Scientists use generative AI to answer complex questions in physics

When water freezes, it transitions from a liquid phase to a solid phase, resulting in a drastic change in properties like density and volume. Phase transitions in water are so common most of us probably don’t even think about them, but phase transitions in novel materials or complex physical systems are an important area of…

Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models

Vision Foundation Models (VFMs) pretrained on massive datasets exhibit impressive performance on various downstream tasks, especially with limited labeled target data. However, due to their high inference compute cost, these models cannot be deployed for many real-world applications. Motivated by this, we ask the following important question, “How can we leverage the knowledge from a…

Animal brain inspired AI game changer for autonomous robots

A team of researchers has developed a drone that flies autonomously using neuromorphic image processing and control based on the workings of animal brains. Animal brains use less data and energy compared to current deep neural networks running on GPUs (graphic chips). Neuromorphic processors are therefore very suitable for small drones because they don’t need…

Build a serverless exam generator application from your own lecture content using Amazon Bedrock

Crafting new questions for exams and quizzes can be tedious and time-consuming for educators. The time required varies based on factors like subject matter, question types, experience level, and class level. Multiple-choice questions require substantial time to generate quality distractors and ensure a single unambiguous answer, and composing effective true-false questions demands careful effort to…

Accelerate NLP inference with ONNX Runtime on AWS Graviton processors

ONNX is an open source machine learning (ML) framework that provides interoperability across a wide range of frameworks, operating systems, and hardware platforms. ONNX Runtime is the runtime engine used for model inference and training with ONNX. AWS Graviton3 processors are optimized for ML workloads, including support for bfloat16, Scalable Vector Extension (SVE), and Matrix…

KV-Runahead: Scalable Causal LLM Inference by Parallel Key-Value Cache Generation

Large Language Model or LLM inference has two phases, the prompt (or prefill) phase to output the first token and the extension (or decoding) phase to the generate subsequent tokens. In this work, we propose an efficient parallelization scheme, KV-Runahead to accelerate the prompt phase. The key observation is that the extension phase generates tokens…

Learn how Amazon Ads created a generative AI-powered image generation capability using Amazon SageMaker

Amazon Ads helps advertisers and brands achieve their business goals by developing innovative solutions that reach millions of Amazon customers at every stage of their journey. At Amazon Ads, we believe that what makes advertising effective is delivering relevant ads in the right context and at the right moment within the consumer buying journey. With that…

pfl-research: Simulation Framework for Accelerating Research in Private Federated Learning

Federated Learning (FL) is an emerging ML training paradigm where clients own their data and collaborate to train a global model without revealing any data to the server and other participants. Researchers commonly perform experiments in a simulation environment to quickly iterate on ideas. However, existing open-source tools do not offer the efficiency required to…

RAG architecture with Voyage AI embedding models on Amazon SageMaker JumpStart and Anthropic Claude 3 models

This post is a guest post co-written with Tengyu Ma and Wen Phan from Voyage AI. Organizations today have access to vast amounts of data, much of it proprietary, which holds the potential to unlock valuable insights when used effectively in generative artificial intelligence (AI) applications. Retrieval Augmented Generation (RAG) is a powerful technique designed…