How I Use Obsidian Zettelkasten to Study AI & Tech Topics

the number one comment I get on my note the number one comment I get on my note taking videos is comments asking me to taking videos is comments asking me to taking videos is comments asking me to show how I actually do this how do I show how I actually do this how do I show how I actually do this how do I create settle cast notes how do I create settle cast notes how do I create settle cast notes how do I Implement them into my system so in this Implement them into my system so in this Implement them into my system so in this video I'm going to take a practical video I'm going to take a practical video I'm going to take a practical example I'm currently studying example I'm currently studying example I'm currently studying artificial intelligence and I'm reading artificial intelligence and I'm reading artificial intelligence and I'm reading this book and I am going to be this book and I am going to be this book and I am going to be processing my notes that I took while processing my notes that I took while processing my notes that I took while reading this book so I'm going to take reading this book so I'm going to take reading this book so I'm going to take my time for this I'm going to show you my time for this I'm going to show you my time for this I'm going to show you exactly how I do it and how slowly I how exactly how I do it and how slowly I how exactly how I do it and how slowly I how slowly I do it so this is your chance to slowly I do it so this is your chance to slowly I do it so this is your chance to get a sneak peek behind the scenes of get a sneak peek behind the scenes of get a sneak peek behind the scenes of what actually goes on in Misha's tcas what actually goes on in Misha's tcas what actually goes on in Misha's tcas and system which now contains 4,000 and system which now contains 4,000 and system which now contains 4,000 notes so let's get into it as you see I notes so let's get into it as you see I notes so let's get into it as you see I have the physical copy here that's how I have the physical copy here that's how I have the physical copy here that's how I read it but I have also uh purchased a read it but I have also uh purchased a read it but I have also uh purchased a pdf version of this so I have this is pdf version of this so I have this is pdf version of this so I have this is all legal I have the the I have done my all legal I have the the I have done my all legal I have the the I have done my purchases so I can show you a little bit purchases so I can show you a little bit purchases so I can show you a little bit from the the contents as I'm going along from the the contents as I'm going along from the the contents as I'm going along because it's really important that I because it's really important that I because it's really important that I drive home some of the key concepts of drive home some of the key concepts of drive home some of the key concepts of artificial intelligence of tcas I mean artificial intelligence of tcas I mean artificial intelligence of tcas I mean um and as I'm learning about artificial um and as I'm learning about artificial um and as I'm learning about artificial intelligence so I've been reading this intelligence so I've been reading this intelligence so I've been reading this book and I took took notes first in this book and I took took notes first in this book and I took took notes first in this little notebook and then later in a little notebook and then later in a little notebook and then later in a another notebook now another notebook now another notebook now normally I would process these on the normally I would process these on the normally I would process these on the same day or the next day however my life same day or the next day however my life same day or the next day however my life has been extremely hectic these past has been extremely hectic these past has been extremely hectic these past couple of weeks and I just had a a

couple of weeks and I just had a a couple of weeks and I just had a a little bit of time in the evening to little bit of time in the evening to little bit of time in the evening to actually do the reading so I prioritized actually do the reading so I prioritized actually do the reading so I prioritized just reading and then taking the notes just reading and then taking the notes just reading and then taking the notes um so I'm I'm kind kind of working um so I'm I'm kind kind of working um so I'm I'm kind kind of working through the backlog of notes ideally through the backlog of notes ideally through the backlog of notes ideally this is done on the same day so I'm not this is done on the same day so I'm not this is done on the same day so I'm not sure how fresh everything is still in my sure how fresh everything is still in my sure how fresh everything is still in my mind as I go through this but uh here we mind as I go through this but uh here we mind as I go through this but uh here we go so here are the scribbles that I took go so here are the scribbles that I took go so here are the scribbles that I took for this and I'm just going to start for this and I'm just going to start for this and I'm just going to start with uh with the first with uh with the first with uh with the first scribbles and it says here Ray Curts scribbles and it says here Ray Curts scribbles and it says here Ray Curts while definition of Singularity when AI while definition of Singularity when AI while definition of Singularity when AI reaches and exceeds human intelligence reaches and exceeds human intelligence reaches and exceeds human intelligence powered by powered by powered by self-learning by learning autonomously self-learning by learning autonomously self-learning by learning autonomously and and and self-improving so that's the first self-improving so that's the first self-improving so that's the first that's the first thought that I'm that's the first thought that I'm that's the first thought that I'm capturing the first thing that I'm capturing the first thing that I'm capturing the first thing that I'm capturing because all everything in this capturing because all everything in this capturing because all everything in this um settle casting system is about um settle casting system is about um settle casting system is about modularity modular nodes so I can either modularity modular nodes so I can either modularity modular nodes so I can either use my obsidian or my command line well use my obsidian or my command line well use my obsidian or my command line well to get started a bit easier I will just to get started a bit easier I will just to get started a bit easier I will just start with obsidian so I'm going to start with obsidian so I'm going to start with obsidian so I'm going to create a new node and that is going to create a new node and that is going to create a new node and that is going to be this note is actually about Ray be this note is actually about Ray be this note is actually about Ray cordts while definition of Singularity cordts while definition of Singularity cordts while definition of Singularity so I will do ray cords so I will do ray cords so I will do ray cords Wilds definition of singularity that is the the name of the note and I

that is the the name of the note and I should probably also just should probably also just should probably also just enable uh show me the key so you can see enable uh show me the key so you can see enable uh show me the key so you can see which keys I'm pressing as I'm which keys I'm pressing as I'm which keys I'm pressing as I'm navigating navigating navigating this here we go so now you should be this here we go so now you should be this here we go so now you should be able to see what I'm doing and the apple able to see what I'm doing and the apple able to see what I'm doing and the apple key here is the super key so Ray CW's key here is the super key so Ray CW's key here is the super key so Ray CW's definition of Singularity and I've definition of Singularity and I've definition of Singularity and I've already made a already made a already made a mistake I see okay so here we go Ray mistake I see okay so here we go Ray mistake I see okay so here we go Ray csw's definition of Singularity when Singularity when AI AI AI reaches and exceeds so this is the notes that I wrote down so this is the notes that I wrote down in my notebook when AI reaches and in my notebook when AI reaches and in my notebook when AI reaches and exceeds human intelligence powered by exceeds human intelligence powered by exceeds human intelligence powered by learning autonomously and learning autonomously and learning autonomously and self-improving now I always write down self-improving now I always write down self-improving now I always write down my notes in my own words it's always my my notes in my own words it's always my my notes in my own words it's always my own words but it doesn't mean that it own words but it doesn't mean that it own words but it doesn't mean that it doesn't contain any similar words so if doesn't contain any similar words so if doesn't contain any similar words so if I just go to my the book here and I've I just go to my the book here and I've I just go to my the book here and I've just search for Ray or for just kurts just search for Ray or for just kurts just search for Ray or for just kurts while here so this is the original quote

