In transformers, the issue of vanishing gradient arises when information does not propagate effectively through the layers, leading to a loss of useful signal. To address this, a residual stream technique is used where the input data is routed around a layer to preserve the original data alongside the processed output. By feeding both the original and processed data to the next layer, errors are prevented from compounding, ensuring the preservation of essential information throughout the system.

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode