Full podcast episode: ua-cam.com/video/cdiD-9MMpb0/v-deo.html Lex Fridman podcast channel: ua-cam.com/users/lexfridman Guest bio: Andrej Karpathy is a legendary AI researcher, engineer, and educator. He's the former director of AI at Tesla, a founding member of OpenAI, and an educator at Stanford.
Einstein's quote, "if you can't explain it simply you don't know the subject well enough," is truly profound. I teach digital skills to youth in Africa. Every time I think I understand the material thoroughly enough, an apprentice asks me a question that demonstrates I don't.
This truly is a way to know if you have mastered a subject. I find that if I could explain it to someone non-technical in an analogy that they'll understand then I know that I understand it as well.
His intuition about "scar tissue" is eye opening. I've always been concerned about wasting time on the wrong things that it paralyzes me to take the initial step. But now I view it as a way to grow to know what is not a good way of doing things. 10,000 hours, here I come.
I believe spending 3 to 4 hours a day for a year should be enough to start with and after you get a job as a junior you will be able to put 9 to 10 hours at work which works towards your improvement. 10000 is a put off to many people but i still understand where he is coming from esp if you are undergrad, you have all the time in the world to study. But if you want to learn machine learning while you are working to pay rent and other financial commitments, that is next to impossible.
@@xWarEternalx that will take you 13 years my friend. By that time, the world will be moved on. The best think is to do 3 to 4 hours a day and after a year you get a job where you can do 9 hours a day using those skillsets. You won't miss anything as you will be in the game. 10000 is ridiculous
10000h is quite general number of course. But even he says it's the time needed to be an expert. But the reality is not every employee needs to be an expert. So no need be discouraged by 10k hours.
@@alphar85 10k is alright. And after 10k you become expert. You don't have to be expert to start doing the job. You become expert doing the job. While you're learning you're a student not an option xpert
I am not a teacher but I believe writing up is the equally helpful test to identify gaps of knowledge. I realise my mind is tricky that let me believe I know something to comfort myself. I realised whenever I want to test myself I need to try to write things up. Many times I actually couldn't finish my notes. Also, imagining I explain a topic to someone else, e.g. my father, is a test if I truly understand the concept.
You're not alone, I just realised that myself. I realised Writing with pen and paper helps me cover gaps. because apparently, I'll never write down something I don't understand. It's very helpful.
Same, sometimes I might feel like I don't know a subject really well or can't remember it but when I take the time to think about it with a pen and paper stuff, just start to pour in and dots connecting.
Hi, I extracted text via Whisper AI and GPT-4 summarised it: 1. Advice for beginners in machine learning: - Focus on putting in 10,000 hours of work - Form a daily habit of working on the subject - Compare your progress to yourself in the past, not others 2. Overcoming paralysis by choice: - Don't worry about making mistakes; they help you learn and grow - Focus on what you have accomplished and the work you have done 3. Teaching and its benefits: - Teaching can be frustrating, but it helps others learn - Preparing educational material is hard work (about 10 hours for 1 hour of content) - Teaching strengthens one's understanding and reveals gaps in knowledge 4. Code as the source of truth: - Building things and using actual code to teach concepts is more effective than using slides or mathematical symbols This structured summary highlights the main points discussed in the podcast, making it easy to understand the key takeaways.
It's great advice. It took me 5 years to become a competent design engineer. I thought I was competent before that but looking back I mostly wasted other people's time with my nonsense.
10,000 is required but not sufficient. Four additional factors: 1. A learnable skill in a valid environment. 2. Quality feedback. 3. Push your limits. 4. Repetition to create automatic behaviour / fast brain response.
I also heard somewhere that most people at the top of their field across all fields tend to dedicate 55-60 hrs each week towards their craft, either through direct work or supporting activities (e.g. a top footballer could spend so many hours in match time, so many hours training, so many hours in the gym, so many doing analysis of games, so many visualising and so on...). Do the math yourself but to reach 10,000 hrs even on 60 hrs a week (excluding PTO and bank holidays) you're looking at 3-4 years. And that's assuming your day job isn't filled with unrelated tasks. As Andrej says elsewhere in the interview it's also good to have some chunks of these hours together, like a few long-hour days with minimal interruptions, so you can really make some good progress in a particular area.
So is it possible to reach 10k hours for multiple fields? My son is 8 and has been playing soccer for 3 years, but of course who knows where that will go. But at least if you start young you can get in the 10k hours much more realistically. But as an adult I have too much life maintenance to do, I don't know if I can do 10k hours in anything even though I want to. The non-stop groceries, cooking, cleaning, laundry, etc is a lot once you have a kid.
