Original video in Chinese.
Key Takeaway
- Google’s Learn about is an AI product built specifically for learning, and when combined with NotebookLM it can cover every learning scenario.
- Learn about can provide a systematic learning framework and guide users into deep learning.
- Through the roles of AI assistant and AI teacher, the product helps users acquire, organize, and learn knowledge from the internet.
- The combination of Learn about and NotebookLM reflects Google’s proposed learning method for the AI era: Conversational Learning.
- The article emphasizes that RAG will become standard for AI-native applications, serious production is the most valuable scenario for AI application deployment, and AI will completely change the way we learn.
Google is about to launch another hit!
Learn about is built specifically for learning. Whatever you want to learn or understand, you can just ask in the chat box. It lays everything out clearly for you. Combined with the earlier NotebookLM product, it basically covers all learning scenarios.
For example, let’s say you want to learn Python.
If you have a textbook or some materials on hand, then use NotebookLM. Upload the documents, and it will help you go through them first, give you summaries, outlines, and so on, so you can get a holistic understanding. Then, in the form of questions and answers, you can dig into the details under the AI’s guidance. Along the way, whenever you want to know something, the AI will answer based on the materials.
What if you don’t have anything on hand? No problem, the internet has everything, and Learn about can handle it. It is your AI assistant, helping you find all the materials on the web related to the topic. It is your AI teacher, organizing the materials it finds in a highly logical way, then teaching you within a larger framework and answering all your questions.
The newly released Learn about, combined with the already wildly popular NotebookLM, is Google’s proposed learning method for the AI era: Conversational Learning.
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Back to today’s topic: Learn about.
This product is still in its early stages. Like NotebookLM when it first launched, it is restricted to certain regions and does not yet support Chinese. Actually, it can answer in Chinese, but as soon as it starts speaking, it gets cut off and then a prompt says it’s not supported. So let’s just wait patiently; I’m guessing it’ll be opened up in two or three months.
When I first used it, I was a little confused: isn’t this just a question-answering engine? Because I casually asked it a question, and Learn about did exactly what Perplexity does—searching the web, giving an answer, and providing sources. But when I seriously asked it how to learn Python, I realized the true power of this product.
Learn about is especially good at providing a systematic learning framework. Take learning Python as an example. In the fundamentals section, it gave a learning outline and suggested starting with five parts: data types, variables, operators, control flow, and functions. Each part has its own expansion. For example, data types include strings and so on.
You can start learning from any part you like. Don’t worry about losing track of the original framework—it’s placed in the left sidebar, where it can be collapsed or expanded and serves as navigation. We can always know which part the point we’re studying belongs to, constantly reinforcing that big-picture view.
Likewise, if a sub-framework appears, it will also be added to the left sidebar. This avoids the situation where layers pile on top of layers and everything ends up a complete mess.
The reason I think this feature is so important is that no matter what you’re learning, you must first build a systematic framework, outline, or mind map. That is the most important thing. Once you have that, then you can dig into the details and then into the individual knowledge points. I also emphasized this point in the video where I previously recommended NotebookLM: a holistic understanding is the foundation of “actually learning.”
If you look at today’s education, you’ll find that it’s all about obsessing over knowledge points. No wonder the students it produces end up with empty heads and become useless.
I’ve gone off topic. Let’s get back to Learn about.
In terms of product features, Learn about makes extensive use of the same question suggestions and guided learning approach as NotebookLM. If you’re just starting and don’t have much of a concept yet, let the AI guide you and gradually go deeper through conversation.
During this process, if you feel the AI is explaining things too shallowly, you can click Go deeper and let it explain in more detail. Likewise, if you feel it’s going too deep and becoming hard to handle, you can also have the AI explain it in a more accessible way. Also, at any time, if you see a concept you don’t understand, just select it and let the AI explain it. Features like these preset functions may be small, but they’re especially practical. Google really put thought into this.
Learn about and NotebookLM are both products about learning, but their positioning is not quite the same. NotebookLM is more of an assistant, helping you understand and digest documents. Learn about, on the other hand, is in a leading position, teaching you like a teacher. So during the teaching process, it will add little questions and mini quizzes, reinforcing your understanding through a simple multiple-choice question—these are all signs of the product’s proactivity.
After using it for these past few days, I’ve already decided to add Learn about to my AI toolkit. If I want to learn something, I’ll use it. If I want to look something up, I’ll use Perplexity. If I want to discuss something, I’ll use Claude.
I’ve found that the three judgments I’ve shared gradually in the community before still hold true:
First, RAG will become standard for AI-native applications. Look, both NotebookLM and Learn about are based on RAG, and they’ve made a lot of magic with this technology.
Second, in the stage where AI applications are being deployed, serious production is the most valuable scenario. Look at the products that became popular this year and are doing well—they’re all in this direction. Non-serious production products will only have a chance to appear in large numbers once AI terminals become widespread.
Third, AI will completely change the way we learn. As long as you want to, you can definitely learn it. So in the future, the world will be divided into two kinds of people: those who want to learn, and those who don’t. For those who don’t want to learn, AI will create massive amounts of entertainment content to feed them. And those who do want to learn will become the builders of the new world.
OK, that’s it for this episode. If you want to discuss AI, come to our newtype community. See you next time!