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As LLMs become increasingly integral to various AI tasks, their massive parameter sizes lead to high memory requirements and bandwidth consumption. While quantization-aware training (QAT) offers…
A set of generic techniques and principles to design a robust, cost-efficient, and scalable data model for your post-modern data stack.Photo by Michael Dziedzic on UnsplashOver…
In the age where everyone uses ChatGPT for work and school, I am taking advantage of that to help me study in my university courseImage generated…
Large Language Models (LLMs) and their multi-modal counterparts (MLLMs) have made significant strides in advancing artificial general intelligence (AGI) across various domains. However, these models face…
Image by freepik Data analysis is undergoing a revolution. Machine learning (ML), once the exclusive domain of data scientists, is now accessible to data analysts…
Ideal Generative AI vs. Reality Foundational LLMs have read every byte of text they could find and their chatbot counterparts can be prompted to have…
Document understanding (DU) focuses on the automatic interpretation and processing of documents, encompassing complex layout structures and multi-modal elements such as text, tables, charts, and images.…
Evaluating conversational AI assistants, like GitHub Copilot Chat, is challenging due to their reliance on language models and chat-based interfaces. Existing metrics for conversational quality need…
Research Published 19 July 2024 Exploring AGI, the challenges of scaling and the future of multimodal generative AINext week the artificial intelligence (AI) community will come…
Survey on Machine Learning-Powered Augmented Reality in Education: ML advances augmented reality (AR) across various educational fields, enhancing object visualizations and interaction capabilities. This survey outlines…