Google NotebookLM - Explained By A Learning Expert

So, a while ago, ChatBT released their study mode, which was to help people learn using AI, and Google has their own version, which is called Notebook LM. A

lot of you asked me to review it, so I spent several hours testing it, learning through it, really trying to make the most of it, and putting it through lots of different real life situations. Uh,

and I have to say that as soon as I started using it, I was pretty impressed. And the more and more I used

impressed. And the more and more I used it, the less impressed I got. I do think it can be really useful, but I think that if you've tried using it for an extended period of time, you're also

running into the same limitations as I experience probably. But the interesting

experience probably. But the interesting thing is I think there are a lot of people who think that it's really helpful for learning, but it's actually more of an illusion of learning. So in

this video I'm going to go through what notebook alm is and how it differs from chatbt. What's good about it from my

chatbt. What's good about it from my perspective as a learning coach who's worked with thousands of people and understands the learning science as well as the parts that are not so good and my

recommendations on how you can use it to make a meaningful difference to your learning efficiency. So first of all

learning efficiency. So first of all what is notebook LM? If you're not familiar it's Google's version of chatpt's study mode. It's their

all-in-one AI tool for learning. And

while it shares a lot of similarities in terms of how it behaves with something like chatbt or any other LLM, uh, one of the key differences is that it's clearly built as a learning support product. It

also consolidates a lot of really useful tools like you can get audio summaries, you can get video summaries, you can get it to generate mind maps for you, you can create flashcards automatically based on the material, uh, you can

create quizzes for yourself using the material. So, it really is pitched as

material. So, it really is pitched as your all- in-one AI learning tool. Let's

talk about how good it actually is for learning. Now, to test this, I ran

learning. Now, to test this, I ran through a couple of different scenarios.

First of all, I looked at it from the perspective of a beginner learning a new topic. The topic I chose to learn was

topic. The topic I chose to learn was some AI fundamentals. After spending a few hours learning through that, I opened up a new notebook and looked at it from the perspective of an expert or

an advanced learner trying to keep up to date with some latest research. So for

this, I used self-regulated learning and higher order thinking and new research on how AI affects that. That's a big part of my existing domain of expertise.

So I'm generally pretty familiar with the the latest science on this. So I

wanted to see how good it is at really getting into some of those detailed nuances. Now for each of these different

nuances. Now for each of these different learner scenarios, I also evaluated it based on common use cases. And there are three common use cases that I wanted to evaluate it against. The first is

intensive study. This is a situation

intensive study. This is a situation where you are sitting at your desk, you've got enough time, you've got your resources, you're dedicating hours to actually sit down and really learn through it. That's the first use case.

through it. That's the first use case.

How good is notebook LM at facilitating that? The second use case is onthe-go

that? The second use case is onthe-go learning. This is when you have 5, 10,

learning. This is when you have 5, 10, 15 minutes to top up your learning. You

might be on the bus commuting, waiting for something. If you're trying to fit

for something. If you're trying to fit in a little bit of learning while you're at work, this is usually the type of learning that you're going to be doing.

And for a lot of people, this is actually the bulk of what their learning is. And the third use case is task

is. And the third use case is task reactive. So this is when you're

reactive. So this is when you're learning specifically just to complete a task or a project that you've been given. You don't really care about

given. You don't really care about building deep expertise. You just need to deliver something and learn just enough to be able to deliver that. This

is actually probably the most common way that people tend to use AI for learning.

And a lot of the time just base Chatbt is already pretty good at this. So I

wanted to see if notebook LM is any better. Now in total I probably spent

better. Now in total I probably spent about 6 or 7 hours on testing it and really learning through it. I don't like when people review learning tools based

on what features it has. You're not

learning to experience the features of a software. you're learning to achieve a

software. you're learning to achieve a goal. And so as I was testing, yes, I

goal. And so as I was testing, yes, I was trying to think about what features they are and how helpful they are, but it was how helpful they are to me actually achieving the goal of learning in the first place. And this is the part

that I actually want to start with first before going into my findings. Uh

because I think that a lot of people feel that these AI tools are helpful for their learning because they're not actually measuring on the right goal. So

just think about this for a second. Your

win criteria whenever you're learning something is to learn, gain whatever knowledge

or skills you need in order to be able to achieve a certain objective.

