diff --git a/README.md b/README.md index 02a5d107..a54eab47 100644 --- a/README.md +++ b/README.md @@ -56,11 +56,11 @@ GNES enables large-scale index and semantic search for text-to-text, image-to-im GNES is all-in-microservice! Encoder, indexer, preprocessor and router are all running in their own containers. They communicate via versioned APIs and collaborate under the orchestration of Docker Swarm/Kubernetes etc. Scaling, load-balancing, automated recovering, they come off-the-shelf in GNES. - How long would it take to deploy a change that involves just changing the encoder from BERT to ELMO or switching a layer in VGG? In GNES, this is just one line change in a YAML file. We abstract the encoding and indexing logic from the code to a YAML config, so that you can combine or stack encoders and indexers without even touching the codebase. + How long would it take to deploy a change that involves just changing the encoder from BERT to ELMO or switching a layer in VGG? In GNES, this is just one line change in a YAML file. We abstract the encoding and indexing logic to a YAML config, so that you can change or stack encoders and indexers without even touching the codebase. Taking advantage of fast-evolving AI/ML/NLP/CV communities, we learn from best-of-breed deep learning models and plug them into GNES, making sure you always enjoy the state-of-the-art performance. -

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Generic & Compatible

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🌌

Generic & Universal

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Model as Plugin

💯

Best Practice