@@nofurtherwest3474 Yes and I'd say it's best to build skills in multiple fields, it will exercise more of your mental and physical faculties, which in turn leads to better health, happiness, success and so on. Then over time you can lean more into what seems to suit you best. If you're struggling for time remember just spending 5 mins a day on something (e.g. learning a new language) will lead to results. If you're awake for 16 hours a day that's 192 chunks of 5 mins. You just have to be very organised, efficient and disciplined. Can even apply it to other tasks like responding to work emails or playing with children. Most things can be done in 5-10 mins, even including meals and breaks.
@@nofurtherwest3474 You don't need to get 10k at anything, you just need to be interest and keep your interest about something alive. That is how you become master at anything. You you teach your son about commitment and support him at what he do. Not build a path and walk him through it. Let him decide.
I would like to remind people that ml is not just coding. You have to learn mathematical concepts like statistics, probability, algebra, calculas. You don’t have to go deep but you would have to learn at least basics to be able to understand how things work under the hood and then you will have to learn libraries to be able to implement theoretical concepts. I think after a hard grind of 6-8months(4hrs a day) you will be able to get a job in the field but it won’t be easy. Good luck
Even being a data specialist for 10 years I was so confused by machine learning models to choose regression do I choose classification, etc. in reality that is taking up so much of my time
10,000 hours is the equivalent of working 8 hours per day for ~3.5 years. But given that no one is going to consistently work at any one thing for that long, we're probably looking at 6-8 years, on average, to become an expert.
only watching this made me realize we didnt take enough appreciation for Andrej 's work. All these good courses for free! I wish I also spend more time learning from him and start practicing.
In the last few years, I've realized that the path you pick doesn't matter. With consistent effort, patience, and time, you can do anything you set your mind to, so don't get hung up on the fork in the road!
I have a bunch of small niches where I’ve just become the #1 resource for that thing and built communities around that thing. I help people to an extreme and they seem to think I’m overly “nice”. In reality I’m just practising my learning techniques in a way that benefits both of us
I love that concept of 10k hours. It resonated with me because of some of the things I do in my own life and career, but it also made me realize I've been stuck on some other aspects of my life, for fear of not making "the best choice." Like choosing a programming language. The right choice is to dive in, learn and correct as you go but just work at it. Great stuff.
The consept of 10k Hours works for closed learning systems. When the output is close related to the input and the feedback it has no delay. Like learning golf. But usually the learning systems are open and needs more general knowledge about how the world works
@@nsyll yeah, it feels like computer science/programming is a "wicked" system (not neat). Forget where I read about these terms. CompSci features the WORST of math AND language. Or, it seems like that to me. Haha. Can't "memorize" anything really... has it's OWN logic. I am gonna try to "chunk" things into my long-term memory. Need to get to 10k hours!
10000 hours is a hell of a time so picking a random thing and grinding to that will certainly put you right up there whether you like it or not. But it's just better to invest time in something u r better at so it will be fun along the way. However u can pick any random stuff and get better at it it's very much possible regardless of what anyone says.
@@Mstorac1990 Yeah, it is a known idea from way back and it has been disputed, so that is why I made the comment. Just that he (an accomplished deep learning expert) is confirming the 10,000-hour concept. I should have worded it differently.
takeaways: Advice for Beginners in Machine Learning Focus on Quantity of Work Believer in the 10,000 hour concept Pick something you're interested in and put in 10,000 hours of work Form a daily habit to maximize likelihood of reaching 10,000 hours Avoid Comparison to Others Only compare yourself to yourself from some time ago Progress is motivating Don't Get Paralyzed by Choice Wasting time doing something wrong is not dead work Accumulate scar tissue and learn from it Focus on what you have done last week Why Teach? Love happy humans Not necessarily love teaching, but love the outcome of happy humans.
Even the person who first pushed the 10k hours thing (K Anders Ericsson) backed away from (and clarified what he meant, limitations of the studies, etc. What we DO know about repetition practice, “putting in the hours” is that the nature of the practice/activities plays the key role. It’s the cliche difference between someone who “practiced” for one year, then repeated 10x and someone who has 10 years of highly novel, diverse, challenging activities. The 10k hours idea led a lot of people to fragile knowledge. Like “deep and strong attractors” but not so much adaptability. There’s no way around needing lots of time and effort “practicing”, but I think of it like the way some AI algorithms are dramatically more efficient and robust, given the appropriate context. Most education is based on a linear process… a RL toward objectives. Given humans are complex dynamical systems, something more like a Novelty Search, Exploration, MAP-Elites (but for humans). In movement sport skill acquisition, there’s been a recent push toward NON-linear pedagogy. I first explored those ideas for teaching programming, but then left computer science to do horse rehab 😁.
