July 2023 Summaries

This guide explores how to create a multimodal search engine using ImageBind and Deep Lake. Multimodality in AI involves generating images with Midjourney or Dall-E, but its use cases are expanding. The combination of these technologies allows for the creation of an AI image search app that retrieves images using text, audio, or visual inputs. This opens new doors for accessibility, user experience, and business intelligence. By leveraging ImageBind by Meta AI and Deep Lake by Activeloop, multimodal data can be stored and queried, unlocking a wide range of potential applications in various industries.

This article introduces EfficientNet, a smaller and faster model ideal for quick-result applications in detecting early signs of Diabetic Retinopathy. It explains how EfficientNet operates using Neural Architecture Search (NAS) to establish a baseline network and then undergoes compound scaling. The Messidor dataset is used to train the EfficientNet model, which can classify and identify the severity of diabetic retinopathy based on visible lesions in the retinal images. EfficientNet's performance compares favorably to other state-of-the-art models due to its unique scaling methodology, offering better accuracy with fewer parameters and less computational complexity.