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CLIP vs CLIPPO
Combining Vision and Language: A Look at OpenAI’s CLIP’s Potential and CLIPPO’s Quantum Leap for Multimodal Learning

OpenAI’s CLIP is a breakthrough in the computer vision. While OpenAI’s DALL-E creates images from text captions for a wide range of concepts expressible in natural language and OpenAI’s CLIP efficiently learns visual concepts from natural language supervision, CLIPPO is a quantum leap for Multimodal Learning in the field of computer vision.

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ABC-XYZ Classification in Supply Chain Intelligence

Poor inventory management often leads to out-of-stock situations for businesses that can be avoidable with proper tools and techniques. Product classification is a customizable and effective way to manage stocks by considering the properties of SKUs and their impact on sales…

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A Brief Introduction to Federated Learning

Federated Learning is a decentralized machine learning technique that follows a collaborative approach to train models. In this method, the processing is broken down across various devices where they are trained on specific data. This modelling happens on a local device level, distributed across multiple devices.

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Zero-shot Question Answering: a technique to advance conversational AI

Fine tuning language models with natural language instructions work really well but has a major flaw – they require large amounts of human instructions to train. Such datasets are limited in quantity and narrow in scope, with most containing similar instructions. Hence, SELF-INSTRUCT, a framework for improving the instruction-following capabilities…

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How ChatGPT can boost Customer Analytics?

As businesses strive to improve customer satisfaction and drive growth, they’re increasingly turning to customer analytics to gain a deeper understanding of their customer’s needs and preferences. Customer analytics can help businesses understand their customers better, improve customer satisfaction and loyalty, optimize marketing campaigns, and increase sales.

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Fine Tuning Language Models with Self-Generated Instructions

Fine tuning language models with natural language instructions work really well but has a major flaw – they require large amounts of human instructions to train. Such datasets are limited in quantity and narrow in scope, with most containing similar instructions. Hence, SELF-INSTRUCT, a framework for improving the instruction-following capabilities…

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