想象一下，一秒钟，您有一个魔术铃，当您想要它响起时可以教。您什么时候要它响？我的姿势非常糟糕，所以我希望每次懒散地响起，提醒您坐下。（也许太帕夫洛维亚人？）我们的朋友山姆想告诉它，每当bluejay（notany other kind of bird) was on their bird feeder. And our friend Kay, a musician, said he’d tell the bell to ring whenever his goldfish swam into a particular part of the fish tank (apparently he’s always wanted to use his goldfish as an instrument).

当然，可教的铃铛可能是一个愚蠢的主意。但是，这篇文章的重点是激发您思考一个更大的想法：如果您可以教日常对象对您有独特有用的东西，该怎么办？

We’ll explore this idea of “teachable technology,” and how you can create a hacky prototype using off-the-shelf electronic parts. We’ll share what we’ve learned along the way and probably end up asking more questions than we answer like:

• What would a simple, understandable teaching interface look like?
• 如何将一些教学能力放到像钟那样基本的东西中，改变人们会使用它的目的？
• 人们可能会启发哪些其他事情来使教学？
• 如果对象如此容易教导，以至于任何人（不仅是程序员）可以根据自己或其社区的独特需求来教授，该怎么办？
• 以及如何以尊重隐私的方式来完成这件事？

我们正在这篇文章中分享我们的草图，这是任何人（设计师，老师，学生）进一步探索这些想法的起点。

Our prototype

现在要制作一个魔术铃……我们使用任何人都可以购买的零件进行了一些快速的原型制作：Raspberry Pi， 一种Coral， 一种nd other DIY electronic parts via sites likeAdafruit。如上所述，它很骇人听闻！因此，这可能不是您每天在当前状态下使用的东西。但这就是使这一有趣的思想实验的原因。我们正在猜测未来，并围绕着我们所有人，作为这些系统的潜在设计师，开始一起提出问题。

One note to keep in mind as we demonstrate the prototype: We needed to write code to build this prototype, but our ultimate goal is to illustrate how a user could, one day, use a system like thiswithout any coding。They would just hook up whatever sensor or signals they wanted, and teach it just by pushing buttons.

So, it has a few basic parts: The输入，，，，which is a camera in this case (but could be other kinds of sensors). Thedecider，这是一台基本上只能决定是/否问题的答案。和输出- 我们的钟声。

For a fun test, let’s try to make the bell ding every time it senses a thumbs up.So, we’re going to teach thedecider回答简单的是/否问题：“我的拇指抬起了吗？”首先，我们在持有“是”按钮的同时对其表示赞许。然后，我们按下“否”按钮来显示它不是a thumbs up — like an empty background, my hand in other positions, and so on.

But, one nice thing we found about a simple system like this is that it lets you rapidly iterate — so, that if we find the bell is dinging when it’s not supposed to, we can quickly teach it with more yes/no examples.

An important note about privacy: In this prototype, the images from the camera stay on-device and are not saved or sent to any server. So the camera is acting less like a traditional camera, and more like a sensor. (More thoughts on this below.)

尝试一下

我们在房屋周围的不同情况下迅速尝试了原型。它很有趣！

“煎饼准备翻转了吗？”We taught the bell to ring when the pancake was ready to flip. (You know, like when you start to see bubbles!)

“Are my eggs done the way I like them?”We taught the bell to ding when the eggs were ready. This was kind of a silly use case, but it was interesting because each of us prefers our eggs a bit different — scrambled, sunny side up, and so on. It sparked interesting conversations around how we could one day teach computers to recognize subtle differences important to each of us.

While these are just a few fun silly experiments we did around the kitchen, there’s no reason why it couldn’t be extended to other things like sensing when a hummingbird is at its feeder, letting you know when you’ve started to slouch, and so on.

Thought Starters

这种“可教技术”的想法（使任何用户能够使用AI轻松教授他们的技术）并不是一个新想法。但是最近我们看到了越来越兴趣，尤其是对使用的人Teachable Machineto explore their own ideas, teaching their own machine learning systems for可访问性，，，，设计/创造力， 一种nd more. The goal isn’t a future with lots of ringing bells, but one where technology is more accessible for everyone, as something that can be taught by anyone — not just techy folks.

如果您有兴趣探索teachable technology，，，，here are some thought starters:

• 隐私。对我们来说，以隐私尊重的方式设计该系统很重要。我们通常认为相机是捕获和存储图像。但是在这里，摄像机的作用更像传感器，没有存储图像或离开设备。但是，将来我们如何设计这样的系统，以便每个人都很容易理解隐私的关键方面？
• 用户作为程序员。您今天在设备上使用的大多数AI系统都是预先构建的。但是像这样的系统将更多地作为空白的板岩到达您的手中，随时可以由您教授。您成为程序员。但是，您没有编写代码行，而是以身作则。
• Custom AI systems uniquely helpful to you.我们为教学技术如何使任何人都能为其独特需求创建自定义AI系统感到兴奋。这样的系统可以使人们能够快速修改并为自己，家庭或社区尝试想法。

Links

该原型仅刮擦表面。当然，我们并不孤单地探索这些想法。这是您可能需要检查的其他过去和当前项目。我们希望这篇文章能激发您进一步探索这些想法。

• Teachable Machine
• 可教的分类器
• Coral.ai
• 可教蛇（Vince Mingpu Shao）
• 对象文件（由Bjorn Karmann撰写）
• Wekinator（作者：丽贝卡·费伯林克（Rebecca Fiebrink））

关于创作者：

Lucas Ochoa，，，，Gautam Bose， 一种nd艾萨克·布兰肯史密斯are creative technologists at Google that are passionate about making technology more accessible for all makers, especially when it comes to machine learning and physical computing.

合作者：Alexander Chen，Jonas Jongejan，Nicole Bleuel