while here so this is the original quote while here so this is the original quote this is the original uh quote this is the original uh quote this is the original uh quote here Ray kurtwell and his vision of the here Ray kurtwell and his vision of the here Ray kurtwell and his vision of the singularity in which a AI empowered by singularity in which a AI empowered by singularity in which a AI empowered by its ability to improve itself and learn its ability to improve itself and learn its ability to improve itself and learn on its own will quickly reach and then on its own will quickly reach and then on its own will quickly reach and then exceed human level intelligence so let exceed human level intelligence so let exceed human level intelligence so let me me me just um cop that so above here is my own just um cop that so above here is my own just um cop that so above here is my own note and down here is the original text note and down here is the original text note and down here is the original text so you can see here that I instead of so you can see here that I instead of so you can see here that I instead of saying like one change I did is that saying like one change I did is that saying like one change I did is that here in the end it says then exceed here in the end it says then exceed here in the end it says then exceed human level intelligence well I brought human level intelligence well I brought human level intelligence well I brought that to the front when AI reaches and that to the front when AI reaches and that to the front when AI reaches and exceeds human intelligence powered by exceeds human intelligence powered by exceeds human intelligence powered by learning learning learning autonomously and here it says empowered autonomously and here it says empowered autonomously and here it says empowered by its ability to to improve itself and by its ability to to improve itself and by its ability to to improve itself and learn on its own and I turn that into learn on its own and I turn that into learn on its own and I turn that into learning autonomously and learning autonomously and learning autonomously and self-improving so I am like I'm keep I'm self-improving so I am like I'm keep I'm self-improving so I am like I'm keep I'm keeping the same meaning but I put it keeping the same meaning but I put it keeping the same meaning but I put it into my own words and this process of into my own words and this process of into my own words and this process of putting it into your own words really putting it into your own words really putting it into your own words really solidifies your thinking and this is the solidifies your thinking and this is the solidifies your thinking and this is the the key aspect of uh the ttle Casten the key aspect of uh the ttle Casten the key aspect of uh the ttle Casten method that you don't just take this and method that you don't just take this and method that you don't just take this and copy it into your system and Tada you're copy it into your system and Tada you're copy it into your system and Tada you're done that doesn't have any value at all done that doesn't have any value at all done that doesn't have any value at all like maybe you have a nice quote for

like maybe you have a nice quote for like maybe you have a nice quote for later but it doesn't have any value this later but it doesn't have any value this later but it doesn't have any value this has value because this is a note that I has value because this is a note that I has value because this is a note that I can use later in my own writing and I can use later in my own writing and I can use later in my own writing and I can just you I I can use this as my own can just you I I can use this as my own can just you I I can use this as my own writing I just need to stitch a few of writing I just need to stitch a few of writing I just need to stitch a few of these notes together and I have an essay these notes together and I have an essay these notes together and I have an essay so so so I might here also uh include a reference I might here also uh include a reference I might here also uh include a reference to the page number uh that I used so I to the page number uh that I used so I to the page number uh that I used so I will then include a reference that I will then include a reference that I will then include a reference that I took this from took this from took this from page XX in the prologue so just so that I know later if prologue so just so that I know later if I want to find rayer while definition of I want to find rayer while definition of I want to find rayer while definition of Singularity again I know where to look Singularity again I know where to look Singularity again I know where to look so that was my first note and so that was my first note and so that was my first note and this is all that I want to have in this this is all that I want to have in this this is all that I want to have in this in this note I just simply want to in this note I just simply want to in this note I just simply want to capture rord Well's definition of capture rord Well's definition of capture rord Well's definition of Singularity and for now I can I could Singularity and for now I can I could Singularity and for now I can I could just create a link to just create a link to just create a link to Singularity Singularity Singularity actually actually actually Singularity because I I know that I'm Singularity because I I know that I'm Singularity because I I know that I'm going to be linking to that in other going to be linking to that in other going to be linking to that in other notes as notes as notes as well so I created this link and now this well so I created this link and now this well so I created this link and now this node is done node is done node is done let's go to the next one one so as I was reading this I was actually so as I was reading this I was actually so as I was reading this I was actually very interested in definitions of AI

very interested in definitions of AI very interested in definitions of AI first of all like that's everything first of all like that's everything first of all like that's everything needs to start with the definitions in needs to start with the definitions in needs to start with the definitions in my opinion and I'm now studying AI my opinion and I'm now studying AI my opinion and I'm now studying AI because I want to I feel I've mastered because I want to I feel I've mastered because I want to I feel I've mastered kubernetes to a degree that I can learn kubernetes to a degree that I can learn kubernetes to a degree that I can learn what I need to learn I can use it for what I need to learn I can use it for what I need to learn I can use it for what I need to use it for I can work what I need to use it for I can work what I need to use it for I can work with it and now I want to deepen my with it and now I want to deepen my with it and now I want to deepen my knowledge on artificial knowledge on artificial knowledge on artificial intelligence and in order to do that I'm intelligence and in order to do that I'm intelligence and in order to do that I'm just starting with the basics with the just starting with the basics with the just starting with the basics with the definitions and then going from there definitions and then going from there definitions and then going from there so um I already have a note called so um I already have a note called so um I already have a note called artificial intelligence which I can artificial intelligence which I can artificial intelligence which I can open oh I have to artificial open oh I have to artificial open oh I have to artificial intelligence intelligence intelligence so let me just enable show me the key again go again go so this is my artificial intelligence so this is my artificial intelligence so this is my artificial intelligence note note note already and I think I will add a already and I think I will add a already and I think I will add a definition section on this note because definition section on this note because definition section on this note because I use index notes for all of my um all I use index notes for all of my um all I use index notes for all of my um all of my settle cast and work I might some of my settle cast and work I might some of my settle cast and work I might some people call these maps of content I like people call these maps of content I like people call these maps of content I like the the term index better so so actually the the term index better so so actually the the term index better so so actually I'm going to create a new heading here I'm going to create a new heading here I'm going to create a new heading here called called called definitions and I'm going to add um definitions and I'm going to add um definitions and I'm going to add um definition of artificial