And this objective could be anything like this could be completing a task. Uh

this could be you know managing a project, leading a team, it could be you know building your own expertise to be able to make decisions and solve complex problems. It doesn't really matter. But

the idea is that there's a certain level of knowledge and a certain level of skills you need to be able to achieve this objective. And in order for new

this objective. And in order for new information to come into your brain for you to learn it and for you to actually achieve the outcome that you want at the end,

you need to be able to understand that information. You need to be able to

information. You need to be able to retain that information at least long enough to be able to use it in the right way. You need to be able to understand

way. You need to be able to understand how to actually use and apply it in the way that you need to, which depends on your objective. For example, if the

your objective. For example, if the objective is I just need to know this so that when someone asks me a question, I can just spit out a fact. That's a very different type of objective to I need to

be able to manage an entire complex project with lots of moving parts and communicate that to external stakeholders who could be asking me any sort of question. That's a much higher level of expertise that you need. And so

remembering that you only win by achieving this objective if you spend a bunch of time learning new information and you feel like you're gaining lots of new knowledge and lots of new skills,

but you're not able to answer those questions or solve those problems. You haven't achieved that objective. It's

it's actually not productive. And to be able to apply your knowledge in the right way, especially for more complex situations, not only do you need to understand and retain what you've learned, but you also usually need to

see how what you've learned connects, how it connects to each other, how all the little pieces come together to serve your purpose and fit into a big picture.

Most of the time when you're learning something new and you feel like, oh, this is getting complicated, there's a lot to learn here, there's a lot to unpack, and you start feeling a little bit overwhelmed. That's because you're

bit overwhelmed. That's because you're recognizing there's a lot of moving pieces here. I don't really see how they

pieces here. I don't really see how they all connect together. I know they do connect together, but I don't know what that is and I don't know how to get there. And usually when people hit this

there. And usually when people hit this wall, that's when they look for shortcuts or alternatives. They ask

themselves, "Do I even need to learn that? Do I even need to go there?" Or

that? Do I even need to go there?" Or

they'll use AI tools to try to make that part easier. But most of the time, if

part easier. But most of the time, if you do truly need to hit the objective of using your knowledge at a high level, you need to figure that out. You need to be able to organize and navigate through

that overwhelm to create meaningful knowledge that is actually connected.

After you're finished your learning process, however long that takes, you need to be able to look back at that same new information that used to feel overwhelming. And you need to feel this

overwhelming. And you need to feel this makes sense to me. I feel this is intuitive. It was overwhelming before.

intuitive. It was overwhelming before.

I've organized it. Now it makes sense.

That's what creates confidence and that's what translates to actual results and performance. Now, you don't always

and performance. Now, you don't always need to hit that level for everything that you learn, but the real problem that AI hopefully can help us solve is when you're trying to hit that higher

level and it is feeling overwhelming.

And so, that was my win criteria. I was

thinking about it in terms of learning something to be able to use it in this complex way, explaining it to someone simply. I wanted to get to a point where

simply. I wanted to get to a point where I feel truly and genuinely confident with that knowledge. And when I look at Notebook LM and CHPD study mode actually

through this lens, it's not as impressive as I wish it would be. And

I'll explain specifically where the issues are in a bit. But first, let's go through the good parts. What is Notebook LM really good for? So, I'm going to measure this based on six different criteria. Ease of use, accuracy,

criteria. Ease of use, accuracy, effectiveness. Effectiveness being how

effectiveness. Effectiveness being how useful is it for actually achieving the goal like I just talked about. And then

the three different use cases is it good for intensive learning on the-go learning and task for active learning.

Now one of the best things about notebook LM both as a beginner learner and as an advanced learner is how easy it is to use. So if you look at how I actually used it for learning some

fundamentals of AI. Uh you can start by just discovering sources which is where you just say what you want to learn. It

will then find some relevant resources for you which you can then screen and vet uh and and check that they're the ones that you want to include. You

import those and automatically straight off that it generates you this summary.

Anything that's generated inside the central panel can be turned into a note that is basically saved like a bookmark for you to come back to and like a normal chat interface. You can then have a conversation asking it questions back

and forth and also recommends questions that might be useful for you. One thing

that you might note if you're familiar with learning science a little bit is that the questions that it's generating for you are relational higher order questions. The idea here is that it's

questions. The idea here is that it's getting you to ask questions that make you think about how each piece of information is connected to other pieces of information. And so that's clearly an

of information. And so that's clearly an attempt and a very deliberate attempt by notebook LM to get you to engage in that higher level of thinking which is necessary to achieve those more complex

outcomes like being able to see how it's all connected together. You can also see that you can generate a video overview, you can generate audio overviews, mind maps, reports, flashcards, and quizzes.

It's pretty convenient because you don't have to wait for one of them to finish.

You can basically just tick all of them if you want and it'll just generate in the background. But as it's generating,

the background. But as it's generating, you can still be exploring, you can still be reading, you can uh be generating other things. That's useful

because something like the video overview often takes several minutes for it to generate. So you don't want to be just sitting there waiting for it to generate a video the entire time. I

thought the mind map overview was pretty interesting and as you know, I'm kind of like the mind map guy. So I clicked into that and it does a reasonable job at separating out this uh topic into

logical categories. And this again helps

logical categories. And this again helps you to see sort of a big picture overview of how everything connects together. And again that's going to be

together. And again that's going to be important for you to achieve this higher level outcomes. So so far if you compare

level outcomes. So so far if you compare that to the experience of using chatbt uh even in study mode already it's doing pretty much everything that catch study

mode would do and it's doing it better and there's more things built into it.

