AmazonScience/document-haystack
Document Haystack Dataset This repository contains the dataset for the paper “Document Haystack: A Long Context Multimodal Image/Document Understanding Vision LLM Benchmark”. 📑 Abstract Paper The proliferation of multimodal Large Language Models has significantly advanced the ability to analyze and understand complex data inputs from different modalities. However, the processing of long documents remains under-explored, largely due to a lack of suitable… See the full description on the dataset page: https://huggingface.co/datasets/AmazonScience/document-haystack.
2090k
122Shareholders and Friends, 3Three decades ago, we believed that information and 4technology would transform banking. We were driven 5by a sense of possibility, a vision to disrupt the status 6quo and to deliver breakthrough products and 7experiences to consumers who were not being well-8served by banks that were hundreds of years old. We 9built a company that was powered by data, analytics, 10scientific testing and statistical modeling. We were a 11technology company that does banking, competing 12against banks that use technology, but it is not who 13they are. Now, three decades and another tech 14transformation later, that continues to be who we 15are. And the revolution in banking is accelerating.16We celebrated our IPO in 1994, the same year that 17the modern internet was born. In the late 2000s, 18three revolutions crashed onto the scene at once: 19the cloud, the smartphone, and machine learning. 20I call this the triple revolution. It propelled the world 21into big data and machine learning in real time, 22enabling instant, mass-customized solutions for 23consumers and businesses. The winning companies 24would offer these real-time, intelligent solutions. 25The rest would risk becoming also-rans.26Eleven years ago we realized that the technology 27on which we had built our company–modern at the 28time–was not made for the world of real-time, intelligent 29solutions. So we went all in on a comprehensive 30technology transformation, starting from the bottom 31of the tech stack up. We searched the world for elite 32technology talent and transformed how we built 33software. We migrated entirely to the public cloud. 34We transformed our data ecosystem. We rebuilt the 35