I'm talking organizing your notes.

Gone.

Formatting your notes.

No more.

Searching your note stop and trying to find that one thing you know you saved but can't locate.

That is going to be gone forever.

It's a new platform that Google just released to the public called Notebook LM.

In this video, I'll show you what Notebook LM is, how it works, and how you can get started using what I believe is the best software ever created for leveraging AI in creative work.

Anything Google created in this arena would already be interesting and worth investigating because it's Google.

They have some of our most valuable data, some of the most powerful AI models, such as the recently released Gemini, which Notebook LM uses, and quite a track record for, you know, completely reshaping our relationship to information.

But there's another wrinkle.

One of the leaders and creators of the project is Stephen Johnson, multiple-time best-selling author and the person who introduced me to tools for thought, the general category that includes second brains.

Stephen joined a team at Google Labs to create a completely different kind of AI that we have not seen before.

And let me tell you, it's the closest one yet to the vision of a true second brain I've been pursuing for years.

Let's begin with a little getting started guide.

Start by visiting notebooklm.google.com and either creating an account or you can sign in with one of your existing Gmail accounts.

Sign up is limited to users in the U.S. who are 18 years or older at the time that I'm filming this video.

Once you're inside, this is the interface you'll see.

Everything in Notebook LM is organized in notebooks, each of which is like a single contained space for all the information related to a specific project such as a piece of writing.

You can create a new notebook by clicking this plus button right here and give it a title such as personal ruggedization.

This was an online course that I took recently that I'd like to organize and distill some of my takeaways.

This is the main interface that you'll be using to interact with Notebook LM and there's three main things to pay attention to.

The first one is the column on the left, which is the sources column.

This is really the main feature that Notebook LM has, which is you can click that plus button and choose from different existing documents from which the AI will draw its knowledge.

And the three kinds of sources you can use are Google Drive documents stored in your own account.

You can upload PDFs and you can copy and paste text directly from other places such as a note-taking app.

For my example, I'll use my Google Drive.

You can select up to 20 different documents in Drive and each one of those documents can have up to 200,000 words, which means you can interact with up to 4 million words of text.

That's a far larger context window than any other AI tool out there.

I'll go ahead and select my notes on that personal ruggedization class that I took recently and say insert.

And I want to show you what happens.

So first of all, that source appears here in the left.

If I click the source, a couple things happen.

First of all, the AI creates kind of a, almost like a summary or an abstract of this source.

And these are some of the key topics.

And then if I want to actually see the full contents of the source, I can just scroll down here.

I want to add a few more sources because the real power of Notebook LM is not working with one source.

It's working and drawing from multiple sources all at the same time and simultaneously.

So what I'm going to do is click add source and add a few more Drive documents.

And what I'm going to do is navigate to a folder where I have saved all the notes on every book and article I've read over the past few years.

Later on in the video, I'll show you how I was able to generate all of these documents.

And what I want to ask myself is what have I already read in the past and even taken notes on that might contribute to and be a useful resource in what I'm working on today?

So I'm just going to go through this list briefly and select any other documents that kind of strike me as potentially relevant.

Here's one about what the world might look like in 2312.

This is a good book here about the power of constraints, climate change, which is the topic of the course that I took, even about what it might look like to terraform other planets, such as in the science fiction book, Blue Mars, some big picture perspective about our place in the universe, designing for behavior change, because we may need to have a lot of behavior change when it comes to preparing for climate change.

I'm really just kind of noticing which books would jump out at me as in some way related to the topic at hand.

So it looks like I have 13.

I'm going to go ahead and click insert.

All of the sources that I chose are now being added to the sidebar.

So let's talk about the two other spaces that you're going to be working with.

And now that we have all of our sources loaded up, the main one is this little box down here, which is really like other chat based AI tools, such as chat GPT that we're used to.

You're basically going to have a conversation with the AI, but drawing on the sources over there in the left.

So I could say something like create an outline of the main ideas related to personal preparation for climate change found in these sources.

Hit enter.

You can see it takes a minute.

And there we go.

It's a hierarchical, highly structured outline with main points and then supporting points or evidence or expanding on those points underneath each one.

And they're kind of in order from early things that you'll need to think about to much later things.

This is just the first step.

There's a few different directions that we could go from here.

The first thing is I could ask it one of these suggested questions that you see down here.

You can see I can actually scroll right and left.

And what's interesting is they're based on this particular text.

So they're not just generic ones that appear the same way every time.

So things like what are the three main things to consider?

So let's say I just want something really snappy, really succinct.

I could click that.

It will ask that question.

And there you go.

It's kind of distilled it down to the three main things that I need to know.

What are some ways that individuals can prepare for and respond to both the personal and societal changes that are likely to occur as a result of climate change?

Let's try that one.

As it's working behind the scenes, I'm really having a conversation.

I can ask it to expand or to distill.

I can ask it to give me more information on one point, but not others.

I can ask it to give me different formats, like write this as a poem, write it as a narrative, write it as a question and answer, FAQ format.

You can see in this case, it's sort of adapted the content to really be focused on personal preparation, which is the angle that I'm most interested in.

There's one more, the third of the main three interfaces that you need to know about.

