Aug 21, 2023 · SimplyRetrieve is an open-source tool with the goal of providing a fully localized, lightweight and user-friendly GUI and API platform for Retrieval-Centric Generation (RCG) approach to the machine learning community.

Dec 6, 2023 · These representations can be used to condition the image generator. This framework, called Representation-Conditioned Generation (RCG), provides an effective solution to the unconditional generation problem without using labels.

Retrieval-augmented generation (RAG): Combines the generative capabilities of LLMs with the ability to retrieve information from external databases or documents in real time. The model queries an external source to find relevant information. It then uses the information to …

Retrieval-augmented generation (RAG) is a technique that enables generative artificial intelligence (Gen AI) models to retrieve and incorporate new information. [1] It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to ...

Nov 16, 2023 · With RCG, the primary role of the GenAI model is to interpret rich retrieved information from a company’s indexed data corpus or other curated content. Rather than memorizing data, the model focuses on fine-tuning for …

Aug 8, 2023 · SimplyRetrieve features a GUI and API based RCG platform, assisted by a Private Knowledge Base Constructor and a Retrieval Tuning Module. By leveraging these capabilities, users can explore the potential of RCG for improving generative AI performance while maintaining privacy standards.

Nov 16, 2023 · With RCG, the primary role of the GenAI model is to interpret rich retrieved information from a company’s indexed data corpus or other curated content. Rather than memorizing data, the model focuses on fine-tuning for …

RCG is a self-conditioned image generation framework that achieves SOTA unconditional image generation performance on ImageNet 256x256, bridging the long-standing performance gap between unconditional and class-conditional image generation.

Dec 7, 2023 · 本文提出了表示条件图像生成(rcg)：一种简单而有效的图像生成框架，为类无条件图像生成树立了新的基准。 RCG 不以任何人工注释为条件。 相反，它以 自监督表示分布 为条件，该表示分布是使用预训练的编码器从图像分布映射而来的。

Oct 18, 2024 · By introducing a compiled execution model, RCG allows developers to focus on building innovative AI applications rather than managing hardware complexities. It abstracts GPU coordination, reduces development overhead, and enhances performance—all while maintaining the familiar programming model of Ray Core.