Transformers, explained: Understand the model behind GPT, BERT, and T5

Over the past five years, Transformers, a neural network architecture, have completely transformed state-of-the-art natural language processing. Want to translate text with machine learning? Curious how an ML model could write a poem or an op ed? Transformers can do it all. In this episode of Making with ML, Dale Markowitz explains what transformers are, how they work, and why they’re so impactful. Watch to learn how you can start using transformers in your app!

Chapters:
0:00 - Intro
0:51 - What are transformers?
3:18 - How do transformers work?
7:41 - How are transformers used?
8:35 - Getting started with transformers

#MakingwithMachineLearning #MakingwithML

product: Cloud - General; fullname: Dale Markowitz; re_ty: Publish;

[Omikoshi]

Ability to break down complex topic is such an underrated super power. Amazing job.

[softcoda]

This has to be the best explanation so far, and by a very large margin.

[rohanchess]

How did you condense so many pieces of information in such a short time? This video is on a next level, I loved it!

[robchr]

Transformers! More than meets the eye.

[tongluo]

Great explanation of the key concept of position encoding and self attention. Amazing you get the gist covered in less than 10 minutes.

[maayansharon]

This is a GREAT explanation! please lower the background music next time it could really help. thanks again! awesome video

[dj]

This is awesome. This has been one of the best overall breakdowns I've found. Thank you!!

[dylan_curious]

This is such an informative video about transformers in machine learning! It's amazing how a type of neural network architecture can do so much, from translating text to generating computer code. I appreciate the clear explanations of the challenges with using recurrent neural networks for language analysis, and how transformers have overcome these limitations through innovations like positional encodings and self-attention. It's also fascinating to hear about BERT, a popular transformer-based model that has become a versatile tool for natural language processing in many different applications. The tips on where to find pertrained transformer models and the popular transformers Python library are super helpful for anyone looking to start using transformers in their own app. Thanks for sharing this video!

[rajqsl]

You have the gift of making things simple to understand. Keep up the good work 🙏

[trushatalati]

This is a really awesome video! Thank you so much for simplyifying the concepts.

[luisxd]

Amazing video! Nice explanation and examples 😄👍
I would like to see more videos like this and practices ones

[rajathslr]

Just Mind-blowing way to explain an LLM, just phenomenal.

[jovermitano]

Thank you for this high-level explanation. I now understand transformers more clearly

[erikengheim]

Thanks you did a great job. I spent some time already looking at different videos to capture the high level idea of what transformers are about and yours is the clearest explanation. I actually do have an educational background in neutral networks but don't go around remembering every details or the state of the art today so somebody removing all the unessesary technical details like you did here is very useful.

[reddyvarinaresh]

I loved it and very simple, clear explanation.

[Jewish]

i really enjoyed the concepts you explained. simple to understand

[mfatal]

Love the content and thanks for the great video! (one thing that might help is lower the background music a bit, I found myself stopping the video because I thought another app was playing music)

[shravanacharya]

So easy and clear to understand. Thanks

[PaperTools]

Dale you are so good at explaining this tech, thank you!

[MaxKar]

Nice amount of info parted in this video. Very clear info on what Transformers are and what made them so great.