Jay Alammar
The GPT-3 model from OpenAI is a new AI system that is surprising the world by its ability. This is a gentle and visual look at how it works under the hood — including how the model is trained, and how it calculates its predictions.
Introduction & GPT-3 Demos (0:00)
GPT-3 Inputs and Outputs (2:06)
Training the GPT-3 model (2:48)
The scale of GPT-3 and its 175 billion parameters (6:37)
The order of GPT-3 token processing (7:58)
“Deep” learning: looking inside a layer stack (9:00)
Input prompts and priming examples (11:00)
Fine-tuning: the best is yet to come (11:56)
Twitter: https://twitter.com/JayAlammar
Blog: https://jalammar.github.io/
Mailing List: http://eepurl.com/gl0BHL
More videos by Jay:
Jay’s Visual Intro to AI
https://www.youtube.com/watch?v=mSTCzNgDJy4
Making Money from AI by Predicting Sales – Jay’s Intro to AI Part 2
https://www.youtube.com/watch?v=V4-lXSs3jrk
Very good blog posts and videos Jay thank you very much !
Nice video Jay!
double likes for Khambala & Telfaz 11 😉
Thank you Jay for the wonderful crisp explanation.
0:13 Anime Time https://youtu.be/TzaJIBtMtRQ
Thanks
❤️
Thank you for the explanation Jay.
يعطيك العافية شغل ممتاز !
😍🙏
Telfaz11 should be proud
Could you please share any tips for illustrations?
This is the jay alammar hey there how to learn these concepts means how to remeber code and learn like you
Nice explanation 👍🏻 looking for coming videos
There has a better way to explain this? It went over my head
Jay why didnt you add GNU sticker in laptop??
Thanks for the crystal clear video Jay! I have one doubt, hoping you could answer it.
In the case of the React demo, are we not essentially training GPT-3 by giving samples of code for some input? Now if there were no updates in weights here, how does GPT-3 even predict the results based on the earlier training? This question is because you mentioned as of now GPT-3 does not do any fine-tuning/update of weights.
You told by showing animation, but its like powerpoint.
Great simple explanation, Thank you!
شكراً جزيلاً!
Your explanations on NLP models are legendary.
Jay, thank you so much for your efforts to visually explain AI. Awesome video.
Some feedback: I didn't really understand "The order of GPT-3 token processing" part. It was quite abstract to me, maybe an example would clarify it =)
Also, maybe it would be helpful to compare the deep learning layers to how images are classified, because it is still very abstract to me how "meaning" is added to tokens. I understand that an image can be classified by layers that analyze patterns of pixels to "recognize/classify" shapes, but how does that work for tokens of text?
Beautifully explained…. ❤️👍