inference

In: Artificial Intelligence

Successful generative AI software as a service (SaaS) systems require a balance between service scalability and cost management. This becomes critical when building a multi-tenant generative AI service designed to serve a large, diverse customer base while maintaining rigorous cost controls and comprehensive usage monitoring. Traditional cost management approaches forContinue Reading

In: Artificial Intelligence

This post is co-written with Kshitiz Gupta, Wenhan Tan, Arun Raman, Jiahong Liu, and Eiluth Triana Isaza from NVIDIA. As large language models (LLMs) and generative AI applications become increasingly prevalent, the demand for efficient, scalable, and low-latency inference solutions has grown. Traditional inference systems often struggle to meet theseContinue Reading

In: Artificial Intelligence

Amazon SageMaker Inference has been a popular tool for deploying advanced machine learning (ML) and generative AI models at scale. As AI applications become increasingly complex, customers want to deploy multiple models in a coordinated group that collectively process inference requests for an application. In addition, with the evolution ofContinue Reading

In: Artificial Intelligence

Modern generative AI model providers require unprecedented computational scale, with pre-training often involving thousands of accelerators running continuously for days, and sometimes months. Foundation Models (FMs) demand distributed training clusters — coordinated groups of accelerated compute instances, using frameworks like PyTorch — to parallelize workloads across hundreds of accelerators (likeContinue Reading

In: Artificial Intelligence

Large language models (LLMs) have revolutionized the way we interact with technology, but their widespread adoption has been blocked by high inference latency, limited throughput, and high costs associated with text generation. These inefficiencies are particularly pronounced during high-demand events like Amazon Prime Day, where systems like Rufus—the Amazon AI-poweredContinue Reading

In: Artificial Intelligence

PixArt-Sigma is a diffusion transformer model that is capable of image generation at 4k resolution. This model shows significant improvements over previous generation PixArt models like Pixart-Alpha and other diffusion models through dataset and architectural improvements. AWS Trainium and AWS Inferentia are purpose-built AI chips to accelerate machine learning (ML)Continue Reading

In: Artificial Intelligence

PixArt-Sigma is a diffusion transformer model that is capable of image generation at 4k resolution. This model shows significant improvements over previous generation PixArt models like Pixart-Alpha and other diffusion models through dataset and architectural improvements. AWS Trainium and AWS Inferentia are purpose-built AI chips to accelerate machine learning (ML)Continue Reading

In: Artificial Intelligence

Headquartered in São Paulo, Brazil, iFood is a national private company and the leader in food-tech in Latin America, processing millions of orders monthly. iFood has stood out for its strategy of incorporating cutting-edge technology into its operations. With the support of AWS, iFood has developed a robust machine learningContinue Reading