Already it's starting to seem like notebook LM is a superior tool when it comes to learning compared to chatbt and that there's a there's a big difference between the two. As I started expanding some of these uh concepts and reading

into it a little bit more, I definitely started feeling that uh sense of overwhelm like wow, there's a lot of complexity to this. This is getting really complicated. How does it all fit

really complicated. How does it all fit in together? And again, that is that key

in together? And again, that is that key wall uh in learning that is very difficult to break and it takes a lot of training and skill and expertise to be able to uh learn through that. And so as

soon as I felt that, instead of using my normal strategies of how I would normally learn through it, I tried to stay a little bit more into the software and see if there was anything in the software that would help me break through that a little bit more easily.

One thing that often helps with reducing this overwhelm is implementing dual coding. Uh dual coding is this learning

coding. Uh dual coding is this learning phenomenon where learning is more effective when you're able to process information through both written words as well as visual. So for example, like

diagrams and pictures. So, one of my quick tips uh is just whenever you're learning a new concept, do a Google image search on it to see what diagrams and and uh like infographics people have

already created about it. And that

usually ends up speeding up the amount of time that it would take to understand that concept by a lot. I wanted to see if I can just get it to create some of these images and infographics for me and to see how accurate it was.

Unfortunately, it wasn't very successful at actually doing that. I tried it a few more times with some other things and I I wasn't really able to get something that I thought was meaningful. I ended

up just doing a Google image search anyway. One thing I did notice though a

anyway. One thing I did notice though a few times is that when it recommends a source uh and I want to read into a little bit deeper. It's a little bit hard to navigate the source guide that

appears on the left. The formatting is often broken, especially if it's coming from a PDF. And when you try to find that relevant piece of information from the original source, it's really hard to navigate and often doesn't really link

up correctly. So half the time I was

up correctly. So half the time I was left kind of just having to believe that this is true and not being able to read deeper into it. One of the sources that it recommended was this book called Mathematics for Machine Learning. Uh and

after reading through a few of the pages here, I did actually find that just reading the original book that it's referencing of was a lot easier to understand uh than the summary that it generated for me. The other thing I was

really curious about is how the video overview works. So, I checked out the

overview works. So, I checked out the video overview, played the video, and honestly really impressive. It gave me this really good big picture summary about how to think about everything. It

covered the major concepts, explained them in a way that was clear and easy to understand. And I can tell that whoever

understand. And I can tell that whoever designed this particular tool at Google.

Uh they for certain worked with learning scientists and researchers to make sure that the method of teaching follows best practice for direct instruction. It

genuinely does feel like given a little bit more time for this to refine and improve, you will be able to get to a point where you can just load up a bunch of resources and it's basically

generating you a personalized set of video lessons and curriculum that you can just learn off of. That is huge because of the fact that one of the biggest limitations when you're learning and you don't have a structured

curriculum is that you just don't know how much you need to learn. And a lot of the confusion around learning just comes from the fact that there isn't a clear structure or a clear goal. So by it

being able to kind of create this curriculum for you, I think it's a huge step in the right direction. Likewise,

the audio overview was surprisingly pretty good. What it does is it creates

pretty good. What it does is it creates this podcast using the material uh that you've given it and there is there's like one female voice and one male voice and they're sort of talking to each

other about the topic. It sounds sort of realistic. And there's this cool

realistic. And there's this cool interactive mode where you can kind of join in on the podcast. So, as you're going through the podcast, you can click join. You can ask questions about it and

join. You can ask questions about it and then it will answer you. Kind of like, you know, calling into a radio show and asking your question. Now, one of the biggest use cases for this style of audio overview and this kind of

podcasting uh is that you can now start learning on the go. So when you're on the commute, when you're driving somewhere, you can have that playing and you can be talking to it and then learning in this period of time when normally you just can't do anything

useful in that time. You're falling

asleep in traffic. And the Notebook LM team clearly thought about this because this website works very very well. If

you load it up on your phone, the interface changes, so you get these tabs. If you have an audio overview

tabs. If you have an audio overview playing, you can actually swap between the tabs. The audio does not get

the tabs. The audio does not get disrupted. There is also a quiz function

disrupted. There is also a quiz function on this which just generates you this multiple choice quiz. uh you can mark the answers that you think. It will tell you whether you're right or wrong. You

can get it to explain the answer. By

default, the quiz that it will generate for you is a little basic, which might be okay if you are a student studying for an exam. If you're trying to use your knowledge for more complex problem

solving or complex applications, it's probably not going to be enough. You can

just tune it and give it more guidance and instruction on the level of questioning that you want it to reach.