definition of artificial definition of artificial intelligence and I'm also going to add intelligence and I'm also going to add intelligence and I'm also going to add the word AI just because it becomes more the word AI just because it becomes more the word AI just because it becomes more searchable now I am going to add this to searchable now I am going to add this to searchable now I am going to add this to my daily node as well as you see I am my daily node as well as you see I am my daily node as well as you see I am creating all of these nodes from my creating all of these nodes from my creating all of these nodes from my daily notes and I'll explain later why I daily notes and I'll explain later why I daily notes and I'll explain later why I do that so just bear with me I'm just do that so just bear with me I'm just do that so just bear with me I'm just going to process these notes first and going to process these notes first and going to process these notes first and then I'm going to show you how I am then I'm going to show you how I am then I'm going to show you how I am going to be structuring these notes and going to be structuring these notes and going to be structuring these notes and referring them to one referring them to one referring them to one another so the next note is as another so the next note is as another so the next note is as follows this is exactly what I wrote follows this is exactly what I wrote follows this is exactly what I wrote term AI invented by okay so this is the these are the notes okay so this is the these are the notes that I wrote in my little notebook

that I wrote in my little notebook that I wrote in my little notebook here and now I'm going to here and now I'm going to here and now I'm going to continue I'm going to just sit here and continue I'm going to just sit here and continue I'm going to just sit here and reflect on what I wrote there and how I reflect on what I wrote there and how I reflect on what I wrote there and how I do I want to pull this apart do I I do I want to pull this apart do I I do I want to pull this apart do I I think this is enough and again these are think this is enough and again these are think this is enough and again these are all in my own words except for this um all in my own words except for this um all in my own words except for this um this part this part this part here and because I I took this note here and because I I took this note here and because I I took this note these notes maybe a week or two ago it's these notes maybe a week or two ago it's these notes maybe a week or two ago it's not fresh in my mind anymore and this is not fresh in my mind anymore and this is not fresh in my mind anymore and this is why it's so important that you make it a why it's so important that you make it a why it's so important that you make it a habit to process these notes like on the habit to process these notes like on the habit to process these notes like on the same day or the day after because then same day or the day after because then same day or the day after because then you remember the context and I don't you remember the context and I don't you remember the context and I don't really remember the context anymore so really remember the context anymore so really remember the context anymore so I'm actually going to go and read about I'm actually going to go and read about I'm actually going to go and read about McCarthy McCarthy McCarthy again McCarthy so here here it speaks about McCarthy so here here it speaks about McCarthy and he was um he basically came McCarthy and he was um he basically came McCarthy and he was um he basically came up with the term uh artificial up with the term uh artificial up with the term uh artificial intelligence McCarthy later admitted intelligence McCarthy later admitted intelligence McCarthy later admitted that no one really liked the name after that no one really liked the name after that no one really liked the name after the goal was genuine not artificial the goal was genuine not artificial the goal was genuine not artificial intelligence but I had to call it intelligence but I had to call it intelligence but I had to call it something so I called it artificial something so I called it artificial something so I called it artificial intelligence so he's the one that came intelligence so he's the one that came intelligence so he's the one that came up with the up with the up with the term and here it says that term and here it says that term and here it says that um organize a two-month 10man study of um organize a two-month 10man study of um organize a two-month 10man study of artificial intelligence to be carried artificial intelligence to be carried artificial intelligence to be carried out during the summer of

out during the summer of out during the summer of 1956 the term artificial intelligence 1956 the term artificial intelligence 1956 the term artificial intelligence was McCarthy's invention so here it says was McCarthy's invention so here it says was McCarthy's invention so here it says literally that he came up with the term literally that he came up with the term literally that he came up with the term and that's why I noted it down like this and that's why I noted it down like this and that's why I noted it down like this so um that is basically the source of this um that is basically the source of this line here invented by McCarthy in line here invented by McCarthy in line here invented by McCarthy in 1956 he founded Stanford AI project in 1956 he founded Stanford AI project in 1956 he founded Stanford AI project in the early 60s that is that is later the early 60s that is that is later the early 60s that is that is later so here I might create a note about this so here I might create a note about this so here I might create a note about this MC McCarthy person but as I've continued MC McCarthy person but as I've continued MC McCarthy person but as I've continued in the book he is not really mentioned in the book he is not really mentioned in the book he is not really mentioned as much anymore I'm not necessarily as much anymore I'm not necessarily as much anymore I'm not necessarily interested in knowing more about him but interested in knowing more about him but interested in knowing more about him but I do have notes about people like Brian I do have notes about people like Brian I do have notes about people like Brian Johnson for Johnson for Johnson for example like I I would have a note about example like I I would have a note about example like I I would have a note about that person and then I would like um that person and then I would like um that person and then I would like um have notes about that person be linked have notes about that person be linked have notes about that person be linked from that note for example but this time from that note for example but this time from that note for example but this time I don't need to do that because McCarthy I don't need to do that because McCarthy I don't need to do that because McCarthy is not as interesting to me I just want is not as interesting to me I just want is not as interesting to me I just want to capture who invented the term so I'm to capture who invented the term so I'm to capture who invented the term so I'm happy with this I'm happy with this this I'm happy with this [Music] [Music] [Music] um this setup it's it's just a nice um this setup it's it's just a nice um this setup it's it's just a nice clean sentence that says where the

clean sentence that says where the clean sentence that says where the definition of AI comes from so next is definition of AI comes from so next is definition of AI comes from so next is the actual the actual the actual definition and here I have used quotes definition and here I have used quotes definition and here I have used quotes So that is interesting and now I'm going So that is interesting and now I'm going So that is interesting and now I'm going to be looking to be looking to be looking at how that's actually phrased in the in the in [Music] [Music] [Music] the document here we go a branch of computer document here we go a branch of computer science that studies the properties of science that studies the properties of science that studies the properties of intelligence by synthesizing intelligence so here it's it talks he intelligence so here it's it talks he the author talks about in a recent the author talks about in a recent the author talks about in a recent report on the current state of AI a report on the current state of AI a report on the current state of AI a committee of prominent researchers committee of prominent researchers committee of prominent researchers defined the field as a branch of defined the field as a branch of defined the field as a branch of computer science that studies properties computer science that studies properties computer science that studies properties of intelligence by synthesizing of intelligence by synthesizing of intelligence by synthesizing intelligence so this is the the intelligence so this is the the intelligence so this is the the definition that is being being used in definition that is being being used in definition that is being being used in the book itself so here it it speaks the book itself so here it it speaks the book itself so here it it speaks more about like it it it goes more into more about like it it it goes more into more about like it it it goes more into the the the details of it but this is the moment details of it but this is the moment details of it but this is the moment where the author takes a stance and where the author takes a stance and where the author takes a stance and gives a gives a gives a definition now this one you may notice I definition now this one you may notice I definition now this one you may notice I have not

