
Using ChatGPT to Improve a Computer Vision Model | Data Dojo 2023
.png?ixlib=gatsbyFP&auto=compress%2Cformat&fit=max)
With the proliferation of use cases for ChatGPT, we set out to investigate whether ChatGPT could be used to make improvements in other AI systems. We tested it on a practical problem in a modality of AI in which it has not been trained on - computer vision - and reported the results. ChatGPT's suggestions achieved on average a 10.1% improvement in precision and a 34.4% improvement in recall over our random sample, using a purely data-centric metric-driven approach.
Eric Landau, Encord's Co-founder and CEO, sits down with the Data-Centric AI Community to share more about the process & lessons learned!
__
Eric Landau is the co-founder and CEO of Encord, an active learning platform for computer vision. Before Encord, he spent nearly a decade in high-frequency trading at DRW where he was the lead quantitative researcher on a global equity delta-one desk and put thousands of models into production. He holds a M.S. in Applied Physics from Harvard University, M.S. in Electrical Engineering, and B.S. in Physics from Stanford University.