In recent years, FM sizes have been increasing. It is important to consider the massive amount of compute often required to train these models. The compute clusters used in these scenarios are composed of more than thousands of AI accelerators such as GPUs or AWS Trainium and AWS Inferentia, customContinue Reading
This post is co-written with Eliuth Triana, Abhishek Sawarkar, Jiahong Liu, Kshitiz Gupta, JR Morgan and Deepika Padmanabhan from NVIDIA. At the 2024 NVIDIA GTC conference, we announced support for NVIDIA NIM Inference Microservices in Amazon SageMaker Inference. This integration allows you to deploy industry-leading large language models (LLMs) on SageMakerContinue Reading
Several factors can make remediating security findings challenging. First, the sheer volume and complexity of findings can overwhelm security teams, leading to delays in addressing critical issues. Findings often require a deep understanding of AWS services and configurations and require many cycles for validation, making it more difficult for lessContinue Reading
This post is co-written with Kristina Olesova, Zdenko Esetok, and Selimcan akar from Accenture. In today’s data-driven world, organizations often face the challenge of extracting structured information from unstructured PDF documents. These PDFs can contain a myriad of elements, such as images, tables, headers, and text formatted in various styles,Continue Reading
In today’s rapidly evolving landscape of artificial intelligence (AI), training large language models (LLMs) poses significant challenges. These models often require enormous computational resources and sophisticated infrastructure to handle the vast amounts of data and complex algorithms involved. Without a structured framework, the process can become prohibitively time-consuming, costly, andContinue Reading
This post is co-written with Jhanvi Shriram and Ketaki Shriram from Krikey. Krikey AI is revolutionizing the world of 3D animation with their innovative platform that allows anyone to generate high-quality 3D animations using just text or video inputs, without needing any prior animation experience. At the core of KrikeyContinue Reading
In large language model (LLM) training, effective orchestration and compute resource management poses a significant challenge. Automation of resource provisioning, scaling, and workflow management is vital for optimizing resource usage and streamlining complex workflows, thereby achieving efficient deep learning training processes. Simplified orchestration enables researchers and practitioners to focus moreContinue Reading