So, if you're going to use quizzes, I would definitely recommend spending a bit of time defining the types of questions that you want at the level of complexity as opposed to just using the default button where you just click the

the quiz button and it just generates it for you automatically. Now, the other major function is flash card usage. Now,

the flash cards are probably the one that I think is the least useful out of these because first of all, you actually get a very similar level of knowledge

challenge with the quiz. And the quiz is actually a superior way of testing yourself anyway. So, the two are kind of

yourself anyway. So, the two are kind of redundant. Like, if you're going to do

redundant. Like, if you're going to do the flash cards, you don't really need to do the quiz. If you're going to do the quiz, you definitely uh don't need to do the flash cards. But the main limitation here is that even though it

generates a series of flash cards which are fine, there is no way to export those flash cards and there's no space repetition timer on it. One of the biggest benefits of using flash cards is

that allows you to tackle lower order specific fine detail and train your recourse through space repetition on the go. It's sort of the most brain dead way

go. It's sort of the most brain dead way that you can improve your attention on discrete isolated little facts. And it's

an effective method for that. you you

chuck it on your your Anki or whatever app that you're using and then a little notification pops up and it says, "Hey, you need to do your flash cards because if you wait too long, you're going to forget them." And then you open your app

forget them." And then you open your app and you do them. It saves it on its algorithm. It, you know, reminds you to

algorithm. It, you know, reminds you to do it again later. And so the main benefit of flash cards is not the fact that it's involving active recall because there are many, many, many, many other ways of engaging active recall

that are vastly more effective than doing flash cards. Like for example, just quizzing yourself. The main

advantage is how easy it is to do active recall with the space repetition algorithm on the go. Like five minutes here and there when you're sitting on the toilet smashing out a few flash

cards. That's the main benefit. And that

cards. That's the main benefit. And that

benefit is not available using Notebook LM. Now, maybe I just didn't know how to

LM. Now, maybe I just didn't know how to use it properly. At least it wasn't obvious how I could take the flash cards that are generated and then export them out like as a CSV or an Excel file or

something that I could then reimpport into my flashcard app of choice. But I

definitely felt like the flash card function on Notebook LM is essentially redundant. I feel like I would probably

redundant. I feel like I would probably never need to use that button if I'm actually using this for long-term learning. So let's go to the scorecard.

learning. So let's go to the scorecard.

See how it's performing. So as a beginner learner or an advanced learner, ease of use is very very good. It's a

great interface. It's a polished product. Everything works the way that

product. Everything works the way that it's kind of meant to work. The

multimodal features like the video overview and the audio overview are surprisingly pretty good, especially given that it's a relatively new product. In terms of accuracy, uh it's

product. In terms of accuracy, uh it's actually hard to comment on this as a beginner learner because as a beginner, I don't know if it is right or wrong.

So, I'm going to defer my judgment on this. But when I used it on

this. But when I used it on self-regulated higher order learning and the impact of AI which is something that I'm very familiar with I couldn't find any technical issues actually I couldn't

even find a single factual error in there. So I say the accuracy on this is

there. So I say the accuracy on this is also very high. Now in terms of effectiveness this is where it gets questionable. When

I was testing this as a beginner learner using uh fundamentals of AI, I was looking at the mind map and I was looking at the video overview and I was looking at the audio view and interacting with that and I was thinking, okay, like it feels really

helpful. This feels really cool. There

helpful. This feels really cool. There

are certain things that have been simpler and easier for me. But that

feeling of being overwhelmed by all this information and not really seeing how it connects together never really disappeared. And actually, when I was

disappeared. And actually, when I was expanding through the mind map, even though it was kind of clear how it all comes together, cuz it's literally telling me this is how it's arranged, as I just kept expanding through it, I just started getting overwhelmed by the mind

map as well. The purpose of the mind map is to help you see how it connects together at the big picture level. And I

didn't feel like it was achieving that.

But the issues became much much clearer when I started moving into a domain that I was very familiar with. So when I looked at the mind map that it generated around self-regulated learning, the categorizations that it created were

technically logical, but they're also not the most meaningful. They're

definitely not the way that I would have organized this. I would probably never

organized this. I would probably never teach this topic in that way. And I

think trying to learn the topic in that structure, connecting it in that way, is going to make it harder than it needs to be. And it's not really intuitive to

be. And it's not really intuitive to understand. The video overview I thought

understand. The video overview I thought was actually a pretty good introduction but the audio overview and the podcast format I started feeling was less and

less valuable as I interacted with it more. one part and this is the minor one

more. one part and this is the minor one is that it has this twoperson sort of co-host dynamic in the podcast which makes it sound quite engaging but often

it gets quite distracting like one person will say one sentence and then the other person will sort of almost finish that point off. It kind of felt like I was talking to a set of

cybernetic twins that telepathically communicate with each other and one twin is finishing the other twin's thoughts all the time. this felt a little strange and it was strange enough that it was actually distracting for me from the actual point that they were trying to

make. But that's probably the the bigger

make. But that's probably the the bigger issue which is the second thing is that I don't think it does a good job of emphasizing the things that are actually important or complicated. There are

certain things that I know in the research get really deep and complicated and is a really important concept that you have to understand. If I'm teaching this and I've taught that many times before, you have to spend a decent

amount of time on that point. if you

don't understand this point, you're going to be confused about everything else after that. But in the podcast format, it's literally like one sentence and they move on from that straight away. Whereas other times, there'll be a

away. Whereas other times, there'll be a concept which is kind of interesting.

