Integrating Vector with Open AI CLIP
Open AI rang in the new year with a major announcement: two new revolutionary pieces of research: 1)DALL-E which can generate images from…
Open AI rang in the new year with a major announcement: two new revolutionary pieces of research: 1)DALL-E which can generate images from text, and 2)CLIP which provides a one-shot image classification approach without the requirement of training a model. This article focuses on CLIP, specifically, how the Vector robot can classify objects that it sees as long as an input list of possible text sequences that describe the expected objects is provided.
First, what is the big deal about CLIP. One of the major challenges in deep learning is the requirement of labelled datasets required to train a model. While many public datasets are available to help you learn how to train neural networks, building a labelled data set for the specific requirement of one’s application is a major challenge. Worse, a model trained on a labelled data set would be good only for the same use case with which the labelled data set was generated. This limits the use of machine learning or deep learning to the folk…
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