have not have not um turned into my own words so in my um turned into my own words so in my um turned into my own words so in my settle cast course which you can get by settle cast course which you can get by settle cast course which you can get by joining my Cube pref Community the link joining my Cube pref Community the link joining my Cube pref Community the link will be down below it's a full course on will be down below it's a full course on will be down below it's a full course on how to create your ttle Casten in how to create your ttle Casten in how to create your ttle Casten in obsidian but in this course I put a lot obsidian but in this course I put a lot obsidian but in this course I put a lot of emphasis that Nicholas Lumen the of emphasis that Nicholas Lumen the of emphasis that Nicholas Lumen the inventor of the ttle cast method rarely inventor of the ttle cast method rarely inventor of the ttle cast method rarely used quotes you should use them very used quotes you should use them very used quotes you should use them very sparingly and I also use them very sparingly and I also use them very sparingly and I also use them very sparingly but very sparingly does not sparingly but very sparingly does not sparingly but very sparingly does not mean that you should never use them and mean that you should never use them and mean that you should never use them and in this case there is a committee that in this case there is a committee that in this case there is a committee that went out and came out with a definition went out and came out with a definition went out and came out with a definition and here I think it is and here I think it is and here I think it is actually actually actually uh a good decision to use the specific uh a good decision to use the specific uh a good decision to use the specific wording of that definition and I have I did change it a definition and I have I did change it a little bit I see I left out a little bit little bit I see I left out a little bit little bit I see I left out a little bit so actually now I just I now that I so actually now I just I now that I so actually now I just I now that I review it again I want to just just take review it again I want to just just take review it again I want to just just take the entire text I think I might have abbreviated text I think I might have abbreviated that because I didn't write it all that because I didn't write it all that because I didn't write it all didn't want to write it all out by okay and then the context is a committee

okay and then the context is a committee of prominent researchers defined the of prominent researchers defined the of prominent researchers defined the field in a recent report so let's check out in a recent report so let's check out what what what that that that uh report is about 100e study on uh report is about 100e study on uh report is about 100e study on artificial intelligence interesting so artificial intelligence interesting so artificial intelligence interesting so can we find that okay so this is the the report The okay so this is the the report The Source material and then I think I I Source material and then I think I I Source material and then I think I I kind of like to include this report here oh here oh oops I will just include this link into oops I will just include this link into oops I will just include this link into the the the note so so that is then the source note so so that is then the source note so so that is then the source material comes from 100e study on material comes from 100e study on material comes from 100e study on artificial artificial artificial intelligence intelligence intelligence so I will include that link in here here okay and I will copy the name of

it and then I will write the context it and then I will write the context myself I will say um the author takes a stance on the say um the author takes a stance on the definition of definition of definition of artificial intelligence in artificial intelligence in artificial intelligence in chapter what is the chapter definitions and getting on with chapter definitions and getting on with it the author takes a stance on the the author takes a stance on the definition of artificial intelligence in definition of artificial intelligence in definition of artificial intelligence in page six um using page six um using page six um using the what is what does you call it a study committee of prominent study committee of prominent researchers a recent report on the researchers a recent report on the researchers a recent report on the current state of current state of current state of AI using the

offers offers the offers offers the definition used in a report on the state definition used in a report on the state definition used in a report on the state of AI by of AI by of AI by Stanford 100e study on artificial Stanford 100e study on artificial Stanford 100e study on artificial intelligence a branch of computer intelligence a branch of computer intelligence a branch of computer science that studies the properties of science that studies the properties of science that studies the properties of intelligence by synthesizing intelligence by synthesizing intelligence by synthesizing intelligence okay so now I have kind of put this into okay so now I have kind of put this into my own words I'm I I'm now reflecting on my own words I'm I I'm now reflecting on my own words I'm I I'm now reflecting on the definition itself where it came from the definition itself where it came from the definition itself where it came from exactly how she phrased it and like exactly how she phrased it and like exactly how she phrased it and like we're probably already 10 minutes into we're probably already 10 minutes into we're probably already 10 minutes into the video and I'm only on my second note the video and I'm only on my second note the video and I'm only on my second note and I'm showing you and I'm showing you and I'm showing you this like laboriously I'm showing you this like laboriously I'm showing you this like laboriously I'm showing you exactly what I do I'm not doing this exactly what I do I'm not doing this exactly what I do I'm not doing this hastily to get views this view this hastily to get views this view this hastily to get views this view this video is probably going to get horrible video is probably going to get horrible video is probably going to get horrible watch time because I'm just so slow but watch time because I'm just so slow but watch time because I'm just so slow but the point of the settle cast method is the point of the settle cast method is the point of the settle cast method is to take it slow it won't work if you do to take it slow it won't work if you do to take it slow it won't work if you do it quickly what I'm showing you here is it quickly what I'm showing you here is it quickly what I'm showing you here is the actual thinking process that I go the actual thinking process that I go the actual thinking process that I go through it's the actual process that through it's the actual process that through it's the actual process that enables me to learn 10 times faster enables me to learn 10 times faster enables me to learn 10 times faster faster than my peers because I engage faster than my peers because I engage faster than my peers because I engage deeply with the material that most deeply with the material that most deeply with the material that most people just don't have the patience for people just don't have the patience for people just don't have the patience for and a settle cast method is a vehicle to and a settle cast method is a vehicle to and a settle cast method is a vehicle to enable