It's easy to explain. It's easy to create these examples and analogies out of, but it's actually conceptually not that important. And then they will spend

that important. And then they will spend longer on that part. And so the emphasis of which points to focus on, which parts to draw out and elaborate, which parts to really create an analogy and pace the

learner through, I think was done fairly poorly. poorly enough that if you are

poorly. poorly enough that if you are not concentrating on everything that's being said and really thinking about it deeply and you let's say for 5 seconds kind of just switch off and you don't

catch what was being said that 5 seconds could have been something that was critical and you're not even going to realize why you're confused about this topic 10 minutes later. Now, the good news is I believe based on my

understanding of the underlying technology that this is probably a current state issue and that this will get better over time. I don't see a reason why it wouldn't be able to get better at doing this. And I think if

this part is refined, that podcast audio overview format could be a really powerful tool that one day I have a sneaky feeling I'm going to start recommending that for all of my students. But as it is right now,

students. But as it is right now, unfortunately, I would probably give it maybe a three out of 10 in terms of actual usefulness and effectiveness at developing my understanding of a topic.

And I think this is actually probably even worse if you're a beginner trying to learn something because as a beginner, you have absolutely no idea that something important was skipped over. So, you don't even realize you

over. So, you don't even realize you should be interjecting and asking a question and asking it to elaborate on it because the point would just pass by.

it would just be one other sentence that you didn't fully understand and then the confusion that that creates is just going to add to your overall sense of overwhelm. But here's the biggest issue

overwhelm. But here's the biggest issue with Notebook LM, and this is not just Notebook LM. Actually, I I haven't found

Notebook LM. Actually, I I haven't found an AI tool that is able to really overcome this or even come close to overcoming this so far, which is that Notebook LM and a lot of these AI tools

are great at solving small problems that don't make much difference. And it's not very good at solving the biggest problem that makes the biggest difference to

your actual ability to learn. In fact,

I'm going to make that an even stronger statement. I think it makes it worse.

statement. I think it makes it worse.

Now, let me be clear about this. I loved

the concept of Notebook LM. I was blown away by how it works and the video overviews and the audio overviews. I

thought that was really cool. It's

heading in the right direction, but I objectively just cannot put my stamp of approval on this yet. And this actually comes down to the win criteria that I was talking about before. The hardest

part about learning and learning to a high level and trying to develop expertise and really work with knowledge in complex ways is organizing and connecting it. It's this part like the

connecting it. It's this part like the connecting information being able to apply it contextually. Like I said, when there are lots of things happening, they all connect together and you don't know how they connect. That creates

overwhelm. In learning science, we call that phenomenon multiple element interactivity. And in my experience,

interactivity. And in my experience, it's the most common reason why people feel overwhelmed when they're learning something. The reason they think

something. The reason they think something is complex or that it will take time is because they recognize multiple element interactivity. In other

words, there are a lot of elements and components and bits and pieces of information that are floating around.

They interact with each other and it's getting complicated. And the reason that

getting complicated. And the reason that happens is biological. The human brain can only process and connect a certain amount of information at one time.

Honestly, in my experience of coaching people and in my own reflection, it's really hard to mentally keep track of more than three or four connections in one go. Now, compare that to actually

one go. Now, compare that to actually learning something that's complicated, which might involve 50 different items with a 100 or 200 different connections.

Going from feeling good about a topic to feeling overwhelmed, might only take you a single paragraph of reading. And the

hallmark of a really good learner is how they navigate through that feeling. When

they're hit in the face with that overwhelm, what do they do about it?

Some people will try to take a shortcut by changing the win criteria. Instead of

saying, "Okay, this is hard. I'm going

to find a way through it." They say, "This is hard, so I'm just not even going to try to do that. Instead, I'm

going to make my win criteria the fact that I've memorized it." And they'll use wrote learning strategies. On one hand the good thing is that well you can achieve certain level of memory doing

that but it's often very timeconuming very tedious very boring and again it's actually not effective for achieving your goal if you need to use that information in a complex way. So when

you think about the process of learning there are lots of parts that can make learning really complicated. There are

lots of resources that you need to examine through and you need to filter through and screen and collect from.

That process can take sometimes hours, days, even weeks. AI is great at solving that problem. That's awesome. That is a

that problem. That's awesome. That is a genuine high yield time save that AI is providing that is valuable and effective for learning because you're not getting much learning benefit from just the act

of collecting resources, generating multimodal forms of learning, visuals and diagrams and audio and video. That

is something that AI is, as we can see, it's starting to be able to do that. And

again, for a relatively new product, it's doing it pretty well. Yes, it's not quite there yet, but I can see it getting there. And when it does get

getting there. And when it does get there, that's going to be a huge benefit for your learning because again, looking for videos, looking for images that are that are personalized to what you need

to know. That's not providing benefit.

to know. That's not providing benefit.