The consept of 10k Hours works for closed learning systems. When the output is close related to the input and the feedback it has no delay. Like learning golf. But usually the learning systems are open and needs more general knowledge about how the world works
For me personally the actual 10,000 hours is not the important part as mileage may vary depending on people’s experiences. I think the much more important thing it enforces is to just start doing it. Yes you may fail as they say in the video but you gotta just do it essentially. This is kinda just a universal truth, if you wanna get good at math, just do math. Programming? Do programming. It really reinforces the need to just do something, anything, and learn; rather than spending 2 months trying to figure out the best way to learn something you could’ve learned in 2 weeks, something I’m very guilty of from time to time. If you think about it the education system with its deadlines and such is more of a tool to force you to just do something, but outside of that one of the most important disciplines is actually just starting and trying things.
This motivated me. Recently, I tried to make a personal project and it didn't work. When you said, it doesn't materialise a lot of times, I felt it. Thank you. It's true. Learning is an iterative process.
Me: I want to get started with machine learning. Do you have any advice? Andrej: Spend 10,000 hours to become an expert Me: Ok, but what about getting started Andrej: You'll need to spend 10,000 hours
I guess what he is saying is that it doesn't matter so much what you do, e.g study at uni, get an internship, do projects that you are passionate about - as long as you get in the hours. Whether it's correct, I don't know and probably depends on you and your past experience. His experience is somewhat biased by being around Tesla employees and MIT students...
He is right. Im 1.5 years in and spent the first 6 months "wasting my time" 2 hours a day. I didnt really waste my time and was learning, but what I mean is I should have learned other things first. You just have to have the mindset of putting in x amount of hours a day and the rest takes care of itself usually.
4:08 is what most young people have to understand. They watch a 5 minute youtube clip on how to do something and all they see is someone slamming together what they couldn't do in hours. They don't realize that to make the 5 minute clip the creator spent endless hours to research the topic, decide how to bring it forth as fast as possible and then edit the clip. They are watching someone succeed extremely fast because they didn't see them failing endless times. And that is what I think deters young people from just diving into it, they think that they too have to make hours of research in minutes.
its very true. jsut about anything you pick, programming langauges for example, its all about knowledge, skills, practice and experience. Hands down that always wins.
10k hours => 416.6667 days of 24/7 studying/working => 833 days of 12/7 studying/working => about 2.2 years of studying/working to become an expert, seems pretty realistic
10K hours are basically 5/6 years... if you consider 8h/day for 5 days/week for basically 9 months.... BUT you should always consider a stimulant environment --> it is a bit of a gross approximation if you think about it
10,000 hours is a good average bet, but we're not all equal in intelligence, memory etc. Some people will only need a few thousand hours, some will need more.
IMO it’s just a way to say that becoming an expert requires huge dedication and time. That being said, I’m not sure about it, what if after 10,000 hours I still suck? I mean for sure time is very important, but sometimes I feel that those gurus are suffering from the survivorship bias (because it worked so well for them): even putting an extremely long amount of time doesn’t guarantee any accomplishment , it may be just one of the important factors.
It is like if you spend 10k hours on a game, for this example I will chose CS:GO. If you would spend 10k on it, you would know everything about it but, yet, you still need to improve in some areas. Same goes to programming.
10,000 hours of effort by any means is , your level and problems analytics can be at Phd level, no joke, 6 hours of learning per day consistency for like 6 months almost 1100 hours of practice, and that would make you decent for you to apply machine learning jobs. As those company might just offer you a junior position with less than the amount of knowledge you needed in that position. But eventually, you will be promoted and those job tasks will be needed true machine learning skills.
I think people are misunderstanding the whole 10k hours things. 10k is just an arbitrary number, it could've been any number but it just so happens when you commit 10k hours or over a year of your life to something you'll become an expert. Of course assuming rate of progression is constant, which for most people it isn't. The point is put in the hours. I used to be in CS and the amount of people who haven't even started a project year 1 cause they cant choose a language or IDE or some other excuse was staggering. Don't over think it, just start and put in consistent time
"Work is not fun" "What matters is how much you do, not what you do" -> 10,000 hrs "You should check if you are better than you 1 year ago, not to others"
This advice puts in perspective people who think 4-8 hours a day is enough what takes you 5-7 years takes someone else 2 years and it’s great motivation or tells you you should try something else
I hate when people say, "If you follow this guide, you won't waste time and you will learn everything you need to know." I think Karpathy gets it: your scar tissue builds when you waste time. You won't waste time in the future if you are self directed. Moreover, the goal of machine learning is to avoid the red hearings.
10000 hours of training is what is needed to train our brain neural network to get good at machine learning. That's a lot. But, with daily training, we can get there.
For those butt hurt about the advice he’s just saying you need to put in the work. Start some where, make mistakes, learn from them and become smarter. Eventually you will be immersed in the subject you were previously curious about and before you know it you will be an expert
1 hour a day = 365 hrs 3 hours a day = 1000 hrs 6 hours a day = 2000 hrs (5years) Learning is a slope. and if you get a full-time work position, in half a decade you will be an expert, at the top of your class.
You should totally invite Daniel Schiffman, who is the founder of the Coding Train, on your podcast. IMHO, he is the best UA-cam educator on the platform.
It's also a fact that you cannot learn everything about a thing in an evening it would take time (10,000 hours, building habits). Understanding that would go a long way.
I don’t think Andrej meant literally 10K hrs but more of getting into the grit of things and iterate with that heavy dose of being passionate about doing it. It it works out, great, you are rewarded and find satisfaction but if not, move on with the knowledge that what is wrong must not be repeated.
Full podcast episode: ua-cam.com/video/cdiD-9MMpb0/v-deo.html
Lex Fridman podcast channel: ua-cam.com/users/lexfridman
Guest bio: Andrej Karpathy is a legendary AI researcher, engineer, and educator. He's the former director of AI at Tesla, a founding member of OpenAI, and an educator at Stanford.
the code is the truth and the 10000 hours is key and is real .. PHP WIKI
Could you playlist each group of clips? Would make it easy to watch through when you don’t have time for the whole podcast. Ty
Thanks Lex! I really like Andrej!
It is good to hear even for someone like him it takes 10 hours to create 1 hour of content.
wow thanks lol
ᱚᱥᱛ
10K hours
@ 2 years = 13.70 hrs/day
@ 3 years = 9.13 hrs/day
@ 4 years = 6.85 hrs/day
@ 5 years = 5.48 hrs/day
@ 6 years = 4.57 hrs/day
Add holidays and sick dayz
Thanks for this.
Exactly what I was calculating haha
@@AsifSaifuddinAuvipy 10years. This is the reality of this advice. Malcolm Gladwell said that first time.
How many hours have you spent on learning when you graduated with PhD ?
His description of learning machine learning is much like machine learning
Neural nets, Neural haha
yeah, it is always trial and error and iteration for the win
yeah total bs.
I gotta put those epochs
10000 epochs
Einstein's quote, "if you can't explain it simply you don't know the subject well enough," is truly profound. I teach digital skills to youth in Africa. Every time I think I understand the material thoroughly enough, an apprentice asks me a question that demonstrates I don't.
This truly is a way to know if you have mastered a subject. I find that if I could explain it to someone non-technical in an analogy that they'll understand then I know that I understand it as well.
🎉
🎉
Props to you for doing what you do. Keep at it.
If you cant explain the subject to a 6 year old clearly, the teacher needs more understanding first.
His intuition about "scar tissue" is eye opening. I've always been concerned about wasting time on the wrong things that it paralyzes me to take the initial step. But now I view it as a way to grow to know what is not a good way of doing things.
10,000 hours, here I come.
Did you start yet?
@@psibarpsi yes I did
@@noobmaster31 Cool! 😍
@@psibarpsi he started on the hub, well past 10,000 now.
Nothing new, Yoda told same to Luke :)
I believe spending 3 to 4 hours a day for a year should be enough to start with and after you get a job as a junior you will be able to put 9 to 10 hours at work which works towards your improvement. 10000 is a put off to many people but i still understand where he is coming from esp if you are undergrad, you have all the time in the world to study. But if you want to learn machine learning while you are working to pay rent and other financial commitments, that is next to impossible.
Save a little money, move to India and study for 2 years. You could survive on less than $15k
@@xWarEternalx nahhhhhh lol
@@xWarEternalx that will take you 13 years my friend. By that time, the world will be moved on. The best think is to do 3 to 4 hours a day and after a year you get a job where you can do 9 hours a day using those skillsets. You won't miss anything as you will be in the game. 10000 is ridiculous
10000h is quite general number of course. But even he says it's the time needed to be an expert. But the reality is not every employee needs to be an expert. So no need be discouraged by 10k hours.
@@alphar85 10k is alright. And after 10k you become expert. You don't have to be expert to start doing the job. You become expert doing the job. While you're learning you're a student not an option xpert
I knew Andrej Karpathy was a genius. I had no idea he is such a kind, joyful person!
10000
@@ElGreco365 what he said was grammatically correct and does not imply he isn’t
I am not a teacher but I believe writing up is the equally helpful test to identify gaps of knowledge. I realise my mind is tricky that let me believe I know something to comfort myself. I realised whenever I want to test myself I need to try to write things up. Many times I actually couldn't finish my notes. Also, imagining I explain a topic to someone else, e.g. my father, is a test if I truly understand the concept.
You're not alone, I just realised that myself. I realised Writing with pen and paper helps me cover gaps. because apparently, I'll never write down something I don't understand. It's very helpful.
Same, sometimes I might feel like I don't know a subject really well or can't remember it but when I take the time to think about it with a pen and paper stuff, just start to pour in and dots connecting.
Don't be discouraged by the 5-year full-time number. The 80/20 rule holds here too: one year to get adequate, and then keep learning.
I find it incredible how humble he is.
Hi, I extracted text via Whisper AI and GPT-4 summarised it:
1. Advice for beginners in machine learning:
- Focus on putting in 10,000 hours of work
- Form a daily habit of working on the subject
- Compare your progress to yourself in the past, not others
2. Overcoming paralysis by choice:
- Don't worry about making mistakes; they help you learn and grow
- Focus on what you have accomplished and the work you have done
3. Teaching and its benefits:
- Teaching can be frustrating, but it helps others learn
- Preparing educational material is hard work (about 10 hours for 1 hour of content)
- Teaching strengthens one's understanding and reveals gaps in knowledge
4. Code as the source of truth:
- Building things and using actual code to teach concepts is more effective than using slides or mathematical symbols
This structured summary highlights the main points discussed in the podcast, making it easy to understand the key takeaways.
10k hrs is just 4-year degree and then some. He only means: "Make it your career"
UA-cam have an api to get the subtitles for free, no need to spend with whisper
Thank you sir!
what i personally find hard, is the amount of information to grasp and not actually forget them in the process of mastering and combining everything.
I think it is ok to forget. You will be able to quickly pick it up next time you need it.
@@arnobchowdhury9641 ^
Repetition
Advice for beginners: put in 10,000 hours….what brilliant advice champ
🤣
It's great advice. It took me 5 years to become a competent design engineer. I thought I was competent before that but looking back I mostly wasted other people's time with my nonsense.
@@NormEllison Mt. Stupid is real 🤪
2 hours a day for 13 years
😂😂😂
10,000 is required but not sufficient. Four additional factors: 1. A learnable skill in a valid environment. 2. Quality feedback. 3. Push your limits. 4. Repetition to create automatic behaviour / fast brain response.
1 and 2 are given for free when you code, 3 and 4 are on the individual
@@vishaljain4915 I'm sure you'll agree 2 requires more than "it compiles" or even "it passed this unit test" 😜
@@vishaljain4915 not true, 2 requires a lot more
And a domain that lends itself to all of the above.
Veritasium ha?
I also heard somewhere that most people at the top of their field across all fields tend to dedicate 55-60 hrs each week towards their craft, either through direct work or supporting activities (e.g. a top footballer could spend so many hours in match time, so many hours training, so many hours in the gym, so many doing analysis of games, so many visualising and so on...). Do the math yourself but to reach 10,000 hrs even on 60 hrs a week (excluding PTO and bank holidays) you're looking at 3-4 years. And that's assuming your day job isn't filled with unrelated tasks. As Andrej says elsewhere in the interview it's also good to have some chunks of these hours together, like a few long-hour days with minimal interruptions, so you can really make some good progress in a particular area.
So is it possible to reach 10k hours for multiple fields?
My son is 8 and has been playing soccer for 3 years, but of course who knows where that will go. But at least if you start young you can get in the 10k hours much more realistically.
But as an adult I have too much life maintenance to do, I don't know if I can do 10k hours in anything even though I want to. The non-stop groceries, cooking, cleaning, laundry, etc is a lot once you have a kid.
@@nofurtherwest3474 Yes and I'd say it's best to build skills in multiple fields, it will exercise more of your mental and physical faculties, which in turn leads to better health, happiness, success and so on. Then over time you can lean more into what seems to suit you best.
If you're struggling for time remember just spending 5 mins a day on something (e.g. learning a new language) will lead to results. If you're awake for 16 hours a day that's 192 chunks of 5 mins. You just have to be very organised, efficient and disciplined. Can even apply it to other tasks like responding to work emails or playing with children. Most things can be done in 5-10 mins, even including meals and breaks.
@@nofurtherwest3474 You don't need to get 10k at anything, you just need to be interest and keep your interest about something alive. That is how you become master at anything.
You you teach your son about commitment and support him at what he do. Not build a path and walk him through it.
Let him decide.
@@gonkong5638 Thanks
@@jd-ev1bw Thanks
10 hours to create 1 hour contents.... thanks for your patience and hard work. Really appreciate it!
I would like to remind people that ml is not just coding. You have to learn mathematical concepts like statistics, probability, algebra, calculas. You don’t have to go deep but you would have to learn at least basics to be able to understand how things work under the hood and then you will have to learn libraries to be able to implement theoretical concepts. I think after a hard grind of 6-8months(4hrs a day) you will be able to get a job in the field but it won’t be easy. Good luck
This single paragraph of a UA-cam comment was literally better than five minutes of non answers from an "expert"
Even being a data specialist for 10 years I was so confused by machine learning models to choose regression do I choose classification, etc. in reality that is taking up so much of my time
For anyone wondering how to put 10k hours and not feel it you need to love that thing you want to do.
