what can you say in general about the promise and power of multimodal learning?

本文关键成果和洞见包括：通过跨模态一致性实现了音频-视觉实例判别，显著提升了多模态学习性能。 总体而言，多模态学习潜力与力量体现在其能够有效整合不同感官信息， 从而增强模型理解与推理能力， 预示着在人工智能领域具有广阔应用前景。

You know how you can teII which one is the right broad?

你知道怎么判别那个婆娘最合适吗？

In the application of simultaneous identification of gender and variety, CNN model has the highest accuracy of 94%, LDA model has the medium accuracy of 92.5%, and SVM model has the lowest accuracy of 89.5%.

在性别与品种同时识别应用中，卷积神经网络（CNN）模型确率最高，达到94%，线性判别分析（LDA）模型居中，确率为92.5%，而支持向量机（SVM）模型确率最低，为89.5%。

I think from the technology point of view, one challenge about this stuff from my perspective is that You know, when you are dealing with a kind of predictive modeling, discriminative modeling world, it's a little easier to measure things.

从技术角度来看， 我认为在我看来，这方面一个挑战是，当你处理是一种预测建模、判别建模领域时，衡量事物会稍微容易一些。

Se veral machine learning algorithms (logistic regression, decision tree, support vector machine, k-nearest neighbor, linear discri minant analysis, and ensemble learning) were used to discriminate between disease groups: healthy, symptomatic HLB-infecte d, and asymptomatic HLB-infected, based on leaf reflectance.

采用了多种机器学习算法（逻辑回归、决策树、支持向量机、K近邻、线性判别分析及集成学习），基于叶片反射率对疾病群体——健康、症状性黄龙病感染和无症状性黄龙病感染——进行区分。