later so this I might expand with other later so this I might expand with other notes reflecting on this definition but notes reflecting on this definition but notes reflecting on this definition but I am currently happy with this I am currently happy with this I am currently happy with this definition like a branch of computer definition like a branch of computer definition like a branch of computer science that studies the properties of science that studies the properties of science that studies the properties of intelligence by synthesizing intelligence by synthesizing intelligence by synthesizing intelligence that is basically a very intelligence that is basically a very intelligence that is basically a very clear and concise definition of the term clear and concise definition of the term clear and concise definition of the term artificial artificial artificial intelligence but later I have written AI intelligence but later I have written AI intelligence but later I have written AI is a field with the goal of creating is a field with the goal of creating is a field with the goal of creating machines with machines with machines with intelligence and I wish I had noted intelligence and I wish I had noted intelligence and I wish I had noted where I got that from where I got that from where I got that from but this is just but this is just but this is just a this is just a note that I wrote a this is just a note that I wrote a this is just a note that I wrote myself these are my own words I didn't myself these are my own words I didn't myself these are my own words I didn't quote around it this is just my own quote around it this is just my own quote around it this is just my own words words words basically and maybe field of um let me see AI is a field with the um let me see AI is a field with the goal of creating machines with goal of creating machines with goal of creating machines with intelligence I'm just oh just oh here here is it here it

here here is it here it here here is it here it is an enchy of methods so this is a this is an enchy of methods so this is a this is an enchy of methods so this is a this actually came earlier let me see let's read through earlier let me see let's read through this in fact in much of the popular this in fact in much of the popular this in fact in much of the popular media the term artificial intelligence media the term artificial intelligence media the term artificial intelligence itself has come to mean deep learning itself has come to mean deep learning itself has come to mean deep learning this is an unfortunate inaccuracy and I this is an unfortunate inaccuracy and I this is an unfortunate inaccuracy and I need to clarify the need to clarify the need to clarify the distinction AI is a field that includes distinction AI is a field that includes distinction AI is a field that includes a broad set of approaches with the goal a broad set of approaches with the goal a broad set of approaches with the goal of creating machines with intelligence of creating machines with intelligence of creating machines with intelligence that is basic this is the broad that is basic this is the broad that is basic this is the broad definition of what we're doing deep definition of what we're doing deep definition of what we're doing deep learning is only one sub approach deep learning is only one sub approach deep learning is only one sub approach deep learning is itself one method among many learning is itself one method among many learning is itself one method among many in the field of machine learning a sub in the field of machine learning a sub in the field of machine learning a sub field of AI in which machines learn from field of AI in which machines learn from field of AI in which machines learn from data or from their own experiences okay so this this comes a experiences okay so this this comes a bit later actually this is then yes this bit later actually this is then yes this bit later actually this is then yes this is the definitions and getting on with is the definitions and getting on with is the definitions and getting on with it chap it chap it chap this is the next chapter so I actually like this uh this chapter so I actually like this uh this chapter a lot and it says AI it really pulls it a lot and it says AI it really pulls it a lot and it says AI it really pulls it apart it makes it very clear what AI is apart it makes it very clear what AI is apart it makes it very clear what AI is and what it's not so AI is a field let's and what it's not so AI is a field let's and what it's not so AI is a field let's let's break this let's break this let's break this down for the sake of clarity I will just down for the sake of clarity I will just down for the sake of clarity I will just um break this up I will copy this and

um break this up I will copy this and um break this up I will copy this and just break it up a bit so here this is just break it up a bit so here this is just break it up a bit so here this is what I wrote AI is a field with the goal what I wrote AI is a field with the goal what I wrote AI is a field with the goal of creating machines with intelligence so I did quote a bit of it intelligence so I did quote a bit of it I would say I I'm paraphrasing here I would say I I'm paraphrasing here I would say I I'm paraphrasing here because I'm leaving out a bit of the the because I'm leaving out a bit of the the because I'm leaving out a bit of the the quote so I did put this in my own words quote so I did put this in my own words quote so I did put this in my own words in that in that in that sense sense sense so um the goal of the AI field is to create the goal of the AI field is to create machines with intelligence then I will just in the intelligence then I will just in the following following following chapter the chapter the chapter the author makes some very author makes some very author makes some very important distinctions important distinctions important distinctions she she she highlights that in popular media the term AI has become media the term AI has become synonimous with deep unfortunate and this unfortunate and this is yeah here we go this is an is yeah here we go this is an is yeah here we go this is an unfortunate

unfortunate unfortunate accuracy in fact much of the popular accuracy in fact much of the popular accuracy in fact much of the popular media the term out of itself become to media the term out of itself become to media the term out of itself become to mean deep learning so you see how mean deep learning so you see how mean deep learning so you see how I'm I did this from memory I read just I'm I did this from memory I read just I'm I did this from memory I read just read this but I rewrote it in a slightly read this but I rewrote it in a slightly read this but I rewrote it in a slightly different way in the following chapter and I'll include the chapter chapter and I'll include the chapter name which is name which is name which is called an anarchy of methods the author makes some very important the author makes some very important distinctions she highlights that in distinctions she highlights that in distinctions she highlights that in popular media the term a has become popular media the term a has become popular media the term a has become synonymous with deep learning and here synonymous with deep learning and here synonymous with deep learning and here she she she says has come to mean deep learning so says has come to mean deep learning so says has come to mean deep learning so it is a different way of phrasing it but it is a different way of phrasing it but it is a different way of phrasing it but still means the same so this these are still means the same so this these are still means the same so this these are my own words I can just publish this as my own words I can just publish this as my own words I can just publish this as my own words and I won't be infringing my own words and I won't be infringing my own words and I won't be infringing on any on any on any copyright well well I'm also attributing copyright well well I'm also attributing copyright well well I'm also attributing the meaning to the author so it's a very the meaning to the author so it's a very the meaning to the author so it's a very careful balancing act that you need to careful balancing act that you need to careful balancing act that you need to do as a writer but this is what I also do as a writer but this is what I also do as a writer but this is what I also mean with writing as if ready for mean with writing as if ready for mean with writing as if ready for publication Nicholas Lumen did this so publication Nicholas Lumen did this so publication Nicholas Lumen did this so whenever you write notes in a ttle cast whenever you write notes in a ttle cast whenever you write notes in a ttle cast and like this you have to write as if and like this you have to write as if and like this you have to write as if it's going to be published and what I'm it's going to be published and what I'm it's going to be published and what I'm writing here is basically a a whole writing here is basically a a whole writing here is basically a a whole chapter of a blog post or an essay or chapter of a blog post or an essay or chapter of a blog post or an essay or whatever I could just use this as a full whatever I could just use this as a full whatever I could just use this as a full note or a full note or a full note or a full um

