The brain of a human being is far beyond what any machine is currently capable of. While it’s true that a computer can perform millions of calculation much faster than the human brain, humans can perform much more complex activities like showing emotions, balancing their bodies in highly difficult terrains, and adapting to changing environments and times. Artificial Intelligence (AI) tries to bridge the gap between what the human brain and a computer can do.

一个人的吨他的大脑远远超出了任何机器目前是可以胜任的。 的确，计算机可以比人脑更快地执行数百万次计算，但是人可以执行更复杂的活动，例如表现出情绪，在高度困难的地形中平衡身体，适应不断变化的环境和时代。 人工智能(AI)试图弥合人脑和计算机可以做什么之间的鸿沟。

One of the most successful outcomes of this, is the humanoid robot — Sophia [1], created by Hanson Robotics. The company goes on to say,

最成功的成果之一是由Hanson Robotics创建的人形机器人Sophia [1] 。 该公司继续说，

Hanson Robotics’ most advanced human-like robot, Sophia, personifies our dreams for the future of AI. As a unique combination of science, engineering, and artistry, Sophia is simultaneously a human-crafted science fiction character depicting the future of AI and robotics, and a platform for advanced robotics and AI research.

汉森机器人公司最先进的类人机器人Sophia体现了我们对AI未来的梦想。 作为科学，工程和艺术性的独特结合，Sophia既是人造的科幻人物，描绘了AI和机器人技术的未来，又是高级机器人技术和AI研究的平台。

While it may seem a fictional character and a cool concept, it may not be unreasonable to think that Sophia might even behave like you, if given a chance for a long term interaction with you. Have you ever wondered, what if you have a doppelganger AI who is just like you? It may sound both funny and spooky, but AI research may surely enable it in the near future.

虽然看起来像是虚构的角色和很酷的概念，但如果有机会与您进行长期互动，那么认为索菲娅甚至可能会表现得像您一样，这并非没有道理。 您是否曾经想过， 如果您拥有像您一样的doppelganger AI，该怎么办？ 这听起来既有趣又怪异，但AI研究肯定会在不久的将来实现。

人工智能的艰难旅程 (Uphill journey of artificial intelligence)

AI is a very difficult topic, but it’s looking promising. By the first half of 20th century, science fiction movies brought in the concepts of intelligent human-like robots and computers. However, enthusiasts didn’t take this just as a work of fiction. By early 1950s, scientists and researchers started taking interest in AI [2]. One such person was Alan Turing, a highly influential individual in the development of theoretical computer science and the famous — ‘Turing machine’. In his 1950 paper, “COMPUTING MACHINERY AND INTELLIGENCE”, Alan Turing asked a question —

人工智能是一个非常困难的话题，但是看起来很有希望。 到20世纪上半叶，科幻电影引入了类似人类的智能机器人和计算机的概念。 但是，发烧友并没有把它当作虚构的作品。 到1950年代初，科学家和研究人员开始对AI产生兴趣[2] 。 这样的人就是艾伦·图灵(Alan Turing)，他在理论计算机科学的发展中非常有影响力，并且是著名的“图灵机”。 艾伦·图灵(Alan Turing)在其1950年的论文“计算机与智能”中提出了一个问题-

Can machines think ?

机器可以思考吗？

Turing was curious to discover, that if humans can assimilate information from their surrounding to learn and make decisions, why can’t computers do the same ? Since then, AI research has interested a huge numbers of researchers and received enormous funding across the world. According to International Data Corporation (IDC), worldwide spending on AI was $37.5 billion in 2019, and is expected to reach $97.9 billion by 2023 [3].

图灵很好奇地发现， 如果人类可以吸收周围的信息来学习和制定决策，那么计算机为什么不能这样做呢？ 自那时以来，人工智能研究引起了众多研究人员的兴趣，并在全球范围内获得了巨额资金。 根据国际数据公司(IDC)的数据，2019年全球AI支出为375亿美元，预计到2023年将达到979亿美元 [3] 。

Today, one of the major implementations of AI, which interacts with humans is through smartphones, laptops, and digital assistants like Siri and Cortana. They not only help you get done with your daily tasks and set reminders, but also learn your habits, your likes and dislikes, and can even detect your mood from your voice and phone usage. In a 2018 Google IO event, Google demonstrated how their assistant was smart enough to make an actual phone call to a saloon, interact with a human on the other side of the call, and schedule an appointment without a single hiccup.

如今，与人互动的AI的主要实现之一是通过智能手机，笔记本电脑以及Siri和Cortana之类的数字助手。 它们不仅可以帮助您完成日常任务和设置提醒，还可以学习您的习惯，好恶，甚至可以通过语音和电话使用情况来检测自己的心情。 在2018年的Google IO活动中，谷歌展示了他们的助手如何聪明到可以实际拨打轿车的电话，与电话另一侧的人互动以及安排约会而不会打h。

计算的进步 (Advancement in computing)

Though artificial intelligence directly does not comprise of only neural network methods, however neural network and deep learning have become increasingly crucial for the effectiveness of AI [4]. With the advancements in silicon technology, processors have become extremely power efficient, fast and reliable. Moreover, storage technology has evolved a lot over the last decade, where it has become possible to store terabytes of data in blazingly fast pocket-sized SSDs, which was impossible just a couple of years ago.

