I really enjoyed both of these LLM videos. They are so concise and informative and the pacing is excellent.

This is one of the best explainer vids on LLMs I’ve seen yet. Not too long, not too short, good pacing, good visualizations. Great work, thanks!

It’s amazing and so funny to me how LLM can produce fully functional python programs and write these poetic Bob Dylan inspired lyrics… but when prompted with “you’re going north. You turn right, then you turn left. Now you’re going …” it said SOUTH ☠️

I like that you used a recipe prompt to demonstrate what a LLM is good at doing, then actually followed the recipe and proved that it actually worked (and tasted good!).

Great stuff. Possibly the best intro material to LLMs that I have seen. Thunbs up!

I think this is the best, most intuitive and most illustrative video describing LLMs/transformers. Thank you so much!

This is the single best explaination I’ve come across on LLM’s

Thanks so much for both of these videos. They are wonderful. I think I understood them a bit more since I’ve done some basic assisted machine learning dev (up to neural networks). If anyone is a bit lost, read up on linear and logistic regression, then onto neural networks.

This is a really good intro indeed! I encourage to make more content like this

Really easy to follow, well paced, easy on the ear, and just the right level thanks!

You really have a talent to teach things.

These are two great videos that introduced how large language model works in a very comprehensive way.👍👍👍

Brilliant overview for a non-technical person like me... and glad to see you tested the recipe!

So pleased to get a clear and credible glimpse under the hood. Thank you.

EXCELLENT Vid, PLS DO MORE, on Deep learning , covering the whole workflow of making an LLM, especially, what os LORa, VEctor embeddings, etc I'm sure you'll get huge interest You have a gift for explaining. Thanks!

Very much enjoyed these two videos. More please! Clear and detailed.

This is my first search for a LLM explanation and very pleased with the video. I am not a mathematician or programmer but I am very interested in learning how LLM works. From my humble perspective I can say we reached a point of no return and this technology is progressing at an exponential rate. With the development of quantum computing, I have no doubt that it will surpass human intelligence in ways we don't understand.

I'm a bit confused by how stacking attention layers works at 4:12. Does the second layer take the first layer's prediction as input? Is the first layer's prediction still "next words" at that point, or is it now some sort of abstract intermediate value? How exactly does that capture higher level reasoning? Would appreciate any clarification!

Thank you! This is excellent. I love the animations. They are helpful!

What a great walk through! Thanks so much for sharing.

Great the concepts transition. Great illustrations. The best of the best this couple of videos. What about more on other networks like r-cnn and audio nets? 😃

This is awesome. Would love to learn more!

I hope you keep up with these videos, they are seriously great. Already suscribed and I'll check the rest of your channel. Thank you.

Not a second wasted. Just brilliant ❤️

Thanks for the crisp walkthrough of the technology. It is a very good introduction.

This is super fascinating. I want to learn to grow my own language models from the ground up with languages like c++/rust. I dont care if the language model i develop is inaccurate or not. I just want to understand chatgpt under the hood. How may i get started?

Thank you. Those were very clear explanations of just the right length. Loved that you cooked the pancakes too!

This is the best video on Language Models that I seen. Probably the best on the Internet. You should maybe add chatgpt to the title to get more views.

Thanks for an original presentation of Large Language Models. It gave me new insight.

Great overview! People need to see this video pair before freaking out that LLMs are actually intelligent.

Thank you. Just the right level for my tiny organic brain.

nice work, really good to visualize these things even though I already know this.

This is really nice! Now I understand why chatGPT tends to make up a lot of stuff with coherent sentences

Pretty nice explanation in both videos.Thanks!

Ever think about audio synthesis and wave forms?? And how analogue synthesis utilising wave tables can offer a way to both communicate and comput information.

This was super informative and concise, loved it! But my real question is how were those pancakes?

Great video, leaving a comment to let you know it was very insightful. Thank you.

eliminating bias and stereotypes from language models is a lost cause, because it's the same as asking the network to lie.

Loved this! Thanks for the great video!

