A Technology Broker and Management Company Specializing in KM Systems
Favorite Any team working with spoken audio hits the same wall with generic speech-to-text. Think contact-center calls, all-hands meetings, podcasts, depositions, and broadcast media. These workloads need two things that standard transcription gets wrong. First, timestamps land at the utterance level, off by several seconds. Second, there’s no reliable answer
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Shared by AWS Machine Learning September 25, 2026
Favorite With Amazon SageMaker HyperPod and Qumulo, you can place training compute in one AWS Region and keep your dataset in another. Training large AI models requires massive GPU capacity, but your ideal compute resources and your training data don’t always reside in the same AWS Region. Accessing data across
Read More Shared by AWS Machine Learning September 25, 2026
Favorite This post was written with contributions from Datacor’s TrackAbout engineering and product teams. For gas and welding distributors, rental billing on assets such as cylinders and bulk tanks is a significant share of total revenue. Yet the data needed to manage those assets was often locked in disconnected systems,
Read More Shared by AWS Machine Learning September 25, 2026
Favorite With voice cloning, you can generate new speech in a target speaker’s voice from a short reference recording, without retraining a model. You can now deploy the publicly available Qwen3-TTS-12Hz-1.7B-Base text-to-speech model from Amazon SageMaker JumpStart to a fully managed, real-time inference endpoint. Voice cloning reproduces the vocal identity
Read More Shared by AWS Machine Learning September 25, 2026
Favorite Executives need to make data-driven decisions during live business reviews, where accuracy and speed matter. A conversational agentic AI assistant can meet this need by answering data questions instantly. But the stakes are high: a wrong number or a slow response in front of leadership carries immediate professional consequences,
Read More Shared by AWS Machine Learning September 25, 2026
Favorite Reinforcement learning (RL) post-training is becoming a standard step in building capable language model agents. Models learn to reason and act across sequences of steps by generating trajectories, receiving rewards, and updating their policy based on outcomes. Running this at scale, across multiple nodes with hundreds of GPU-hours of
Read More Shared by AWS Machine Learning September 25, 2026
Favorite AI coding agents have become a core part of how developers write, debug, and refactor software. Open weight models on Amazon Bedrock now make these agents practical to run privately and cost-effectively. But most options require you to send your proprietary data to a third-party API, lock you into
Read More Shared by AWS Machine Learning September 24, 2026
Favorite With video intelligence powered by agentic AI, you can ask natural language questions about uploaded videos and get answers within seconds. Organizations across media, security, insurance, and professional services are generating more video than their teams can review. Meeting recordings accumulate in shared drives, and security cameras capture weeks
Read More Shared by AWS Machine Learning September 24, 2026
Favorite This post is co-written with Mauro Rallo and Patrick van der Plas from HEMA. When engineers at HEMA needed an answer, they went portal-hopping, navigating disconnected wikis, service catalogs, and IT portals to find it. To turn that friction into instant answers, the 100-year-old Dutch retailer built a knowledge
Read More Shared by AWS Machine Learning September 24, 2026
Favorite This guest post is co-written by Angela Mapes and Adam Walker of Aderant. In this post, we share how Aderant, a global provider of business management software for the legal industry, built an intelligent ticket triage system using Amazon Nova Lite through Amazon Bedrock. Aderant’s solution automates much of
Read More Shared by AWS Machine Learning September 24, 2026