Thanks to the widespread adoption of ChatGPT, millions of people are now using Conversational AI tools in their daily lives. At its essence, ChatGPT belongs to a class of AI systems called Large Language Models, which can perform an outstanding variety of cognitive tasks involving natural language.
What are Large Language Models?
Language Models (LMs) are a class of probabilistic models explicitly tailored to identify and learn statistical patterns in natural language. Because of their current success, they are seen commonly as models that comprehensively understand natural language. But surprisingly, they are trained with quite a simple logic.
In this video, let's explore the main concepts related to building and using LLMs.
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References:
03:00 - Transfer Learning - [ Ссылка ]
03:32 - Neural Networks - [ Ссылка ]
03:32 - Backpropagation - [ Ссылка ]
04:35 - Word Embeddings - [ Ссылка ]
04:35 - Attention mechanism - [ Ссылка ]
08:28 - Emergent abilities of large language models - [ Ссылка ]
10:13 - RLHF - [ Ссылка ]
00:00 Introduction
00:27 Self-Supervised Learning
01:35 Fine-Tuning and Transfer Learning
03:04 Architecture of an LLM
04:40 Encoder-Decoder Structure
05:40 Making Bigger Models
06:58 Data Need of LLMs
07:40 Emergent Abilities of LLMs
08:30 Instruction Tuning
09:40 Reinforcement Learning from Human Feedback
10:17 Follow us for more!
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