Latent Space: The AI Engineer Podcast cover image

ICLR 2024 — Best Papers & Talks (ImageGen, Vision, Transformers, State Space Models) ft. Durk Kingma, Christian Szegedy, Ilya Sutskever

Latent Space: The AI Engineer Podcast

CHAPTER

Advancements in Transformer Architectures

This chapter explores cutting-edge developments in transformer architectures, focusing on long context extension techniques and state space models. It discusses the implications of these advancements in real-world applications and poses future research directions that extend beyond transformers. Additionally, the chapter examines challenges in model training, particularly with linear time-invariant models, and proposes innovative solutions for enhancing performance.

00:00
Transcript
Play full episode

Remember Everything You Learn from Podcasts

Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
App store bannerPlay store banner