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Swiss Re & Palantir: Scaling Data Operations with Foundry

Swiss Re & Palantir Scaling Data Operations with Foundry Editor’s note: This guest post is authored by our customer, Swiss Re. Authors Lukasz Lewandowski, Marco Lotz, and Jarek Sobanski lead the core technical team responsible for the implementation of Palantir Foundry at the Swiss reinsurer. They have been managing overall platform operations, core architectural principles, site reliability, …

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Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker

As generative AI models advance in creating multimedia content, the difference between good and great output often lies in the details that only human feedback can capture. Audio and video segmentation provides a structured way to gather this detailed feedback, allowing models to learn through reinforcement learning from human feedback (RLHF) and supervised fine-tuning (SFT). …

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Don’t let resource exhaustion leave your users hanging: A guide to handling 429 errors

Large language models (LLMs) give developers immense power and scalability, but managing resource consumption is key to delivering a smooth user experience. LLMs demand significant computational resources, which means it’s essential to anticipate and handle potential resource exhaustion. If not, you might encounter 429 “resource exhaustion” errors, which can disrupt how users interact with your …

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Unify structured data in Amazon Aurora and unstructured data in Amazon S3 for insights using Amazon Q

In today’s data-intensive business landscape, organizations face the challenge of extracting valuable insights from diverse data sources scattered across their infrastructure. Whether it’s structured data in databases or unstructured content in document repositories, enterprises often struggle to efficiently query and use this wealth of information. In this post, we explore how you can use Amazon …

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Announcing new updates to Cloud Translation AI, now covering 189 languages

Your next big customer doesn’t speak your language. In fact, 40% of global consumers won’t even consider buying from websites not in their native tongue. With 51.6% of internet users speaking languages other than English, you’re potentially missing half your market.  Until now, enterprises faced an impossible choice in addressing translation use cases. They had …

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Racing into the future: How AWS DeepRacer fueled my AI and ML journey

In 2018, I sat in the audience at AWS re:Invent as Andy Jassy announced AWS DeepRacer—a fully autonomous 1/18th scale race car driven by reinforcement learning. At the time, I knew little about AI or machine learning (ML). As an engineer transitioning from legacy networks to cloud technologies, I had never considered myself a developer. …

Effortless robot movements

Humans and animals move with remarkable economy without consciously thinking about it by utilizing the natural oscillation patterns of their bodies. A new tool can now utilize this knowledge for the first time to make robots move more efficiently.

Duo-LLM: A Framework for Studying Adaptive Computation in Large Language Models

This paper was accepted at the Efficient Natural Language and Speech Processing (ENLSP) Workshop at NeurIPS 2024. Large Language Models (LLMs) typically generate outputs token by token using a fixed compute budget, leading to inefficient resource utilization. To address this shortcoming, recent advancements in mixture of expert (MoE) models, speculative decoding, and early exit strategies …

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Build cost-effective RAG applications with Binary Embeddings in Amazon Titan Text Embeddings V2, Amazon OpenSearch Serverless, and Amazon Bedrock Knowledge Bases

Today, we are happy to announce the availability of Binary Embeddings for Amazon Titan Text Embeddings V2 in Amazon Bedrock Knowledge Bases and Amazon OpenSearch Serverless. With support for binary embedding in Amazon Bedrock and a binary vector store in OpenSearch Serverless, you can use binary embeddings and binary vector store to build Retrieval Augmented …