『Mixture of Transformers: Unveiling New Patents in Multi-Modal AI』のカバーアート

Mixture of Transformers: Unveiling New Patents in Multi-Modal AI

Mixture of Transformers: Unveiling New Patents in Multi-Modal AI

無料で聴く

ポッドキャストの詳細を見る

このコンテンツについて

 In this episode of Unzip, our hosts—Hope, Ryan, and Vivian—explore the cutting-edge advancements in AI through a newly-released paper on 'Mixture of Transformers' (MoT). Sponsored by LimitLess AI, the episode delves into how MoT optimizes transformer models for multi-modal inputs with efficiency gains and adaptability across different data types like text, images, and speech. Highlighting the contributions of authors like Noam Shazeer, Azalia Mirhoseini, and Geoff Hinton, the discussion covers the methodology, findings, and real-world applications that showcase MoT's potential to reshape AI landscapes. Join us as we bridge the gap between complex AI research and practical implementations.paper: Mixture of Transformers link: https://arxiv.org/abs/2411.04996

Mixture of Transformers: Unveiling New Patents in Multi-Modal AIに寄せられたリスナーの声

カスタマーレビュー：以下のタブを選択することで、他のサイトのレビューをご覧になれます。

Audible.co.jp

Amazon.co.jp
レビューはまだありません。