How to love something if there is not yet a 'reward'?
You are working towards an idea that you may or may not play out
@@digitalsamurai42 Who said that there is no reward?
@@digitalsamurai42 That is the first issue. You will just waste your life if you are doing it just for the reward.
@@digitalsamurai42 You love the journey, learning concepts and acomplishing small steps, not the end goal because it will never be a tangible end goal
@@digitalsamurai42 you scatter intermittent sparse rewards, treat yourself like a reinforcement learning agent lol
I'm maximizing. 20hrs/day. See ya bois in 500 days! YA YEET
Get some sleep mate. Greedy algorithms are usually not the most efficient.
I would like this comment but it has 100 likes already, I feel like if I like it to 101 it feels wrong ya know.
This is the way. I do 12-14 hour days when learning something new. Can overtake the average practitioner in a field pretty quickly that way.
get on my level and practice 40 hours a day bro
You are gonna sleep? hahaha
10,000 hours is the equivalent of working 8 hours per day for ~3.5 years. But given that no one is going to consistently work at any one thing for that long, we're probably looking at 6-8 years, on average, to become an expert.
I’m an expert in coding 😎👍
Yep but you don't necessarily need to become an expert though. I bet 5000 hours and even less will get you far
only watching this made me realize we didnt take enough appreciation for Andrej 's work. All these good courses for free! I wish I also spend more time learning from him and start practicing.
Outliers by Malcom Gladwell and Mastery by Robert Greene offer great insight for anyone on their journey towards mastery
Gladwell is a hack.
Nice..
In the last few years, I've realized that the path you pick doesn't matter. With consistent effort, patience, and time, you can do anything you set your mind to, so don't get hung up on the fork in the road!
I have a bunch of small niches where I’ve just become the #1 resource for that thing and built communities around that thing. I help people to an extreme and they seem to think I’m overly “nice”. In reality I’m just practising my learning techniques in a way that benefits both of us
I love that concept of 10k hours. It resonated with me because of some of the things I do in my own life and career, but it also made me realize I've been stuck on some other aspects of my life, for fear of not making "the best choice." Like choosing a programming language. The right choice is to dive in, learn and correct as you go but just work at it. Great stuff.
Yessir
The concept was most recently popularized in the Malcolm Gladwell best seller "Outliers".
The consept of 10k Hours works for closed learning systems. When the output is close related to the input and the feedback it has no delay. Like learning golf. But usually the learning systems are open and needs more general knowledge about how the world works
@@nsyll yeah, it feels like computer science/programming is a "wicked" system (not neat). Forget where I read about these terms. CompSci features the WORST of math AND language. Or, it seems like that to me. Haha. Can't "memorize" anything really... has it's OWN logic. I am gonna try to "chunk" things into my long-term memory. Need to get to 10k hours!
He is really outstanding at teaching, and you know that he puts a lot of effort and thought to produce it the way he does.
After a couple years, I learned to just stick with one model in this case gradient boost because it does both classification and regression
10000 hours is a hell of a time so picking a random thing and grinding to that will certainly put you right up there whether you like it or not.
But it's just better to invest time in something u r better at so it will be fun along the way.
However u can pick any random stuff and get better at it it's very much possible regardless of what anyone says.
U are right
I couldn't agree more about : Teaching is the best way to understand 👍
I love that this 10,000 hour guidance is coming from Andrej Karpathy, a very accomplished machine learning expert.
I’m not sure that he did come up with it because the first time I read about was in the book outliers.
@@Mstorac1990 Yeah, it is a known idea from way back and it has been disputed, so that is why I made the comment. Just that he (an accomplished deep learning expert) is confirming the 10,000-hour concept. I should have worded it differently.
takeaways:
Advice for Beginners in Machine Learning
Focus on Quantity of Work
Believer in the 10,000 hour concept
Pick something you're interested in and put in 10,000 hours of work
Form a daily habit to maximize likelihood of reaching 10,000 hours
Avoid Comparison to Others
Only compare yourself to yourself from some time ago
Progress is motivating
Don't Get Paralyzed by Choice
Wasting time doing something wrong is not dead work
Accumulate scar tissue and learn from it
Focus on what you have done last week
Why Teach?
Love happy humans
Not necessarily love teaching, but love the outcome of happy humans.
This guy Andrej Karpathy is awesome!
He said 'just do it'
Even the person who first pushed the 10k hours thing (K Anders Ericsson) backed away from (and clarified what he meant, limitations of the studies, etc. What we DO know about repetition practice, “putting in the hours” is that the nature of the practice/activities plays the key role. It’s the cliche difference between someone who “practiced” for one year, then repeated 10x and someone who has 10 years of highly novel, diverse, challenging activities.
The 10k hours idea led a lot of people to fragile knowledge. Like “deep and strong attractors” but not so much adaptability.