But the hard part is when you have all of that information and now it's entering into your brain and you have to do something with that information. You

have to take this information and you have to organize it in a way that makes sense for you. And the key issue that people don't understand often is that it is the process of trying to organize it

that creates the learning. It is not the end product that matters. Trying to see how it connects together and challenging your brain to think through these different pathways causes those pathways

to be reinforced which translates into understanding and mastery. And so you can take a mind map or a video that was created by the world's leading expert on this topic and they could say this is

the way that it makes sense for me and they could give you their mind map and you can receive that mind map and it will do no benefit for you because you didn't do any of the thinking involved in generating that mind map. And

likewise you can have two people learning the exact same topic and they could organize the information differently and it could both be accurate. It just makes sense for each

accurate. It just makes sense for each person slightly differently. A lot of the time if you were to look through some of the notes that I've written uh in the past for like different things that I've studied, you wouldn't really be able to make sense of it. But when I

look at it, it makes sense for me because when I look at it, it reminds me of the process that I used to come to those conclusions. I remember drawing

those conclusions. I remember drawing the line from here to here, moving this point from here to over here, regrouping and recategorizing the information in this way because I felt it made more

sense than the first way that I grouped it. I remember all those decisions and

it. I remember all those decisions and those challenges that I mentally overcame which leads to the learning.

And the issue is that what the AI tool sort of promises in a way is that you can click a button and it will just do that for you. It

generates the outcome for you. And when

you have the outcome just given to you without the process, it's just adding something else to be overwhelmed by. And

now, not only do you not see how it all connects together, you also are trying to fit your understanding around this mind map that it's given you because that's the way you're meant to

understand it. And that's the part that

understand it. And that's the part that I mean by I think it's actually making it worse. When I was going through this

it worse. When I was going through this material, especially when I was approaching it as if I was a beginner, I was deliberately trying to hold back on some of the the learning strategies that I would normally use to work through

that overwhelm. And I was letting the AI

that overwhelm. And I was letting the AI guide me in my thinking. And I felt the experience to be incredibly inefficient and very confusing. Actually, much more

confusing than if I was just reading it like in a book. And the reason is that I was holding off from engaging in a more organic process of trying to organize and make sense and connect the

information together. Instead of having

information together. Instead of having the sea of overwhelm and just diving into it and just trying to swim through and make sense of it, I was holding off on that and I was trying to find an

easier way. I was trying to find a

easier way. I was trying to find a shortcut. So, I was using their audio

shortcut. So, I was using their audio overview and their video overview and their mind map that they generated and I was trying to make myself fit this knowledge into the frames that they had given me and it wasn't clicking. And

when I compare that to the advanced test that I did with knowledge that I'm really familiar with, it makes sense why it wasn't clicking because the way that it is categorized, I just I don't think is inherently that meaningful. But when

I was a beginner going through AI fundamentals, I didn't realize that it wasn't meaningful. When I looked at it,

wasn't meaningful. When I looked at it, it seemed logical. It seemed like it should make sense. And so after spending, I don't know, maybe 30 or 40 minutes just trying to understand the information in the frame and the context

it's trying to give me, I just gave up because I didn't feel that my overwhelm was improving at all. And I felt myself leaning into the tendency of just trying to memorize this instead because I

wasn't making any progress. And that's

interesting because normally I would have spent that 30 to 40 minutes just diving into the overwhelm and making sense of it. And I probably wouldn't have been able to get through everything

in 30 minutes, but I would have had 30 minutes more of organizing and trying to make sense of it and like actually useful, meaningful learning as opposed to what ended up happening, which is 30

minutes of trying to make it fit and just realizing I don't think this is working. And so right now, if I think

working. And so right now, if I think about my position about where AI tools are headed and how useful I think it's going to be for learning, I'm kind of on the fence. I really want AI to be

the fence. I really want AI to be effective for learning. I want it to be the big enabler that allows people that, you know, struggle with their critical thinking and higher order of thinking and have typically not been great

learners to be able to be great learners because I do this for a living. I teach

people those skills and I see that moment when it suddenly clicks and they're able to think and operate at a level that they previously weren't able to operate at. And you can see it just changes the way that they think about

their opportunities in life and what they're capable of. like these are real, you know, tangible benefits that I that I see in in people and I think that's an amazing transformation and that's the reason why I left my job as a medical

doctor to do that because I found a lot of fulfillment in creating that kind of transformation and if AI can do that at scale that's a that's a huge deal. But

as I experience more and more and as I have conversations with dozens of the students and the professionals that I'm working with trying to use AI while also learning the techniques that I teach them, what I'm seeing more and more the

trend of is that while it is saving time in some parts, it seems to be distracting in other ways. It is

promising a shortcut to mastery that it can't deliver on. And a lot of beginners don't realize that it's not delivering on that because they're not measuring the effectiveness of the tool they're using based on this criteria. They're

measuring the effectiveness of it based on how long does it take for me to get through this content. They're measuring

it on how many hours am I saving without taking into consideration the outcome they get to at the end of those hours.