尽管人工智能不仅仅包括神经网络方法，但是神经网络和深度学习对于AI的有效性已变得越来越重要[4] 。 随着硅技术的进步，处理器已变得极其省电，快速且可靠 。 此外，在过去的十年中，存储技术已经发生了很大的发展，其中已经可以在非常快的袖珍型SSD中存储TB级的数据，而这在几年前是不可能的。

This has enabled researchers to build and train large complex neural networks [5] required for AI to emulate human like features such as feelings, and the important act of “reasonable decision making” [6]. Also, a huge number of computations can be made on these, not so power hungry processors, which are enabling better battery life for such remote applications. A huge amount of research is also going on in faster and more accurate sensors and their reliable integrations with onboard embedded systems [7], which will enable such AI to be more aware of its surroundings than ever before — may be even more than a living human !

这使得研究人员能够构建和训练AI所需的大型复杂神经网络[5] ，以模仿诸如感觉之类的人类特征以及“合理决策”的重要行为[6] 。 而且，可以在这些处理器上进行大量计算，而不是耗电的处理器，这为此类远程应用程序提供了更长的电池寿命。 更快，更准确的传感器及其与机载嵌入式系统的可靠集成也正在进行大量研究[7] ，这将使此类AI能够比以往任何时候都更加了解其周围环境，这可能比活着的更多。人类！

Faster and larger storage in a smaller form factor means that a huge amount of information can be stored within the AI hardware. This can be information which was stored by the designers of the AI, but more importantly, it will enable the AI to store information in real time — information that it experiences on interaction with the environment. This information can be used by the AI in real-time to learn new things — what is called “self aware AI” [8], that is, it knows what to learn and what not. This will enable such AI to adapt to changes and interact more realistically with the environment.

以较小的尺寸实现更快，更大的存储，意味着可以在AI硬件中存储大量信息。 这可以是AI设计人员存储的信息，但更重要的是，它将使AI能够实时存储信息 -与环境交互时所经历的信息。 AI可以实时使用这些信息来学习新事物，即所谓的“自觉AI” [8] ，也就是说，它知道要学习什么而不要学习什么。 这将使此类AI适应变化并与环境进行更实际的交互。

值得一提的是新兴的5G技术 (Worth mentioning the emerging 5G tech)

5G is beginning to emerge as a super fast network, not only for data consumption, but also near real-time remote control — thanks to its low latency. This means a lot of the AI decision can be made in the cloud, without the need for local storage. Storing and computing decisions in the cloud will not only help in a more apt decision by the AI due to the “almost infinite” knowledge available [9], but will also help keep track and control of the AI to not perform illegitimate or objectionable tasks. It is worth taking a look at the potential use cases of remote controlling devices using 5G, which was released by Ericsson.

5G由于其低延迟而开始成为一种超高速网络，不仅用于数据消耗，而且还用于近乎实时的远程控制。 这意味着很多AI 决策都可以在云中做出 ，而无需本地存储。 在云中存储和计算决策不仅会由于可用的“几乎无限”的知识而帮助AI 做出更恰当的决策 [9] ，而且还将有助于跟踪和控制AI而不执行非法或令人反感的任务。 值得一看的是爱立信发布的使用5G的远程控制设备的潜在用例。

他们了解我们的一切 (They know everything about us)

But how a doppelganger ?

但是怎么一个混血儿呢？

How can the AI think and make decisions like me ?

AI如何像我一样思考和做出决定？

Have you ever talked to your friend about buying an iPhone, and the next moment you see a Google Ad about the latest iPhone? Or were you ever looking to order food, and your favorite dish came up automatically? Or even LinkedIn suggest you a complete message with which you can reply to a connection? — you surely have experienced this !

您是否曾经与您的朋友谈论过要购买iPhone，而下一次您看到有关最新iPhone的Google广告？ 还是您曾经想点菜，而您最喜欢的菜会自动出现？ 甚至LinkedIn会为您建议一条完整的消息，您可以通过它回复连接？ — 您肯定已经经历过！

Huge tech companies like Google and Facebook are continuously collecting your data — what you search, who you talk to, whose posts you like, and even what music your like. This data is used to personalize your experience with their products, to make their products think like you ! But the scope of this information goes much beyond just content personalization.

诸如Google和Facebook这样的大型科技公司正在不断收集您的数据- 您搜索的内容，与谁交谈，喜欢的帖子以及喜欢的音乐 。 此数据用于个性化您对他们产品的体验，使他们的产品像您一样思考！ 但是，这些信息的范围远远超出了内容个性化的范围。

This data can be specifically used to train AI to behave and decide like you. With the paradigm of connected devices (smartphones and wearables), data about your sleep pattern till people who matter to you, everything in stored in the cloud. A paper in IEEE [10] also studied the use of Microsoft Kinect, a sensor which detects your posture, for robotic applications. The paper investigated how a robot can be taught indoor navigation by reverse engineering, using data collected from human subjects.