If you get a response, let's say this one that you especially like, you don't want to lose it.

This is a free-flowing conversation.

So you might think, well, if I keep going and keep conversing, I'm going to lose track of some of these great responses.

All you have to do is click this little pin icon and it saves to this big space up here, taking up the top of the screen.

You can think of this as a kind of pin board, where you are pinning these kind of little cards with interesting information that the AI has given you, just so that you keep them top of mind and easy to see and easy to reference.

One more cool detail here.

Let's say in the midst of your work, you realize, oh, there's another source I'd like to add.

You can always click right here where it says add note and either copy and paste from somewhere.

For example, your note-taking app or something that you found online or something from an email, or you can just write directly into the note.

For example, let's say I remember that the creator of that course that I took, his name is Alex Stephan, recently wrote a piece on Substack that is much more recent and much more timely.

And I want to also incorporate that writing and that thinking into what I'm doing.

What I can do is head over to Evernote.

Here is the excerpts from his article.

I'm going to do command A for select all.

I'm going to copy all that text and put it right into a new note.

And now what it will do is allow me to check this box right here and incorporate what I've just added right into the conversation.

That was a very basic tour of three of the main areas that you are going to need to pay attention to to use Notebook LM effectively.

What Google has done is basically redesigned a note-taking app from scratch with modern AI in mind.

You still need to take notes, but you can just kind of dump them into one giant pile and use the AI to sort through and make sense of them rather than having to meticulously organize things in files and folders.

Notebook LM is different from other AI tools such as ChatGPT because you can train it on a specific set of documents you know and trust.

That could be excerpts from books you've saved, notes you've taken in class, highlights from articles or web pages, or your own thoughts.

This is called source-grounded AI.

You point the AI at a specific set of documents, effectively giving it instant expertise in whatever knowledge they contain.

So you always know it's only drawing on authoritative, private, trusted information.

Next, I want to take a look at some of my favorite use cases that I've been using Notebook LM for.

Sometimes I'm reading a difficult, complex piece of writing such as an academic paper, and I just need some help understanding it.

What you can do is upload a PDF of what you're reading.

This is a paper about the role of forgetting and learning.

I'm going to go ahead and select it and say, what is the role of forgetting and learning?

So you can see here it's basically summarized what is quite a long technical paper into something that I can understand.

So I noticed one of the points here, which is that knowledge can sometimes have a negative value, kind of piques my interest.

And the amazing thing about this conversational interface is I can now ask, what are some examples of ways knowledge can have negative value?

That's kind of confusing to me.

So you can see here, this is fantastic.

Knowledge that's incorrect.

Redundant knowledge.

Harmful knowledge.

So imagine if I'm working on a project where I'm trying to convince, let's say, an IT administrator to not save every file that's ever been created across the entire organization.

That's something that I could ask it to do for me.

I could say, please turn this information into a letter written to an IT admin, arguing that we don't need to preserve every document ever created by the organization.

And there we go.

Probably need some editing.

I'll definitely want to go through it and add my own touch.

But what's so neat about this is what you see right here, which is the citations.

Let's say I send this letter to the IT admin and they want to know, well, where did this come from?

What is the source?

What is the evidence?

What's the proof?

By clicking here, I can see specifically where every piece of information or fact or argument in this conversation came from.

So for example, let's click on number six here.

And not only does it show you what is the original text that it's drawing from, but over here on the left, it will open up a window and highlight in purple that piece of text in context.

This is so important.

To have value, citations need to be shown in context.

What was being argued before that up here?

What was being argued after that?

What is the holistic kind of situation in which this knowledge arose?

Let's do another one, which is meeting notes.

How often have you been a part of a meeting, let's say a long meeting, and you get the transcripts of everything that was said, but they're so long and convoluted.

You don't really want to spend the time to read through all those.

Even just the notes that you take yourself as part of a meeting that you're in.

This is a great use case for Notebook LM.

Here is a Google Doc, which is the full transcription of a phone call that I had with a client of mine who's named Duck.

And you can see it's very detailed, very comprehensive, has who was speaking, when they spoke, what they said.

So there's definitely value here.

But when I start to scroll, you can see this is 26 full pages of very detailed text.

I really don't want to spend the time to find the one or two facts or opinions or whatever it is I'm looking for from so much text.

So what I'm going to do is just copy the title of this Google Doc, go back to Notebook LM.

I've created a new notebook here called Meeting Notes.

Click Add Source.

Let's go back to Google Drive.

I'm going to paste it in the search just to make it easy to find.

There it is.

You can see one selected.

I'm going to hit Insert.

And what I can do now is essentially have a conversation with that document, which, if we look here, has over 12,000 words.

It's much, much bigger than can fit in Chat GPT, for example.

So what I'm going to ask is, what are the main points of my conversation with Doug?

So you can see here, Doug expressed interest in creating a training program.

What kind of training program?

Well, he believes a group workshop would be most effective.

What does he want to incorporate into that workshop?

Elements of my course.

I mean, this really just saved me 30 minutes to an hour at least.

So I could even go a step further.

Please create a proposal for a group workshop training program for Doug's organization.

And there we go.