Like if you need to go from level one to level 10 and it normally would take you 50 hours to do that, but with using AI now, you can do, you know, level one to level three in just 2 hours. Well, the

first option is actually still more efficient. It's still better to spend 50

efficient. It's still better to spend 50 hours going from level one to level 10 if that's where you need to get to because that's the only path that actually gets you to the level you need to go. It doesn't matter how fast you're

to go. It doesn't matter how fast you're going if you're not getting to where you need to go. So overall, I'm gonna rate

the effectiveness of Notebook LM a pretty solid meh. I think if you're trying to reach a lowish level of understanding, then I think that's fine.

If you if you're trying to reach a relatively low level of understanding, then the effectiveness is going to be good. And most of that is because if you

good. And most of that is because if you were normally trying to do that, most of the time that you're wasting is in collecting those resources and bringing it together and maybe finding the right video. And because that time is

video. And because that time is genuinely really saved by AI, uh that's going to be really effective for that.

But in mastery level expert learning where most of the time is not in the collecting the resources and most of the time is just trying to make sense of overwhelming information, I don't think this is really moving the needle by

much. And there is a real risk that it

much. And there is a real risk that it will make things harder and worse uh while giving you the illusion that you are learning for a lot of people

especially if you do not have training and learning skills. However, there is one important caveat to this which is that the effectiveness

scales with your skill. I think if you are a skilled learner, you can use Notebook LM to learn effectively. It's going to be

no worse than whatever other method that you're normally using. You should be able to improve your current efficiency by using it as long as you're aware of the traps and you're able to navigate

through that and use your own learning skills to interface with it. And

likewise, if you are not very skilled with learning and you don't have a lot of those skills and those habits and that knowledge about how learning works, then when you use it, you're most likely

going to depend on the tool a lot more to guide you. So even though you're more likely to fall into those traps that I mentioned, you're probably not going to do any worse than whatever you're already doing because in your normal

learning, you're probably falling into different traps anyway. And so even though I think using this as an alternative to getting better at learning is a big no, that's not going to be effective and it's not going to be

a winning game for you, if you just compare yourself not using Notebook LM to using Notebook LM, I think you're more likely to get an advantage just by using it. And if you're using it and

using it. And if you're using it and also actively trying to improve your learning skills, I think you're going to get an even bigger improvement. Now,

FYI, if you are thinking about how do you actually go about improving your learning skills so that you're not just becoming dependent on AI and falling into all these different traps that I've been talking about, then one of the best

places that I'd recommend that you start is my free weekly newsletter. If you

felt that some of the things that I've talked about today have been insightful, maybe you haven't thought about learning in this way, I got a lot of these insights and I put them into this newsletter. I typed them myself uh

newsletter. I typed them myself uh because I tried getting them to be typed with chatbt and honestly I spent a lot of time trying to get my newsletters to be AI generated but I could never get it to a point where I was actually happy

with it. So unfortunately I spent my own

with it. So unfortunately I spent my own time writing every single one of those newsletters, every single word. And I

try to teach you the most important things for you to be able to learn new skills and knowledge much more quickly.

So if you're interested in signing up to that, it is totally free. You can

unsubscribe at any time. I'll leave a link to that in the description below.

Now, really quickly, uh let's go through the use cases. Uh how good is it for an intensive study session versus on the-go learning versus task reactive learning?

Uh I actually think that for all categories at all levels, it's basically equally as good. You can use this tool for when you're sitting down long hours.

You can use this tool when it's already preloaded with things on the go. uh if

you're starting a new notebook and you're having to import new resources and kind of configure things for the first time, you're not really, I think, going to be able to do that in just like 5 or 10 minutes. But if you already have

an existing notebook you've been learning from and then you're trying to reference that during the day, I think it's a really quick and effective way to do that. the mobile app or the mobile

do that. the mobile app or the mobile responsive version of the website works great and especially that audio overview podcast feature especially when it gets better. Uh I think it's going to be a

better. Uh I think it's going to be a game changanger for task reactive learning where you have to have a certain body of information that you're just trying to problem solve through.

I'm imagining like a developer learning a new library of new documentation to go through. Get all that documentation

through. Get all that documentation loaded up into sources here and then just use that to you know guide you on your on your task completion. I think

that's going to be a really effective tool that you can use. And so

considering all of these things, using notebook LM versus chatbt or Chachibd study mode, Notebook LM, clear clear winner at the current state, I see

absolutely no reason why you would ever use Chachib study mode compared to notebook LM. And so if you're interested

notebook LM. And so if you're interested in using Notebook LM, here are a couple of final tips that I would give for you to make sure you get the most out of it.

