Image Identification and Classification with Amazon Bedrock, OpenSearch, and OpenCLIP
<p>In this post, we will build a hypothetical auction vehicle damage assessment and valuation application using generative AI technologies. Based on the vehicle identification number (VIN) and images showing vehicle damage, we will use machine learning and generative AI technologies to assess the vehicle’s value for auction and create a detailed vehicle description. Major technologies include <strong>OpenCLIP</strong>, an open-source implementation of OpenAI’s CLIP (<strong>C</strong>ontrastive <strong>L</strong>anguage-<strong>I</strong>mage <strong>P</strong>re-training), Amazon’s recently announced <strong>Vector Engine for Amazon OpenSearch Serverless (Preview)</strong>, and <strong>AI21 Labs’ Jurassic-2 (J2) Ultra Foundation Model</strong>, accessed through <strong>Amazon Bedrock</strong>. The application can be easily adapted for multiple other industries as well where evaluating the cost of damage is required, including insurance claims, shipping, and retail.</p>
<p>This post was inspired by a series of Generative AI hackathons I recently competed in with two of my close AWS peers, <a href="https://www.linkedin.com/in/jigna-gandhi-51a8675b/" rel="noopener ugc nofollow" target="_blank">Jigna Gandhi</a> and <a href="https://www.linkedin.com/in/chadjodon/" rel="noopener ugc nofollow" target="_blank">Chad Jodon</a>. As a team, we developed this winning solution for the vehicle auction industry.</p>
<p><a href="https://ai.gopubby.com/image-identification-and-classification-with-amazon-bedrock-opensearch-and-openclip-5442baca1846"><strong>Read More</strong></a></p>