how is it possible that i’ve watched a ton of videos trying to understand LLMs from the likes of universities and big tech companies yet this simple video in comic sans explains everything in the most direct and concise manner possible !?
I've been watching a lot of videos on LLMs and the underlying mathematics. This explanation is PHENOMENAL. Not dumbed down, not too long, and uses concepts of existing maths and graphing that cement the concept perfectly.
I have been working on ways to explain LLMs to people in the humanities for the past year. You've done it in 5 brilliant minutes. From now on, I'm just going to hand out this URL.
I loved this. Clarity = real understanding= respect for the curiosity and intelligence of the audience. Requests: Would like more depth about "back propagation", and on to why so many "layers" and so on...!!!!
Great video. "energy function" instead of error function, but a great explanation of gradient descent and backprop in a super short time. Excellent job!
Wait a minute all day I try to understand what are neural networks and you have explained all parts so easily wow 😮 it obviously 🙄 imply that I have struggled to learn all of these terms so far but I finally have found a good explanation of back-propagation, gradient-descent, error functions and such 🎉🎉🎉🎉
i generally don't subscribe to any channels but this one deserves one. This takes a lot of understanding and love for the subject to do these kind of videos. thank you very much
I had not considered exactly how words related to eachother in automated texts and this video explained that concept in a really clear and concise way.
Wow, this video was really informative and fascinating! It's incredible to think about how much goes into building and training a language model. I never realized that language modeling involved so much more than just counting frequencies of words and sentences. The explanation of how neural networks can be used as universal approximators was particularly interesting, and it's amazing to think about the potential applications of such models, like generating poetry or even writing computer code. I can't wait for part two of this video!
Awesome video! I really appreciated your explanation and representation of neural networks and how the number of nodes and weights affect the accuracy.
What an amazing lecture on LLM! Loved the example Markov chain model with the bob Dylan lyrics, that was actually a fun homework exercise in one of my grad school courses. This really helped me understand neural networks, which are so much more complex.
Great video. The example of the network with too few curve functions to recreate the graph really helped me understand how more or fewer nodes affects the accuracy of the result.
![[1hr Talk] Intro to Large Language Models](/img/n.gif)
This is seriously *really* good, I've not seen someone introduce high level concepts by-example so clearly (and nonchalantly!)
What have they done? amazing stuff
Agree. I have it on one of my playlists now.
how is it possible that i’ve watched a ton of videos trying to understand LLMs from the likes of universities and big tech companies yet this simple video in comic sans explains everything in the most direct and concise manner possible !?
This is so good. I can't believe it has so few views.
Same, brillant explaination on NN
Was just about to write the same.
if you really think so, post the link to this video on your social media.
So few views... If a Kardashian posts a brain fart it gets more views from the unwashed masses. That is the sad reality.
Very few study about it
if there is an Oscar for best tutorial on the internet, this video deserves it !
Finally! Someone who knows how explain complexity with simplicity.
This is t he best explanation of LLMs I've seen
That might be the best, most concise and impactful neural network introduction I have seen to date
I've been watching a lot of videos on LLMs and the underlying mathematics. This explanation is PHENOMENAL. Not dumbed down, not too long, and uses concepts of existing maths and graphing that cement the concept perfectly.
I have been working on ways to explain LLMs to people in the humanities for the past year. You've done it in 5 brilliant minutes. From now on, I'm just going to hand out this URL.
These visuals were SO HELPFUL in introducing and understanding some foundational ML concepts.
Thanks, what a video, in 8 minutes I have learnet so much, and very well explained with graphics indeed.
This is an excellent articulation. We need part 3, 4, and 5
Holy shit. This is one of the best TH-cam videos I've seen all year so far. Bravo 👏👏👏
The best content ever I saw about the subject. Super dense and easy.
you sir, deserve my subscription. This was so good.
Thanks for showing what a neural network function looks like
I loved this. Clarity = real understanding= respect for the curiosity and intelligence of the audience.
Requests: Would like more depth about "back propagation", and on to why so many "layers" and so on...!!!!
I really liked your explanation of how "training a network" is performed. Made it a lot easier to understand
Straight away subscribed .... i would really love these videos in my feed daily.❤
this is excellently done, I'm very grateful for you putting this together.
Agree with the other comments, so clear and easy to understand. I wish all teaching material was this good...
Wow. This is so well presented. And a different take that gets to the real intuition.
nice concise video explaining what is a large language model
This is insanely good. I've understood things in 8 minutes that I could not understand after entire classes
nice animations
This is the best explanation of Large Language Models. I hope your channel gets more subscribers!
