From 9bb65d9f053d0691245c4ec039e6bae9848af0fe Mon Sep 17 00:00:00 2001 From: Jael Gu Date: Wed, 18 Sep 2024 13:27:20 +0800 Subject: [PATCH] Add more resources Signed-off-by: Jael Gu --- README.md | 10 ++++++++++ 1 file changed, 10 insertions(+) diff --git a/README.md b/README.md index 28e1f61..3c98167 100644 --- a/README.md +++ b/README.md @@ -114,3 +114,13 @@ Takes in a numpy rgb image in channels first. It transforms input into animated Jie Chen, Gang Liu, Xin Chen "AnimeGAN: A Novel Lightweight GAN for Photo Animation." ISICA 2019: Artificial Intelligence Algorithms and Applications pp 242-256, 2019. + + +# More Resources + +- [What is a Generative Adversarial Network? An Easy Guide](https://zilliz.com/glossary/generative-adversarial-networks): Just like we classify animal fossils into domains, kingdoms, and phyla, we classify AI networks, too. At the highest level, we classify AI networks as "discriminative" and "generative." A generative neural network is an AI that creates something new. This differs from a discriminative network, which classifies something that already exists into particular buckets. Kind of like we're doing right now, by bucketing generative adversarial networks (GANs) into appropriate classifications. +So, if you were in a situation where you wanted to use textual tags to create a new visual image, like with Midjourney, you'd use a generative network. However, if you had a giant pile of data that you needed to classify and tag, you'd use a discriminative model. +- [Multimodal RAG locally with CLIP and Llama3 - Zilliz blog](https://zilliz.com/blog/multimodal-RAG-with-CLIP-Llama3-and-milvus): A tutorial walks you through how to build a multimodal RAG with CLIP, Llama3, and Milvus. +- [Generative AI for Creative Applications using Storia Lab - Zilliz blog](https://zilliz.com/blog/generative-ai-for-creative-applications-using-storia-lab): This post discusses how Storia AI generates and edits images through simple text prompts or clicks and how we can leverage Storia AI and Milvus to build multimodal RAG. +- [Image Embeddings for Enhanced Image Search - Zilliz blog](https://zilliz.com/learn/image-embeddings-for-enhanced-image-search): Image Embeddings are the core of modern computer vision algorithms. Understand their implementation and use cases and explore different image embedding models. +- [Real-Time GenAI without Hallucination Using Confluent & Zilliz Cloud](https://zilliz.com/product/integrations/confluent): nan \ No newline at end of file