Tutorial: Beyond Neural Search: Hands-on Building Cross-Modal/Multi-Moda... Han Xiao & Sami Jaghouar

Tutorial: Beyond Neural Search: Hands-on Building Cross-Modal/Multi-Modal Solution with Jina AI - Han Xiao & Sami Jaghouar, Jina AI Neural search is using deep learning to search unstructured data, which has been developed rapidly over the last 2 years. With opensource framework like Jina (https://github.com/jina-ai/jina), searching cross-modal/multi-modal data via deep neural networks becomes extremely straightforward. DALL·E, a powerful image-to-text generator released by OpenAI in 2021 further boosts the popularity of multimodal applications. We now see thousands of astonishing artwork made by DALL·E every day. How all these new technologies will change our way of comprehending data? Most importantly, how can developers easily build solutions & applications leveraging those technologies? This tutorial will answer these two questions. This tutorial is bi-partite. In part 1, Dr. Han Xiao will introduce the recent advances of neural search and multi-modal intelligence. He will break down the design principle of Jina ecosystem. In part 2 (bring your laptop), Han will guide step by step to build DALL·E Flow: a Human-in-the-Loop workflow for creating HD images from text. He will demonstrate how Jina unlocks multi-modal/cross-modal capability in your solution & applications. This is a great chance to get hands dirty with Jina and DocArray's Pythonic API and to embrace the charm of generative arts.