这些数据可以专门用于训练AI像您一样行为和决策。 借助已连接设备(智能手机和可穿戴设备)的范例， 有关您的睡眠方式的数据会一直存储到云中， 直到对您至关重要的人 。 IEEE [10]中的一篇论文还研究了Microsoft Kinect(一种可检测您的姿势的传感器)在机器人应用中的使用。 本文研究了如何使用从人类受试者收集的数据通过逆向工程对机器人进行室内导航教学。

Such AI, if implemented in a robot, can definitely deceive your colleagues for you in an office meeting. It will not only look and behave like you, but in some aspects may also be smarter than you in decision making — thanks to the emergence of 5G and the connected devices paradigm, which will enable the AI to stay up to date with the latest happenings. No, I am not saying that our technology is ready enough for such a move, but we may be close. The rate at which AI is developing and attracting researchers, it is not hard to imagine a future with AI all around us. But, this would lead to the next big question, which has been one of the biggest debates of the century !

如果在机器人中实现这种AI，那么在办公室会议上肯定会欺骗您的同事。 它不仅会像您一样看起来和举止，而且在某些方面可能比您更明智地进行决策 -这要归功于5G的出现和连接设备的范式，这将使AI保持最新状态。 。 不，我并不是说我们的技术已经为这一举动做好了准备，但是我们可能已经接近了。 人工智能的发展和吸引研究者的速度，不难想象我们周围的人工智能的未来。 但是，这将导致下一个大问题，这是本世纪最大的辩论之一！

它会危害我们吗？ (Would it endanger us ?)

All this might seem very cool and helpful to humans for performing tasks and in decision making. But, researchers and the non-scientific community also worry about the potential dangers it may have on us.

所有这些看起来似乎很酷，对人类执行任务和决策很有帮助。 但是，研究人员和非科学界也担心它可能对我们造成潜在的危险。

1. Decision making — Many fear that such smart decision making will make humans too dependent on AI tools to make decisions for them. As this effect will deepen, people will be forced to believe the AI without being aware of the context as to how it works, and will also handicap their independent decision making ability. [11]

   决策制定 -许多人担心这种明智的决策会使人们过于依赖AI工具来为他们做出决策。 随着这种影响的加深，人们将被迫在不了解AI如何工作的情况下相信AI ，还将削弱他们的独立决策能力。 [11]

2. Cyber threats — Cyber security has been a major concern in the modern era. As people and devices are getting more connected, the vulnerability to cyber-attackers and the potential impacts it may have, is already a startling question. With the sudden influx of AI and its exponential growth, the impacts of cyber-attacks on such technology is not fully known, and the consequences it may have on the society should not be underestimated. Issues such as data privacy also are a major concern, as more and more personal information is used by AI.

   网络威胁 -网络安全已成为当今时代的主要关注点。 随着人们和设备之间的联系越来越紧密，网络攻击者的脆弱性及其可能产生的潜在影响已经成为一个令人震惊的问题。 随着AI的突然涌入及其指数级增长， 人们尚不完全了解网络攻击对此类技术的影响，因此不应低估其对社会的影响。 随着AI使用越来越多的个人信息，诸如数据隐私之类的问题也是一个主要问题。

3. Dangers of autonomous AI — As AI is becoming more complex and smarter, it is believed that soon it will require no human input (or what is called supervised learning) to perform a task. It will be programmed to automatically learn from the environment and decide its action to perform a particular task. However, many fear that such autonomous behavior requires a strict ethical norm to be considered in the AI design [12], as it should not cause any harm or devastation in completing its objective. A write up by Stanford University beautifully illustrates this potential issue of AI.

   自主AI的危险 —随着AI变得越来越复杂和智能，人们相信很快它将不需要人工输入(或所谓的监督学习)来执行任务。 它将被编程为自动从环境中学习并决定其执行特定任务的动作。 然而，许多人担心这种自主行为需要在AI设计中考虑严格的道德规范 [12] ，因为它在完成其目标时不会造成任何伤害或破坏。 斯坦福大学的一篇文章很好地说明了AI的这一潜在问题。

AI is either the best or the worst thing to happen to humanity. ~ Stephen Hawking

人工智能是人类发生的最好或最坏的事情。 〜斯蒂芬·霍金

I would like to conclude this article by asking a question — What would you name your doppelganger? Do let me know in the comments section. I hope you liked this article and it gave you insights on how AI is becoming smart and more aware about its surrounding, and how the data explosion can lead to personalization to such a level, that your office colleagues may mistake your doppelganger for you ! For discussing this more, feel free to email me at jishnudeep.kar@gmail.com or DM me on Instagram.

在结束本文时，我想提出一个问题- 您将如何命名doppelganger？ 请在评论部分让我知道。 我希望您喜欢这篇文章，并为您提供了有关AI如何变得更加智能和对其周围环境的更多了解的见解，以及数据爆炸如何将个性化提升到如此水平，以致您的办公室同事可能会误以为是您的doppelganger！ 有关更多讨论，请随时通过jishnudeep.kar@gmail.com给我发送电子邮件，或在Instagram上发给我DM。

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