Transformer Explained in 5 minutes by a Cat Girl

Описание: I explain the transformer neural network architecture that is widely used in AI today. This gives you the core pieces of the architecture in plain English terms in a pretty speedy amount of time. This is used in some of big popular AI architectures today such as ChatGPT and Anthropic's Claude.

00:00 1. Introduction to Dr. Juice
00:04 1.1. Discussion on transformer architectures
00:07 1.2. Importance of neural networks
00:09 1.3. Introduction to chat GPT developments
00:23 1.4. Advances in AI capabilities
00:30 1.5. Generative videos and images
00:35 1.6. Transformer architecture in AI advancements
00:47 1.7. Technical and intuitive explanation
00:54 2. Understanding Transformer Architecture
00:56 2.1. Lego block analogy
01:00 2.2. Self-attention operation basics
01:05 2.3. Neural network composition
01:15 2.4. Importance of the self-attention operation
01:22 2.5. Input to transformer networks
01:30 2.6. Converting text into vectors
01:53 2.7. Word representation in vector space
02:00 2.8. Dimensionality in embeddings
02:03 2.9. Explaining input matrix
02:32 2.10. Input-output processing in chatbots
02:57 2.11. Dive into heart of transformer
03:04 2.12. Self-attention operation detailed
03:49 2.13. The key-query matrix
04:00 2.14. Dot product and similarity measures
04:35 2.15. Operation flow in transformers
04:56 2.16. Matrix multiplication in transformers
05:43 3. Additional Details on Transformers
05:48 3.1. Other small transformer details
06:00 3.2. High-level explanation of attention matrix
07:01 3.3. Handling computational expenses
07:58 3.4. Multi-head attention for efficiency
08:16 4. Conclusion and Summary
08:22 4.1. Invitation for likes and subscriptions