There’s no way around needing lots of time and effort “practicing”, but I think of it like the way some AI algorithms are dramatically more efficient and robust, given the appropriate context. Most education is based on a linear process… a RL toward objectives.
Given humans are complex dynamical systems, something more like a Novelty Search, Exploration, MAP-Elites (but for humans).
In movement sport skill acquisition, there’s been a recent push toward NON-linear pedagogy.
I first explored those ideas for teaching programming, but then left computer science to do horse rehab 😁.
Don't be left out involve yourself with BTC and other crypto investments follow up a manager on Instagram 👇🏽
Jesse00134
He will reply to you
The 10,000 experiment rule (James Altucher) is a much better rule. Don't nitpick at the exact number, that can vary.
@@ks-dd7gv you should consider speaking with him on instagram
The consept of 10k Hours works for closed learning systems. When the output is close related to the input and the feedback it has no delay. Like learning golf. But usually the learning systems are open and needs more general knowledge about how the world works
For me personally the actual 10,000 hours is not the important part as mileage may vary depending on people’s experiences. I think the much more important thing it enforces is to just start doing it. Yes you may fail as they say in the video but you gotta just do it essentially. This is kinda just a universal truth, if you wanna get good at math, just do math. Programming? Do programming. It really reinforces the need to just do something, anything, and learn; rather than spending 2 months trying to figure out the best way to learn something you could’ve learned in 2 weeks, something I’m very guilty of from time to time. If you think about it the education system with its deadlines and such is more of a tool to force you to just do something, but outside of that one of the most important disciplines is actually just starting and trying things.
I went from being a design graduate to an AI engineer, all thanks to UA-cam. No tech degree, just dedication and hard work.
This motivated me. Recently, I tried to make a personal project and it didn't work. When you said, it doesn't materialise a lot of times, I felt it. Thank you. It's true. Learning is an iterative process.
Me: I want to get started with machine learning. Do you have any advice?
Andrej: Spend 10,000 hours to become an expert
Me: Ok, but what about getting started
Andrej: You'll need to spend 10,000 hours
Propably i have engineering degree in 75
I guess what he is saying is that it doesn't matter so much what you do, e.g study at uni, get an internship, do projects that you are passionate about - as long as you get in the hours.
Whether it's correct, I don't know and probably depends on you and your past experience. His experience is somewhat biased by being around Tesla employees and MIT students...
He is right. Im 1.5 years in and spent the first 6 months "wasting my time" 2 hours a day. I didnt really waste my time and was learning, but what I mean is I should have learned other things first. You just have to have the mindset of putting in x amount of hours a day and the rest takes care of itself usually.
Thank you Andrej and Thank you Lex, you both are good humans!
4:08 is what most young people have to understand. They watch a 5 minute youtube clip on how to do something and all they see is someone slamming together what they couldn't do in hours. They don't realize that to make the 5 minute clip the creator spent endless hours to research the topic, decide how to bring it forth as fast as possible and then edit the clip. They are watching someone succeed extremely fast because they didn't see them failing endless times. And that is what I think deters young people from just diving into it, they think that they too have to make hours of research in minutes.
3:17 - it is really nice to help and teach people, I love it too
This is my favorite part of the whole interview.
He is talking about a way to learn anything. Im here for machine learning
All he is saying is totally accurate (from my POV, after decades being a Professor).
Superb! You are doing some excellent work, you interview man
Thanks for this advice I'm starting learning machine learning for my project and my brain starts hurting me when I learn the concepts.
How has the journey been ?
bro quit@@s.cupidAI
its very true. jsut about anything you pick, programming langauges for example, its all about knowledge, skills, practice and experience. Hands down that always wins.
10k hours => 416.6667 days of 24/7 studying/working => 833 days of 12/7 studying/working => about 2.2 years of studying/working to become an expert, seems pretty realistic
Working 84 hours a week doesn’t sound super realistic to me. Maybe 60 if you’re dedicated!
10K hours are basically 5/6 years... if you consider 8h/day for 5 days/week for basically 9 months.... BUT you should always consider a stimulant environment --> it is a bit of a gross approximation if you think about it
The learning never stops:)
This really helped give me perspective on my own progress and inspire me to keep going thanks 🙏
I have to say ... Lex does good interviews.
Agree that Andrej is the best ML teacher out there
Teaching is Learning.
By far the best advice!
Thanks for choosing the hard... we really get authentic and real knowledge of data science
Wow this helps me 🙂 Lex always brings the best of the best
Learning by teaching is the Feynman method
Interest keeps on pursuing goals
When lex says my mind and throat get tensed.
Most of the time you don't know that you know what you think you know until you are told to explain it to somebody else. And that is "Teaching"
Have quarterly look back... to keep tab on progress and focus on goal, often times it diverges in 3-months
This was an eye opening clip for learning machine learning.
