Demystifying Generative AI - 'Under the hood' of Large Language Models: How AI Learns & Generates

Dive deep into the fascinating world of artificial intelligence and language models with our second episode of "Demystifying Generative AI". This episode takes you under the hood of ChatGPT, revealing the intricate processes that enable computers to understand and generate human language.

Learn about the different machine learning paradigms, including supervised and reinforcement learning, and how large language models (LLMs) are trained on vast datasets to predict and generate text.
Discover the revolutionary architecture of transformers, introduced in the groundbreaking paper "Attention is All You Need", and how it solved major challenges in AI language processing.

Explore the importance of encoder and decoder blocks, self-attention layers, and positional encodings in making AI more efficient and capable of understanding the context and nuances of language. Whether you're a tech enthusiast, a professional in the field, or simply curious about how AI works, this episode offers valuable insights into the technology shaping our future.

Don't forget to like, share, and subscribe for more content on unraveling the mysteries of generative AI. Share your thoughts and questions in the comments below, and let us know what topics you'd like us to cover next!

#generativeai #cloudcomputing #chatgpt #largelanguagemodels

[ZaarsShed]

Thank you Matthias! Looking forward for Part III!

[_AKA_ThaScientist]

Thanks for the video. I am completely green on this generative idea topic.