The first thing, and this is not super obvious if you're just kind of using the interface and just getting into it, is if you are using Notebook LM to learn

information like you you actually need to learn the stuff and you're not doing it just purely for task reactive uh you know just like asking questions and getting answers straight away. Go into

the settings of the chat and tick the option for learning guide. By default,

it is not turned on. What taking it into learning guide will do is whenever you have a conversation with it, instead of it just dumping the answer for you, it will ask you questions and force you to

generate some responses. And here's a really I think this is an interesting thing that I think you guys should all be really wary of when you're using AI tools. It's not enabled by default. But

tools. It's not enabled by default. But

here's the thing. I promise you when you enable learning guide your actual learning your ability to achieve the outcomes that you wanted is going to be

higher. So why if it produces a better

higher. So why if it produces a better result would it be turned off by default? That's because using this needs

default? That's because using this needs to feel good for you the consumer. This

is a product. So if you use it and you feel like it doesn't feel good, you're not going to use it anymore. and the

product is not going to be a success.

And when it comes to learning, this becomes a really problematic point because research on learning, especially around the idea of desirable difficulty or the misinterpreted effort hypothesis,

shows that learners often feel that something is not effective if it feels harder. Whereas the truth is effective

harder. Whereas the truth is effective learning is effortful. It involves you having to think about it. And what

happens when you turn learning guide on is that you have to engage with the chat. You actually have to think about

chat. You actually have to think about what you're learning. It will ask you, hey, what's your current understanding?

It'll ask you a series of questions to test you instead of just giving you the answer. For a lot of people, because

answer. For a lot of people, because that involves more effort, they're going to say, I can't be bothered using this.

This is not good because I want the fastest, shortest solution possible. And

so that's probably the reason why by default it is turned off. So my

recommendation for you is turn it on and realize that when you need to spend more effort to answer questions and engage with it, that's improving your learning.

In learning science, this is promoting something called the generative effect or generation. My second tip is to earn

or generation. My second tip is to earn the response.

Pay for a response with a question or a curiosity or a gap in your knowledge that you've identified. a thing that you have realized you don't understand or it

doesn't make sense to you. Target that

and get the answer to that. Do not treat this like a lecture. Don't engage with it passively. Don't sit there, get it to

it passively. Don't sit there, get it to generate a summary, click a few buttons, read stuff, click the next button, read the next stuff, use the recommended question that it's it has at the bottom,

click that and just read what it is.

Don't be a passenger in your learning.

Being a passenger in your learning is a very fast way to get nowhere. Take

control. Use a summary. But then stop.

Pause. Don't look at the screen. Think

about it. Think about where your knowledge is. Think about what makes

knowledge is. Think about what makes sense for you, where your gaps are. Be

specific about it. Feel where you are less confident. And then turn that

less confident. And then turn that feeling into words. What do you feel less confident about? What about the knowledge and the information do you not see connecting? Turn that into a

see connecting? Turn that into a question and a prompt. Get the answer again. Pause. Think about it.

again. Pause. Think about it.

Consolidate. Spend more of your time thinking about the knowledge and building expertise and mastery and less time just consuming and being passive.

Again, involves more work, involves more thinking, but it's vastly more effective. And the final tip, don't

effective. And the final tip, don't expect AI to be your learning savior.

For now, in the foreseeable future, from my perspective, neither Google or Open AI or Microsoft or whatever other company is going to come down from the

sky and deliver unto you the AI tool that fixes all of your learning issues.

That wall where you feel like it's getting complicated and you're feeling overwhelmed, that is the wall of learning that you're looking at. And I

don't think AI is going to bore a tunnel through that wall for you anytime soon.

Your ability to learn effectively shouldn't depend on the AI tool that you're using. It's not about the tool.

you're using. It's not about the tool.

It's about you the learner and then how you interact with different tools. That

is where the bottleneck is going to be.

The more you can change, the better your outcomes are going to be. And the most ironic part about me telling you this conclusion is that when I actually

used the self-regulated learning and the impact of AI on learning as the topic for the advanced learner testing, this is actually the conclusion that it generated for me in the video overview.

An AI learning tool telling me that the issue is not with AI learning tools. as

I'm using an AI learning tool to learn about AI learning tools, I think is like a special kind of poetic irony. So, let

me know what you think about this below.

What's your experience been with Notebook LM? And are there any other AI

Notebook LM? And are there any other AI tools that you want me to review? If

you're looking to improve your learning skills and get a little bit deeper into this and improve yourself, the thing that makes the biggest difference, then you might want to check out this video here where I go through a bit of a

master class on everything that you need to know to get started in learning to learn. Hope this helped. Thank you so

learn. Hope this helped. Thank you so much for watching and I'll see you in the next