Behind the Streams: Three Years Of Live at Netflix. Part 1. By Sergey Fedorov, Chris Pham, Flavio Ribeiro, Chris Newton, and Wei Wei Many great ideas at Netflix begin with a question, and three years ago, we asked one of our boldest yet: if we were to entertain the world through Live — a format almost as old as …
Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. This enhancement builds on the core functionality of Amazon Bedrock Knowledge Bases , which is designed to seamlessly connect foundation models (FMs) with …
Embeddings are a cornerstone of modern semantic search and Retrieval Augmented Generation (RAG) applications. In short, they enable applications to understand and interact with information on a deeper, conceptual level. In this post, we’ll show you how to create and retrieve embeddings with a few lines of Dataflow ML code to enable both of these …
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Vehicle data is critical for original equipment manufacturers (OEMs) to drive continuous product innovation and performance improvements and to support new value-added services. Similarly, the increasing digitalization of vehicle architectures and adoption of software-configurable functions allow OEMs to add new features and capabilities efficiently. Sonatus’s Collector AI and Automator AI products address these two aspects …
In the fast-paced world of AI, it can be challenging to pause and reflect on how we work. Yet this reflection is the cornerstone of continuous improvement. The 2025 DORA survey offers a unique opportunity for you and your team to do just that. By taking just 10-15 minutes to participate before July 18, you …
Read more “Get better at getting better: Take the 2025 DORA survey”
The rapid progress of foundation models and large language models (LLMs) has fueled significantly improvement in the capabilities of machine learning systems that benefit from mutlimodal input data. However, existing multimodal models are predominantly built on top of pre-trained LLMs, which can limit accurate modeling of temporal dependencies across other modalities and thus limit the …
Read more “Visatronic: A Multimodal Decoder-Only Model for Speech Synthesis”
We design and implement AXLearn, a production deep learning system that facilitates scalable and high-performance training of large deep learning models. Compared to other state-of-art deep learning systems, AXLearn has a unique focus on modularity and support for heterogeneous hardware infrastructure. AXLearn’s internal interfaces between software components follow strict encapsulation, allowing different components to be …
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This post provides the theoretical foundation and practical insights needed to navigate the complexities of LLM development on Amazon SageMaker AI, helping organizations make optimal choices for their specific use cases, resource constraints, and business objectives. We also address the three fundamental aspects of LLM development: the core lifecycle stages, the spectrum of fine-tuning methodologies, …
Read more “Advanced fine-tuning methods on Amazon SageMaker AI”
Editor’s note: The Jina AI Reader is a specialized tool that transforms raw web content from URLs or local files into a clean, structured, and LLM-friendly format. In this post, Han Xiao details how Cloud Run empowers Jina AI to build a secure, reliable, and massively scalable web scraping system that remains economically viable. This …
Read more “How Jina AI built its 100-billion-token web grounding system with Cloud Run GPUs”
Ceramics — the humble mix of earth, fire and artistry — have been part of a global conversation for millennia. From Tang Dynasty trade routes to Renaissance palaces, from museum vitrines to high-stakes auction floors, they’ve carried culture across borders, evolving into status symbols, commodities and pieces of contested history. Their value has been shaped …
Read more “A Gaming GPU Helps Crack the Code on a Thousand-Year Cultural Conversation”