um um resource so again she aular become resource so again she aular become resource so again she aular become synonymous of deep learning this is unfortunate she goes on to explain that unfortunate she goes on to explain that the goal of the AI field is to create the goal of the AI field is to create the goal of the AI field is to create machines with intelligence deep intelligence deep learning is a learning is a learning is a what do you call what do you call what do you call it here she says is only one such it here she says is only one such it here she says is only one such approach it's one method among many in approach it's one method among many in approach it's one method among many in the field of machine the field of machine the field of machine learning deep learning is learning deep learning is learning deep learning is a a a method an deep learning is itself one method among deep learning is itself one method among many in the field of machine learning a many in the field of machine learning a many in the field of machine learning a subfield of AI deep learning is AI deep learning is actually actually actually a method which is part of machine

artificial not AI itself I like artificial not AI itself I like that and then later there is machine that and then later there is machine that and then later there is machine learning but that I also have learning but that I also have learning but that I also have a yeah another note that I wrote down a yeah another note that I wrote down a yeah another note that I wrote down here where it down okay so this is what I wrote down a down okay so this is what I wrote down a subfield of AI in which machines learn subfield of AI in which machines learn subfield of AI in which machines learn from data or from their own experiences mhm so that is then definitely going to mhm so that is then definitely going to be a new be a new be a new note about machine learning that's going note about machine learning that's going note about machine learning that's going to be a new index in my system I to be a new index in my system I to be a new index in my system I suppose because machine learning is not AI machine AI machine learning is a sub field of AI and I like the word AI and I like the word subfield but I will just call it a yeah okay I will just copy the word

a yeah okay I will just copy the word subfield in this case because it's well subfield in this case because it's well subfield in this case because it's well maybe thesaurus well this is maybe a time where I would well this is maybe a time where I would maybe uh ask Claude sometimes it's if I'm stuck then Claude sometimes it's if I'm stuck then I I I will help because um English is not my first language so I um English is not my first language so I like to use like to use like to use thesaurus but um sometimes I just use thesaurus but um sometimes I just use thesaurus but um sometimes I just use my my my um I use AI to find a u synonym for um I use AI to find a u synonym for um I use AI to find a u synonym for words so let's find another way of here a branch of a domain within AI here a branch of a domain within AI yeah a domain within AI I like that deep learning is itself one method that deep learning is itself one method among many in the field of using a among many in the field of using a among many in the field of using a branch of AI yeah a branch I like that branch of AI yeah a branch I like that branch of AI yeah a branch I like that one a branch so here I'm going to refine one a branch so here I'm going to refine one a branch so here I'm going to refine this into machine learning is a branch this into machine learning is a branch this into machine learning is a branch of

AI where machines learn from their own AI where machines learn from their own data or experiences so experiences so here a subfield of AI in which machines here a subfield of AI in which machines here a subfield of AI in which machines learn from data or their own learn from data or their own learn from data or their own experiences I have kind of put this in a experiences I have kind of put this in a experiences I have kind of put this in a different way I mean I know the concept different way I mean I know the concept different way I mean I know the concept now I know that its relation to AI but I now I know that its relation to AI but I now I know that its relation to AI but I have taken a different word and by doing have taken a different word and by doing have taken a different word and by doing this process I have molded over in my this process I have molded over in my this process I have molded over in my mind and therefore it is more lodged mind and therefore it is more lodged mind and therefore it is more lodged into my mind now and this why it's so into my mind now and this why it's so into my mind now and this why it's so important that I do take my time to important that I do take my time to important that I do take my time to really deeply reflect on this and spend really deeply reflect on this and spend really deeply reflect on this and spend some quality time while doing this which belongs to I belong to this which belongs to I belong to machine machine machine learning deep learning is a type of learning deep learning is a type of learning deep learning is a type of artificial intelligence not AI learning this can actually be a a learning this can actually be a a separate note so this is a definition of separate note so this is a definition of separate note so this is a definition of machine machine machine learning and that one I will actually learning and that one I will actually learning and that one I will actually add to the add to the add to the definitions one here

definitions one here definitions one here but as you see it Springs from this note but as you see it Springs from this note but as you see it Springs from this note where I'm defining Ai and in that way where I'm defining Ai and in that way where I'm defining Ai and in that way the fact that machine learning is a the fact that machine learning is a the fact that machine learning is a subfield of AI is now reflected in this explain yes explain yes so this note so this note so this note then talks about machine learning is a then talks about machine learning is a then talks about machine learning is a branch of AI where machines learn from branch of AI where machines learn from branch of AI where machines learn from their own data or experiences so I've now processed experiences so I've now processed another page in my little notebook and I didn't write any further notebook and I didn't write any further any much further on machine learning as any much further on machine learning as any much further on machine learning as I wrote these notes down but now I'm I wrote these notes down but now I'm I wrote these notes down but now I'm kind of interested in the fact kind of interested in the fact kind of interested in the fact where the author takes she she uses this where the author takes she she uses this where the author takes she she uses this um oh I should actually add um oh I should actually add um oh I should actually add this one again here so here here she she quotes this word

so here here she she quotes this word experiences and now I kind of want to experiences and now I kind of want to experiences and now I kind of want to know more about um these experiences and know more about um these experiences and know more about um these experiences and this I will actually just use Claude this I will actually just use Claude this I will actually just use Claude for in this sentence the for in this sentence the for in this sentence the author um has has put experiences in quotes I'm trying I'm learning I'm quotes I'm trying I'm learning I'm studying AI from the ground up and I'd studying AI from the ground up and I'd studying AI from the ground up and I'd like to know more about what you like to know more about what you like to know more about what you think author implied think author implied think author implied by putting this in quotes I quotes I realize machines can't realize machines can't realize machines can't actually experience anything but could actually experience anything but could actually experience anything but could you explain it to says you've touch on a fascinating and says you've touch on a fascinating and philosophically Rich question the use of philosophically Rich question the use of philosophically Rich question the use of quotation marks about learn experience quotation marks about learn experience quotation marks about learn experience signals that their analogies or signals that their analogies or signals that their analogies or proximations when we say machines learn proximations when we say machines learn proximations when we say machines learn it's fundamentally different from Human it's fundamentally different from Human it's fundamentally different from Human learning learning learning learning yeah what's really happening is learning yeah what's really happening is learning yeah what's really happening is statistical pattern recognition yeah statistical pattern recognition yeah statistical pattern recognition yeah exactly yeah she goes into that later in exactly yeah she goes into that later in exactly yeah she goes into that later in in the in the in the book optimization of numer yeah so it's