This point was well articulated by Martin Gladwell's Outliers book.
Malcolm. Great read
10,000 hours is a good average bet, but we're not all equal in intelligence, memory etc. Some people will only need a few thousand hours, some will need more.
That's about 3.5 years of 8 hours everyday. It sounds about right on average.
@@ricosrealm people don't work on weekends
Also remember that you will be proficient well before 10000 hours. The pain and suffering declines drastically/exponetially
@@ziggs123 Yeah they do. Me being an example
@@georgeosborn421 average is 5 days a week is what I mean
Thank you Lex for introducing me to Andrej!
Explain a complex concept simply and a simple concept complexly.
IMO it’s just a way to say that becoming an expert requires huge dedication and time. That being said, I’m not sure about it, what if after 10,000 hours I still suck? I mean for sure time is very important, but sometimes I feel that those gurus are suffering from the survivorship bias (because it worked so well for them): even putting an extremely long amount of time doesn’t guarantee any accomplishment , it may be just one of the important factors.
It's best to spend 2 hours persuading someone else to do it
lmfaoo
This tip is his teacher told him. Feifei li is such an hard working person that her student is also that kind of people
really can't wait for Andrej to come back on the podcast and talk about open ai and if he's found something that's interests him
It is like if you spend 10k hours on a game, for this example I will chose CS:GO. If you would spend 10k on it, you would know everything about it but, yet, you still need to improve in some areas. Same goes to programming.
10,000 hours of effort by any means is , your level and problems analytics can be at Phd level, no joke,
6 hours of learning per day consistency for like 6 months almost 1100 hours of practice, and that would make you decent for you to apply machine learning jobs. As those company might just offer you a junior position with less than the amount of knowledge you needed in that position. But eventually, you will be promoted and those job tasks will be needed true machine learning skills.
X10 would bring you to around 10.000 hours.
I think people are misunderstanding the whole 10k hours things. 10k is just an arbitrary number, it could've been any number but it just so happens when you commit 10k hours or over a year of your life to something you'll become an expert. Of course assuming rate of progression is constant, which for most people it isn't. The point is put in the hours. I used to be in CS and the amount of people who haven't even started a project year 1 cause they cant choose a language or IDE or some other excuse was staggering. Don't over think it, just start and put in consistent time
"Work is not fun"
"What matters is how much you do, not what you do" -> 10,000 hrs
"You should check if you are better than you 1 year ago, not to others"
Preparation to teach is the best way to learn.
I will great if we get more prodcast like this
Lol love how he said maximizing our likelihood
true. start is the most important thing.
Advice to beginning Guitar: Put in 10,000 hours
Advice to beginning Machine Learning: Put the Guitar down
This advice puts in perspective people who think 4-8 hours a day is enough what takes you 5-7 years takes someone else 2 years and it’s great motivation or tells you you should try something else
I hate when people say, "If you follow this guide, you won't waste time and you will learn everything you need to know." I think Karpathy gets it: your scar tissue builds when you waste time. You won't waste time in the future if you are self directed. Moreover, the goal of machine learning is to avoid the red hearings.
Thanks malcom gladwell for the advice
his vids are honestly the best
10000 hours of training is what is needed to train our brain neural network to get good at machine learning. That's a lot. But, with daily training, we can get there.
For those butt hurt about the advice he’s just saying you need to put in the work. Start some where, make mistakes, learn from them and become smarter. Eventually you will be immersed in the subject you were previously curious about and before you know it you will be an expert
1 hour a day = 365 hrs
3 hours a day = 1000 hrs
6 hours a day = 2000 hrs (5years)
Learning is a slope. and if you get a full-time work position, in half a decade you will be an expert, at the top of your class.
Truly Amazing 😃
10000hrs = Drill, drill, drill and repeat. ❤
i am ok at teaching, what an understatement
I needed to hear this. Thank you!
what machine learning engineers do:
1. Download paper
2. Implement it
3. Keep doing until have a skill
You should totally invite Daniel Schiffman, who is the founder of the Coding Train, on your podcast. IMHO, he is the best UA-cam educator on the platform.
Ok..
Happy humans! What a noble soul. Thanks Lex
It's also a fact that you cannot learn everything about a thing in an evening it would take time (10,000 hours, building habits). Understanding that would go a long way.
10,000 hrs is about 5 years of focus, based on 8 to 9 hour work days
Learning is about seeing meaning when you see yellow lines on the snow you know it’s the marks of urine
And you've pissed yourself again
I don’t think Andrej meant literally 10K hrs but more of getting into the grit of things and iterate with that heavy dose of being passionate about doing it. It it works out, great, you are rewarded and find satisfaction but if not, move on with the knowledge that what is wrong must not be repeated.
Thanks for the insight.
It’s really helpful.