Скачать или смотреть Transformers Explained: How 'Attention' Changed AI | Before AGI Podcast

Descript Referral Link: https://get.descript.com/968yizg2t4r3 In this episode of Before AGI, we dive deep into the groundbreaking paper 'Attention is All You Need' that laid the foundation for modern AI advancements. Discover how the transformer model has revolutionized natural language processing, outpacing older models like RNNs with its efficient and sophisticated techniques. Learn about the inner workings of transformers, including the encoder-decoder architecture and the self-attention mechanism, and explore their real-world applications in search engines, voice assistants, and chatbots. Join us as we explore the transformative potential of this AI technology and its impact on everyday life.

00:00 Introduction to the Foundation of Modern AI
00:35 The Pre-Transformer Era: RNNs and Their Limitations
01:17 The Birth of Transformers: Attention is All You Need
02:41 How Transformers Work: Encoders, Decoders, and Self-Attention
05:35 Real-World Applications of Transformers
07:58 Limitations and Future of Transformer Technology
10:24 Conclusion and Further Learning Resources

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