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DeepMind的AI学习超越人类的关系推理水平 – 译学馆
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DeepMind的AI学习超越人类的关系推理水平

DeepMind's AI Learns Superhuman Relational Reasoning | Two Minute Papers #168

亲爱的学霸们 这是由Károly Zsolnai-Fehér带来的两分钟论文
Dear Fellow Scholars, this is Two Minute Papers with Károly Zsolnai-Fehér.
这篇文章出自谷歌DeepMind公司的一群家伙们
This paper is from the Google DeepMind guys,
它讲述了关于教导神经网络进行相关关系的推理
and is about teaching neural networks to be capable of relational reasoning.
这意味着我们可以利用图像提出算法 询问相关
This means that we can present the algorithm with an image and ask it relatively complex
的复杂问题
relational questions.
例如 如果我们展示图片并向它询问” 最靠近蓝色物体的物体是什么颜色? “时
For instance, if we show it this image and ask “What is the color of the object that
它就会回答”红色”
is closest to the blue object?”, it would answer “red”.
这是一个特别困难的问题 因为算法处理的是一堆像素
This is a particularly difficult problem because all the algorithm has access to is a bunch of pixels.
用代码实现的数学表达法几乎不可能描述图像中的
In computer code, it is near impossible to mathematically express that in an image, something
相邻或相接这种信息 特别是在三维空间中
is below or next to something else, especially in 3 dimensional scenes.
除了列出颜色外 这还需要对整个图像有认知和理解
Beyond a list of colors, this requires a cognitive understanding of the entirety of the image.
这是我们人类所擅长的 但是计算机算法
This is something that we humans are amazingly good at, but computer algorithms are dreadful
并不擅长
for this type of work.
这种工作几乎就像教学习算法理解人类常识一样
And this work almost feels like teaching common sense to a learning algorithm.
本方法通过注解和已有的神经网络加上一个
This is accomplished by augmenting and already existing neural network with a relational
关系神经模块来完成
network module.
这是在 所谓长短期记忆(LSTM)的循环神经网络
This is implemented on top of a recurrent neural network that we call long short-term
基础上实现的 它能处理序列信息 如输入判据
memory or LSTM, that is able to process sequences of information, for instance, an input sentence.
本节目的老司机们都知道我们在往期节目里讨论过LSTM
The more seasoned Fellow Scholars know that we’ve talked about LSTMs in earlier episodes,
当然 同以往一样 描述区里会包含这些节目的链接
and of course, as always, the video description contains these episodes for your enjoyment.
一定要看看哟 你会爱上它的
Make sure to have a look, you’ll love it.
从结果我们可以看到 这种推理关系同样也适用于
As you can see in this result, this relational reasoning also works for three dimensional
三维场景
scenes as well.
论文结果表明 这种方法不仅是对现存算法的大跃进
The aggregated results in the paper show that this method is not only leaps and bounds beyond
而且 现在 握紧你手中的论文
the capabilities of already existing algorithms, but, and now, hold on to your papers – in
多数情况下 它也展现出超人的性能
many cases, it also shows superhuman performance.
我喜欢在机器学习论文中看这些图表 其中几个学习算法
I love seeing these charts in machine learning papers where several learning algorithms and
和人类都在进行着相同的测试任务
humans are benchmarked on the same tasks.
本文刚刚发表 一个非官方的公开实现版本就已发布
This paper was barely published and there is already a first, unofficial public implementation
同时也已有两篇研究论文将其作为参考
and two research papers have already referenced it.
这真是证明了当今机器学习难以置信的研究速度啊
This is such a great testament to the incredible pace of machine learning research these days.
说它有竞争力 都是低估它了
To say that it is competitive would be a huge understatement.
在关系推理方面实现高质量结果 是实现基础智力的重要基石
Achieving high quality results in relational reasoning is an important cornerstone for
即使现在还有很多很多的事情要做
achieving general intelligence, and even though there are still much, much more to do, today
我都能感受到 今天会是我们未来日子里重要的一部分
is one of those days when we can feel that we’re a part of the future.
同时 故障案例报告也放在论文中了 这也同样
The failure cases are also reported in the paper and are definitely worthy of your time
值得您关注
and attention.
我在获取这篇论文的连续报道授权时
When I asked for permissions to cover this paper in the series, all three scientists
有三位来自DeepMind的科学家很热心的在30分钟内回复了我
from DeepMind happily answered yes within 30 minutes.
我简直不敢相信!
That’s unbelievable.
感谢你们!
Thanks guys!
另外 这里还有一些问题听起来和IQ测试中比较容易的部分
Also, some of these questions sound like ones that we would get in the easier part of an
很类似
IQ test.
相信在不久的将来 看到学习算法能够出色的完成一套完整的IQ测试
I wouldn’t be very surprised to see a learning algorithm complete a full IQ test with flying
我也不会感到惊讶
colors in the near future.
如果你喜欢这一集 认为每月八集视频值得花费一美元
If you enjoyed this episode, and you feel that 8 of these videos a month is worth a
请考虑在Patreon支持我们
dollar, please consider supporting us on Patreon.
这样 我们可以制作出更好的视频 为您提供更好的享受
This way, we can make better videos for your enjoyment.
最近 我们实现了一个新的里程碑 这意味着这些资金的一部分
We’ve recently reached a new milestone, which means that part of these funds will be used
将被用于授权研究项目中
to empower research projects.
详细资料可以在视频说明中看到
Details are available in the video description.
感谢您的收看和大力支持 我们下期再见!
Thanks for watching and for your generous support, and I’ll see you next time.

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视频概述

AI又有了长足的进步,经DeepMind的大神研究,AI学习超越人类的逻辑推理,未来也许可以拥有自主完成IQ测试的能力。

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