book optimization of numer yeah so it's book optimization of numer yeah so it's not actually learning in the sense of not actually learning in the sense of not actually learning in the sense of how a human learns similarly a machine experiences learns similarly a machine experiences aren't experiences in any conscious or aren't experiences in any conscious or aren't experiences in any conscious or phenomenological sense they're really phenomenological sense they're really phenomenological sense they're really just input data points training examples just input data points training examples just input data points training examples and recorded interactions or and recorded interactions or and recorded interactions or outcomes now I love how how Claude is explaining now I love how how Claude is explaining this the quotation marks serve as a kind this the quotation marks serve as a kind this the quotation marks serve as a kind of epistemological humility of epistemological humility of epistemological humility acknowledging that we're borrowing terms acknowledging that we're borrowing terms acknowledging that we're borrowing terms from Human cognition and Consciousness from Human cognition and Consciousness from Human cognition and Consciousness to describe what what are essentially to describe what what are essentially to describe what what are essentially mathematical and computational processes mathematical and computational processes mathematical and computational processes oh this is so good I wish I wrote that oh this is so good I wish I wrote that oh this is so good I wish I wrote that myself myself myself it's similar how to how we might say a it's similar how to how we might say a it's similar how to how we might say a thermostat knows when to turn on the thermostat knows when to turn on the thermostat knows when to turn on the heat it's a useful metaphor but no one heat it's a useful metaphor but no one heat it's a useful metaphor but no one would argue that the thermostat has would argue that the thermostat has would argue that the thermostat has actual knowledge in the way humans actual knowledge in the way humans actual knowledge in the way humans do this distinction becomes particularly do this distinction becomes particularly do this distinction becomes particularly important in AI ethics and philosophy of important in AI ethics and philosophy of important in AI ethics and philosophy of Mind discussions wow this is so good thank discussions wow this is so good thank you so much you so much you so much Claude while AI systems can process Claude while AI systems can process Claude while AI systems can process information and adjust their behavior information and adjust their behavior information and adjust their behavior Behavior Based on data there is still an Behavior Based on data there is still an Behavior Based on data there is still an open question about whether they can open question about whether they can open question about whether they can have genuine experiences or have genuine experiences or have genuine experiences or Consciousness in the way biological Consciousness in the way biological Consciousness in the way biological entities entities entities do okay so this is really useful and do okay so this is really useful and do okay so this is really useful and this is also I'm showing you this

this is also I'm showing you this this is also I'm showing you this because I often use Claude in this way because I often use Claude in this way because I often use Claude in this way as a kind of Mentor or teacher and I use as a kind of Mentor or teacher and I use as a kind of Mentor or teacher and I use AI to it's fascinating that I'm now AI to it's fascinating that I'm now AI to it's fascinating that I'm now using AI to learn about AI that in using AI to learn about AI that in using AI to learn about AI that in itself is hugely fascinating itself is hugely fascinating itself is hugely fascinating but I really like the way Claude put but I really like the way Claude put but I really like the way Claude put this and I'm this and I'm this and I'm actually like I'm not a fan of actually like I'm not a fan of actually like I'm not a fan of copying um AI or copying text straight copying um AI or copying text straight copying um AI or copying text straight from Ai and this is definitely not going from Ai and this is definitely not going from Ai and this is definitely not going to be published but this is just so good to be published but this is just so good to be published but this is just so good that I'm not going to let this go to waste so in the waste so in the book The author put learn and book The author put learn and book The author put learn and experiences in quotation experiences in quotation experiences in quotation marks marks marks signaling that we do signaling that we do signaling that we do not signaling that machines do not not signaling that machines do not not signaling that machines do not actually learn or actually learn or actually learn or experience however for the sake for for the sake of sake for for the sake of communication we must use the these communication we must use the these communication we must use the these words to words to words to indicate that machine learning can indicate that machine learning can indicate that machine learning can enable machines to perform enable machines to perform enable machines to perform tasks better and better over

time we use the word the the human term time we use the word the the human term learning for this learning for this learning for this but in reality what's happening is that but in reality what's happening is that but in reality what's happening is that the model is gaining more the model is gaining more the model is gaining more accurate accurate accurate statistical data so this is basically my own data so this is basically my own phrasing of this so yes I am I'm reusing phrasing of this so yes I am I'm reusing phrasing of this so yes I am I'm reusing the AI text here and the AI text here and the AI text here and then then then CLA when I ask CLA thought about this it CLA when I ask CLA thought about this it CLA when I ask CLA thought about this it generated this fascinating piece of text text so usually I won't like have my notes so usually I won't like have my notes so usually I won't like have my notes this large but in this case this is just this large but in this case this is just this large but in this case this is just something that I I stumble upon and I something that I I stumble upon and I something that I I stumble upon and I really like how Claude explained this really like how Claude explained this really like how Claude explained this but I'm just going to indicate that this but I'm just going to indicate that this but I'm just going to indicate that this was gener ated by Claude and then I can was gener ated by Claude and then I can was gener ated by Claude and then I can use this note later for further use this note later for further use this note later for further reflection if I want to go deeper into reflection if I want to go deeper into reflection if I want to go deeper into how machines learn or how machines learn or how machines learn or experience but I've I've realized the experience but I've I've realized the experience but I've I've realized the point I like it it it drove the point point I like it it it drove the point point I like it it it drove the point home to me that machines don't actually home to me that machines don't actually home to me that machines don't actually learn it's just statistical pattern learn it's just statistical pattern learn it's just statistical pattern recognition and for the the stage of my recognition and for the the stage of my recognition and for the the stage of my research that I'm in currently that is

research that I'm in currently that is research that I'm in currently that is all I need to know I don't necessarily all I need to know I don't necessarily all I need to know I don't necessarily want to go deep into how machines want to go deep into how machines want to go deep into how machines actually learn and how these models actually learn and how these models actually learn and how these models actually work although I did take more actually work although I did take more actually work although I did take more notes on that which I'm going to be notes on that which I'm going to be notes on that which I'm going to be doing in the next section but this um doing in the next section but this um doing in the next section but this um this is how deep I want to go and then I this is how deep I want to go and then I this is how deep I want to go and then I use this as data for later reference and use this as data for later reference and use this as data for later reference and I can also include the claw link here so I can also include the claw link here so I can also include the claw link here so I can just find that later and then um I can just find that later and then um I can just find that later and then um now I'm I'm finished with this this note okay so now that I note okay so now that I have a few notes created now now I can have a few notes created now now I can have a few notes created now now I can show you how I will actually structure show you how I will actually structure show you how I will actually structure this um because I've now been adding this um because I've now been adding this um because I've now been adding these both to these both to these both to my daily note and this artificial my daily note and this artificial my daily note and this artificial intelligence note but what I also like intelligence note but what I also like intelligence note but what I also like to do is to do is to do is to create input nodes so what I do is I to create input nodes so what I do is I to create input nodes so what I do is I create a note that represents this create a note that represents this create a note that represents this book and let me see artificial humans so this this is the note that

