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Opening the Black Box: How MyComputerBrain Complements Teachable Machine and Sci-kit AI
- Digital Technologies Institute PTY LTD
- Mar 26
- 3 min read
G’day! If you’re keen to learn about AI, you might have already had a crack at Teachable Machine or Sci-kit AI (scikit-learn). Both are brilliant in their own way—Teachable Machine offers a slick, user-friendly interface, while Sci-kit AI lets you build models with just a few lines of code. But here’s the thing: neither tool shows you what’s happening under the hood. That’s where MyComputerBrain™ (MCB) steps in.
Teachable Machine: Great for Getting Started, But What’s Behind It?
Teachable Machine is a fantastic way to dip your toes into AI. Its interactive design makes it easy for anyone to train models for image, sound, and even pose recognition. However, while its friendly interface is a real winner for beginners, it tends to hide the inner workings of the model. You get the output without really seeing how the AI makes its decisions—a bit like watching a magic trick without knowing the secret.
Sci-kit AI: Quick, Simple, and a Bit of a Black Box
On the flip side, Sci-kit AI is excellent if you’re after quick results with minimal fuss. Its code-driven approach means you can build and test models in no time. But just like Teachable Machine, it often leaves you wondering: what exactly is happening inside those few lines of code? The internal processes—the nitty-gritty of data handling, feature selection, and algorithm tuning—remain largely hidden from view.
MyComputerBrain: Let’s Open That Black Box!
MyComputerBrain™ is an Aussie-made educational platform designed by the Digital Technologies Institute. It’s built to demystify AI by taking you step-by-step through the inner workings of neural networks. Here’s how MCB complements the other tools:
Interactive, Hands-On Learning: MCB doesn’t just let you use AI—it shows you how it ticks. The platform offers interactive experiments that break down complex AI concepts into manageable lessons. You can watch in real time as data flows through a neural network, seeing every decision and adjustment as it happens.
Embedded Safe AI: One of the real beauties of MCB is its in-house developed safe AI, which runs right in your browser. This isn’t just about safety and data privacy; it’s about giving you a clear window into how AI operates. You get to see how a neural network learns and adapts, which is something you won’t get with Teachable Machine or Sci-kit AI.
Guided Learning with Immediate Feedback: MCB is all about making AI accessible. It breaks down learning tasks into guided steps, providing immediate feedback along the way. This approach helps you build a solid understanding of AI’s internal processes, bridging the gap between using AI tools and truly understanding them.
Complementary to Existing Tools: While Teachable Machine and Sci-kit AI are great for getting started, they often leave you in the dark about what’s really happening under the hood. MCB fills that gap, allowing students to explore the mechanics of AI. It’s like having a behind-the-scenes tour of an AI’s brain!
Let’s look at a typical scenario in which an AI classifies emoji into happy and sad. Here is the experiment in Teachable Machine, where you simply upload or capture images for “happy” and “sad,” train the model with a click, and instantly see the results. It’s straightforward and great for quick demos, but you don’t get to see how the AI is making its decisions. By contrast, MyComputerBrain shows you every layer of the neural network—each neuron, each connection—and how they interact to produce the classification. You’re not just getting a final “happy” or “sad” outcome; you’re actually watching the AI learn, step by step, which helps demystify that so-called “black box.”
Here’s another scenario from the field of STEM: using AI to find the best-fit curve for data from a chemistry class. In this case, a student measured reaction times at different temperatures—30, 40, 50, 60, and 70 degrees Celsius—and plotted the results. With Sci-kit AI, you can whip up a few lines of code, train a model, and get a neat curve over your data points. It’s quick, but again, you don’t really see how the algorithm is tuning itself. MyComputerBrain, however, peels back the layers by showing how each neuron in the network adjusts its weights in real time to match the measured data. It’s like getting a backstage pass to watch the AI “learn” the relationship between temperature and reaction time, which helps students truly grasp what’s happening behind that best-fit curve.
Wrapping It Up
In a nutshell, if you want to get a deeper, more transparent insight into how AI really works, MyComputerBrain™ is the perfect mate to Teachable Machine and Sci-kit AI. By opening up the black box, MCB not only enhances your understanding but also inspires confidence in your ability to tackle more advanced AI challenges down the track.
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