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5 Ways of Converting Unstructured Data into Structured Insights with LLMs

Image by Author   In today's world, we're constantly generating information, yet much of it arises in unstructured formats.  This includes the vast array of content on social media, as well as countless PDFs and Word documents stored across organizational networks.  Getting insights and value from these unstructured sources, whether they be text documents,…

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UC Berkeley and NYU AI Research Explores the Gap Between the Visual Embedding Space of Clip and Vision-only Self-Supervised Learning

MLLMs, or multimodal large language models, have been advancing lately. By incorporating images into large language models (LLMs) and harnessing the capabilities of LLMs, MLLMs demonstrate exceptional skill in tasks including visual question answering, instruction following, and image understanding. Studies have seen a significant flaw in these models despite their improvements; they still have some…

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This AI Paper from NVIDIA and UC San Diego Unveils a New Breakthrough in 3D GANs: Scaling Neural Volume Rendering for Finer Geometry and View-Consistent Images

3D-aware Generative Adversarial Networks (GANs) have made remarkable advancements in generating multi-view-consistent images and 3D geometries from collections of 2D images through neural volume rendering. However, despite these advancements, a significant challenge has emerged due to the substantial memory and computational costs associated with dense sampling in volume rendering. This limitation has compelled 3D GANs…

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Building an LLMOPs Pipeline. Utilize SageMaker Pipelines, JumpStart… | by Ram Vegiraju | Jan, 2024

Utilize SageMaker Pipelines, JumpStart, and Clarify to Fine-Tune and Evaluate a Llama 7B Model Image from Unsplash by Sigmund2023 was the year that witnessed the rise of various Large Language Models (LLMs) in the Generative AI space. LLMs have incredible power and potential, but productionizing them has been a consistent challenge for users. An especially…

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Embrace AI to enhance claims management

Submitting an insurance claim is often tedious for customers and underwriters alike. Collecting documents, filling forms, and waiting for decisions are frustrating, with lots of manual overhead and outdated document management systems. This represents significant inefficiency — Accenture estimates a whopping $160 billion productivity loss over five years across the global insurance industry. The introduction…

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