Attention-based sequence transduction neural networks

Google LLC · USPTO — US10452978B2 · 2019

Abstract

Patent covering a neural sequence-transduction system that relies on attention layers to relate positions within input and output sequences, without recurrent or convolutional structure.

Why it matters

The Transformer, as a granted patent. Useful for seeing how a landmark architecture is framed in IP terms — and a reminder that the research and the patent often diverge.

transformerspatentarchitecture

Read the source

https://patents.google.com/patent/US10452978B2/en

About Nybble^™

The AI space moves fast.
Nybble^™ is how you keep up — and stay sharp.

Snack

What happened. In two minutes.

The AI news cycle moves at a pace no one can keep up with. Snack distills what launched, what shipped, and what matters — every day, without the filler.

Go to Snack

Stack

The concepts behind the headlines.

News tells you what. Stack tells you why and how. From RAG architectures to agentic evals, these are the ideas that will shape what you build next.

Go to Stack

Hack

Prove you actually get it.

Reading about LangChain is not the same as knowing it. Hack challenges you with production-grade questions, then shows you the references that make the answer stick.

Go to Hack

Attention-based sequence transduction neural networks

The AI space moves fast.Nybble™ is how you keep up — and stay sharp.

The AI space moves fast.
Nybble^™ is how you keep up — and stay sharp.