Great explanation, glad I stumbled upon it ! Subscribed :)

Very clear. Thanks a lot.

what bothers me is that (if I am to accept your account of them) these models still seem largely sequence based. in my time in university we focused extensively on parsing the grammar before we even thought about letting AI predict the next word. some grammatical structures are triangular in the sense that they wrap around the structure of the previous iteration and put a word in front of AND behind it. think of constructs like "on the one hand X, on the other". things like that seem impossible to learn efficiently on the basis of sequence alone, since the length of X is variable. grammatical structure also simply eliminates a lot of possibilities when it comes to next word prediction. two words that have the same literalization aren't even the same word grammatically in a lot of cases.

Very good content! Keep going! thanks.

I would love more of the visual explainers on ML concepts. Subscribing. "Some folks say they're overhyped / But I do think that's true / I think they're just misunderstood / Just like me and you" That generated lyric gave me CHILLS

Very well made!

amazing videos!! learnt so much

Very interesting... Now I understand more about how ChatGPT works...

An excellent video on language models

This is doing a lot more than "predicting the next word" as people say. Its actually learning to use language to learn and communicate.

I love that you finished cooking the recipe! Great video :)

honestly the most important question is, was the recipe any good ? I feel like I wanna get into this AI stuff. I'm going to add a full rack to my basement and try to work out a text processing AI to help me dribble new ideas for my work.

Thanks for the good explanation, very much on time

This was awesome! Thanks

imagine combining GPT 4 with AlphaGo

Very underrated and underappreciated video.

Please do more videos on LLMs!!! But also I need to know, how were the pancakes?

just wow... nothing can match this explanation..

Well done!

great video bud cheers!

What do you think of GPT4?

Typo alert! Frost's wonderful poem begins as so: "Two roads diverged in a yellow wood". (Not "diverted"!)

Great videos! Btw, how did you like your avocado cocoa thing? 😄

Just look how far we have come in only eight months.

I loved that you actually cooked that recipe! :-)

Awesome. Thank you

Thank you for this. But one question is, does this mean GPT-3 etc is intelligent? Is it actually aware of what it's saying or is it just guessing the whole way?? But still, even the guess can be so good that it doesn't even matter. Hope the pancakes tasted great.

5:53 lol this gut feeling based measurement to decide to ship this to public is one of the achilles heels of current AI providers cause they need to generate revenue fast.

you actually made the cookies hahaha that's awesome, great video btw!

Cool video, thanks

GPT-4: Might I suggest dubbing them "Chocomole Pancakes"? 😮😂

Fantastic work, hope those pancakes tasted better than they looked! xD

Thank you for the video. However, it was difficult to understand in parts. You said we need to train the model on facts to answer the president question. And therefore we need a stack of transformers. Huh? Why? Why particularly a stack and not a heap? Why 96? Why do they have hundreds of billions of params? What exactly do you mean some layers "focus on syntax" while others focus on other things. Then you said, we're ready to train. Hold on, you haven't explained how those transformers are trained together. And FINALLY, oh God, why do most people take this for granted. How on earth does "a haiku about a turtle and a stop sign" actually get input into the model? The model is trained to auto-complete, right, so why isn't the response an auto-completion of that sentence? How does that get transformed into the response we see? How can it tell me why a joke is funny? What sort of auto-completion goes on there?

It looks like GPT hands you a great chocolate guacamole pancake recipe... now I wanted to try too loool

Thumbs-up for actually making the pancakes. 😂

5:55 the german one is correct

fun funny fantastic and I am a fan!

ChatGPT gets the 37 question right now.

Big thanks mate

That language neural network at 0:50 belongs on a tshirt somewhere

I can't get why we stack them like so. If the first transformer block predicts a word, what second does, third? And why do they still need attention then?

Wonderful stuff. 👍 Also, _please can I get some oven and the oven please let us have to do the run and not a big difference in a bit more about people who have been in touch your own house is the best way of a bit more about people..._ *My phone wrote the part in italics.

5.6K subscribers? 🤔 NOT FOR LONG.

😂😂😂 7:19

liked and subscribed

Was the chocolate guacamole pancake any good?

Soo, are cocoa-guacamole pancakes any good?

Verdict on the guacookies?

pancake approved 🥞👍

7:10 oh nO YOU DID NOT DO THAT

What is a 'parameter'? It seems like a basic concept that wasn't explained.

So how did the pancakes taste?

How did those pancakes taste?! for real!

Hey dude, I just spent 8+7 minutes, not 5.

Haha you made the pancake

Who else confused

How were the pancakes?

promosm

the Mona Lisa of LLM explanations .. thanks!