humans so this this is the note that represents the book and I'm moving this represents the book and I'm moving this represents the book and I'm moving this to input to input to input books I have every book I read that I books I have every book I read that I books I have every book I read that I take notes on it has its own entry in my in my on it has its own entry in my in my system and then from this note I'm going system and then from this note I'm going system and then from this note I'm going to be adding um adding um these as well so these as well so these as well so and let's turn that into a bulleted list and let's turn that into a bulleted list and let's turn that into a bulleted list because I like the look of that here we because I like the look of that here we because I like the look of that here we go so what this go so what this go so what this achieves and I I I show you all of this achieves and I I I show you all of this achieves and I I I show you all of this because I want to show you why I do this because I want to show you why I do this because I want to show you why I do this so what this achieves by adding it from so what this achieves by adding it from so what this achieves by adding it from the daily note the artificial the daily note the artificial the daily note the artificial intelligence note and having my um book intelligence note and having my um book intelligence note and having my um book note where these notes originate from is note where these notes originate from is note where these notes originate from is that I can for example go to the that I can for example go to the that I can for example go to the definition of artificial intelligence definition of artificial intelligence definition of artificial intelligence Noe and when I then go to the back Links Noe and when I then go to the back Links Noe and when I then go to the back Links of this note I see where it comes from of this note I see where it comes from of this note I see where it comes from so if I do the what is it local graph so if I do the what is it local graph so if I do the what is it local graph open local graph here so open local graph here so open local graph here so here I see that this note is linked to here I see that this note is linked to here I see that this note is linked to several notes Here I can see that it was several notes Here I can see that it was several notes Here I can see that it was created on this date because that's created on this date because that's created on this date because that's where it spawned from so if I click

where it spawned from so if I click where it spawned from so if I click there then I can also see what I was up there then I can also see what I was up there then I can also see what I was up to on that day and I see that I have to on that day and I see that I have to on that day and I see that I have created different AI related notes on created different AI related notes on created different AI related notes on that day that is interesting that day that is interesting that day that is interesting already then I see that it is part of an already then I see that it is part of an already then I see that it is part of an index node called artificial index node called artificial index node called artificial intelligence and Ai and this one has a intelligence and Ai and this one has a intelligence and Ai and this one has a lot of different notes lot of different notes lot of different notes already and going back to definition of already and going back to definition of already and going back to definition of intelligence I also see that this note intelligence I also see that this note intelligence I also see that this note actually spawned a different note here actually spawned a different note here actually spawned a different note here we go and this is why I like to do it we go and this is why I like to do it we go and this is why I like to do it this way and maybe I can even this way and maybe I can even this way and maybe I can even excal excalibrate do I have that open excal excalibrate do I have that open excal excalibrate do I have that open yeah here we yeah here we yeah here we go this is another way why another go this is another way why another go this is another way why another reason why I like to do it when I use reason why I like to do it when I use reason why I like to do it when I use excal brain this be with this one it excal brain this be with this one it excal brain this be with this one it becomes even clearer so here I have my becomes even clearer so here I have my becomes even clearer so here I have my artificial intelligence note but this is artificial intelligence note but this is artificial intelligence note but this is myart Definition of artificial myart Definition of artificial myart Definition of artificial intelligence and here it becomes even intelligence and here it becomes even intelligence and here it becomes even clearer that this note its parent notes clearer that this note its parent notes clearer that this note its parent notes are um The Daily note are um The Daily note are um The Daily note here and the book note I can see that here and the book note I can see that here and the book note I can see that this note comes from there and then this this note comes from there and then this this note comes from there and then this note led to this note machine learning note led to this note machine learning note led to this note machine learning is a branch of is a branch of is a branch of AI and now I can see that this AI and now I can see that this AI and now I can see that this note its parents are also here it's on

note its parents are also here it's on note its parents are also here it's on the this daily note is in the the this daily note is in the the this daily note is in the book and it book and it book and it is um related to these other notes now when um related to these other notes now when I take this book note here I see that it I take this book note here I see that it I take this book note here I see that it originated from this date so this is originated from this date so this is originated from this date so this is when I started writing about it that can when I started writing about it that can when I started writing about it that can be an interesting point of data to have be an interesting point of data to have be an interesting point of data to have but because the way excal brain renders but because the way excal brain renders but because the way excal brain renders it I see that this note relates led to it I see that this note relates led to it I see that this note relates led to the following notes down here and I can the following notes down here and I can the following notes down here and I can see its see its see its interrelations so if I were to link Ray interrelations so if I were to link Ray interrelations so if I were to link Ray cords cords cords whil uh definition of Singularity to the whil uh definition of Singularity to the whil uh definition of Singularity to the machine learning note for example then I should be able to see example then I should be able to see that uh here yeah here we see that this this uh here yeah here we see that this this link is now um it is now connected to link is now um it is now connected to link is now um it is now connected to this note which wasn't there before I this note which wasn't there before I this note which wasn't there before I don't actually want to connect it to it don't actually want to connect it to it don't actually want to connect it to it but it's just an example and for me I but it's just an example and for me I but it's just an example and for me I like to use these visual explorations of like to use these visual explorations of like to use these visual explorations of my tcast and to when I go deeper into my tcast and to when I go deeper into my tcast and to when I go deeper into this and I want to see visually which this and I want to see visually which this and I want to see visually which notes are related to what and I can ex notes are related to what and I can ex notes are related to what and I can ex expand the the number of branches and expand the the number of branches and expand the the number of branches and such like it is super

such like it is super such like it is super useful useful useful so these are the first not few notes so these are the first not few notes so these are the first not few notes that I've created on this topic now in that I've created on this topic now in that I've created on this topic now in the next section I'm going to be using the next section I'm going to be using the next section I'm going to be using my neovim workflow and showing you how I my neovim workflow and showing you how I my neovim workflow and showing you how I use that as