Great video. "energy function" instead of error function, but a great explanation of gradient descent and backprop in a super short time. Excellent job!
Brilliantly explained !
The content is gem. Thank you for this.
Being able to visualize this so simply is legendary. You're doing amazing work. Subbed
Wait a minute all day I try to understand what are neural networks and you have explained all parts so easily wow 😮 it obviously 🙄 imply that I have struggled to learn all of these terms so far but I finally have found a good explanation of back-propagation, gradient-descent, error functions and such 🎉🎉🎉🎉
Thanks Steve, this explanation is just... Brillant! 😊
Best and simplest explanation I have ever come across. Thank you sir
Omgg are you serious? You have some top-notch pedagogical skills.
You have made it so easy to see and understand - it puts into place all the complicated explanations that exist out there on the net.
This is an insanely good explanation. Subscribed.
This video deserves more views.
possibly the best explanation of LLM i've ever seen. accurate, pointed and concise
Eventhough I knew all this stuff, it is still nice to watch and listen to a good explanation of these fundamental ML concepts.
Brilliant! A truly example of intelligence and simplicity to explain! Thanks a lot.
Stunning video of absolutely high and underrated quality !!!!
Thanks so much, for this !
This might be the highest signal to noise video I've ever watched
This video is a must watch
Clean and clear explaination
Great way to explain a complex idea ⚡️
This is awesome. Very good Illustrations.
i generally don't subscribe to any channels but this one deserves one. This takes a lot of understanding and love for the subject to do these kind of videos. thank you very much
This was actually amazing
This is so good
I’m inspired to go back and learn Fourier and Taylor series
to everyone who was enjoying it assuming that no background was required, wait till 03:47
Finally I’m not the only one. Thought I was taking crazy pills reading these comments.
You’re a saint. This is incredible
This is uncut gold.
Clearly explained! I will use it.
Incredibly well explained! Thanks a lot!
Simple and clear, kudos!
Fantastic. Please teach more
You are a legend.
This video was ahead of its time
This is brilliant.
Excellent. Some of the best work I've seen. Thanks.
Great explanation of an advanced topic
Seems really really cool
I had not considered exactly how words related to eachother in automated texts and this video explained that concept in a really clear and concise way.
Really great description 👌
Amazing Video!
Unbelievably good video. Great work.
Wow. This is incredible!!
such a great content! thank you!
Wow .. what an explanation sir ❤
Thank you 🙏
Very well explained. Thank you for the video!
fantastic video, thank you!!!
Very nice illustration and fantastic explanation. Thanks
Great explanation. Thank you very much
Probably one of the best explanations I've come across. :)
Thank you so much! Very well and simply explained!
Wow, what a fantastic explanation!
This is literally gold
Outstanding!
Very clear and concise explanation! Excellent work!
Amazingly insightful. Fantastically well explained. Thanks !
This was awesome. I don't think I could adequately explain how this all works yet, but it fills in so many gaps. Thank you for this video!
Wow, this video was really informative and fascinating! It's incredible to think about how much goes into building and training a language model. I never realized that language modeling involved so much more than just counting frequencies of words and sentences. The explanation of how neural networks can be used as universal approximators was particularly interesting, and it's amazing to think about the potential applications of such models, like generating poetry or even writing computer code. I can't wait for part two of this video!
You are so good at explaining it! Please keep doing it.
🎉 I know I need to write something to promote this video. It deserves that
You are a genius, thank you for this amazing video!
Awesome video! I really appreciated your explanation and representation of neural networks and how the number of nodes and weights affect the accuracy.
Purely awsome
What an amazing lecture on LLM! Loved the example Markov chain model with the bob Dylan lyrics, that was actually a fun homework exercise in one of my grad school courses. This really helped me understand neural networks, which are so much more complex.
Underrated channel!!!!
Absolutely brilliant..great examples
this is gold, thanksss sir
such clean and lucid explanation. amazing
Wow, just saw this 😂, its excellent, thank you
very well explained!
Great video. The example of the network with too few curve functions to recreate the graph really helped me understand how more or fewer nodes affects the accuracy of the result.
Really well explained!!
Fascinating and such wonderful explanation. Thank you very much!
This is really good.
Really great explanation of LLM! Just earned a subscriber and I'm looking forward to more of your videos :)
This is fantastic. Thank you for sharing.
Incredible. Thank you