Favorite This post is a collaboration between AWS, NVIDIA and Heidi. Automatic speech recognition (ASR), often called speech-to-text (STT) is becoming increasingly critical across industries like healthcare, customer service, and media production. While pre-trained models offer strong capabilities for general speech, fine-tuning for specific domains and use cases can enhance
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Shared by AWS Machine Learning March 14, 2026
Favorite This post shows you how to build a scalable multimodal video search system that enables natural language search across large video datasets using Amazon Nova models and Amazon OpenSearch Service. You will learn how to move beyond manual tagging and keyword-based searches to enable semantic search that captures the
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Shared by AWS Machine Learning March 13, 2026
Favorite Deploying AI agents safely in regulated industries is challenging. Without proper boundaries, agents that access sensitive data or execute transactions can pose significant security risks. Unlike traditional software, an AI agent chooses actions to achieve a goal by invoking tools, accessing data, and adapting its reasoning using data from
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Shared by AWS Machine Learning March 13, 2026
Favorite As organizations scale their generative AI workloads on Amazon Bedrock, operational visibility into inference performance and resource consumption becomes critical. Teams running latency-sensitive applications must understand how quickly models begin generating responses. Teams managing high-throughput workloads must understand how their requests consume quota so they can avoid unexpected throttling.
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Shared by AWS Machine Learning March 13, 2026
Favorite EAGLE is the state-of-the-art method for speculative decoding in large language model (LLM) inference, but its autoregressive drafting creates a hidden bottleneck: the more tokens that you speculate, the more sequential forward passes the drafter needs. Eventually those overhead eats into your gains. P-EAGLE removes this ceiling by generating
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Shared by AWS Machine Learning March 13, 2026
Favorite A new Google AI initiative aims to improve heart health outcomes for people living in remote Australian communities. View Original Source (blog.google/technology/ai/) Here.
Favorite Agentic AI isn’t a feature you turn on. It’s a shift in how work is defined, who does it, and how decisions get made. Most enterprises learn this the hard way. They launch pilots that stall the moment they hit real processes, systems, and governance. The pattern repeats: vague
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Shared by AWS Machine Learning March 12, 2026
Favorite Members Newsletter – March 2026 Dear OSI supporters, Every March, Open Education Week invites us to reflect on something that will feel familiar to everyone in this community: the idea that knowledge is most powerful when it is freely accessible, adaptable, and shared. It is a principle that open
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Shared by voicesofopensource March 11, 2026
Favorite This post is cowritten by David Stewart and Matthew Persons from Oumi. Fine-tuning open source large language models (LLMs) often stalls between experimentation and production. Training configurations, artifact management, and scalable deployment each require different tools, creating friction when moving from rapid experimentation to secure, enterprise-grade environments. In this
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Shared by AWS Machine Learning March 11, 2026
Favorite The adoption and implementation of generative AI inference has increased with organizations building more operational workloads that use AI capabilities in production at scale. To help customers achieve the scale of their generative AI applications, Amazon Bedrock offers cross-Region inference (CRIS) profiles. CRIS is a powerful feature that organizations
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Shared by AWS Machine Learning March 10, 2026
Shared by AWS Machine Learning March 14, 2026
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