Advances in Neural Compression with Auke Wiggers - #570

The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)

コンテンツは TWIML and Sam Charrington によって提供されます。エピソード、グラフィック、ポッドキャストの説明を含むすべてのポッドキャストコンテンツは、TWIML and Sam Charrington またはそのポッドキャストプラットフォームパートナーによって直接アップロードされ、提供されます。誰かがあなたの著作権で保護された作品をあなたの許可なく使用していると思われる場合は、ここで概説されているプロセスに従うことができますhttps://ja.player.fm/legal。

2y ago 37:39

MP3•エピソードのホーム

Today we’re joined by Auke Wiggers, an AI research scientist at Qualcomm. In our conversation with Auke, we discuss his team’s recent research on data compression using generative models. We discuss the relationship between historical compression research and the current trend of neural compression, and the benefit of neural codecs, which learn to compress data from examples. We also explore the performance evaluation process and the recent developments that show that these models can operate in real-time on a mobile device. Finally, we discuss another ICLR paper, “Transformer-based transform coding”, that proposes a vision transformer-based architecture for image and video coding, and some of his team’s other accepted works at the conference.

The complete show notes for this episode can be found at twimlai.com/go/570

699 つのエピソード