Multi-Turn Reinforcement Learning (MTRL) is a training method used to teach models to complete multi-step tasks with feedback only after the entire sequence. In contrast to fine-tuning, MTRL doesn't rely on a single correct sequence or label. Agents interact with an environment, making decisions, and reporting rewards after each sequence ends. With MTRL, a model can be made proficient in a spec...
Amazon Quick Sight's geospatial maps allow businesses to visualize patterns connected to location through point maps, filled maps, and now, layer maps. With the new point and LineString geometry types from GeoJSON files, users can mark specific locations and trace routes. This post covers dataset and GeoJSON structure, prerequisites, and advanced techniques for creating layer maps in Amazon Qui...
When updating Amazon SageMaker AI real-time endpoint configuration, changing the instance type, instance count, or environment variables through AWS CloudFormation or AWS CDK can result in deployment failure. This is due to SageMaker AI requiring the scalable target to be deregistered before updating the endpoint. However, deregistering the scalable target causes CloudFormation to lose track of...
NVIDIA's Cosmos platform, a leading open models platform, has been expanded with new training tools, simulation checkpoints, and Data Factory blueprints for building world models. Cosmos Data Factory brings together data curation, processing, and synthetic data generation tools, enabling multimodal and multisensory data curation at scale. This includes new features in Cosmos Curator for curatin...
In this text, the author describes their experience using random forest regression, specifically with Extra Trees learners, compared to the standard architecture. The goal is to predict a single numeric value using various regression techniques, with tree-based methods being one category. Random forest regression uses multiple decision trees with different subsets of the data, averaging the res...
Amazon SageMaker AI introduces training session APIs, allowing users to drive GPU-backed sessions from their own Python process. Users can call operations like forwardbackward() and optimstep() to customize their training loops without managing infrastructure, enabling quick iteration and debugging.
This post discusses the use of Artificial Intelligence (AI) in healthcare organizations, focusing on Amazon Quick, a platform that handles Protected Health Information (PHI), a uniquely complex and regulated data type. The post explains the concept of agentic AI, which goes beyond traditional data processing to retrieve data from both unstructured and structured sources, call external systems, ...
IskayPet, a leading pet care company in Iberia with operations in Spain, Portugal, and France, faced a challenge in efficiently answering operational questions across retail, veterinary care, animal care, procurement, and people and onboarding, spread across hundreds of Microsoft SharePoint documents in four languages. The time-consuming process of manually searching and verifying information l...
In this post, the author discusses the challenges of scaling a self-hosted text-to-speech (TTS) endpoint on Amazon SageMaker, particularly when dealing with unexpected traffic spikes. The author notes that the auto scaling policy, which is supposed to prevent overloading, relies on guesses about the target value. The post introduces Kokoro-82M, an 82-million-parameter TTS model, which is deploy...
This article discusses a solution to improve the response time of AI voice agents by closing the gap between generation and synthesis of text-to-speech (TTS) responses. Instead of waiting for the full response to be generated before starting synthesis, each sentence generated by an agent is immediately streamed to a hosted TTS model on Amazon SageMaker AI, allowing audio playback to begin befor...
Rescale's AI-driven platform accelerates innovation in engineering by integrating HPC, modeling, simulation, and AI. They used AI-DLC on AWS to build an intelligent triage agent, reducing operational overhead and speeding up deployment.
U. S. Hunger's mission goes beyond delivering meals, focusing on understanding families' needs. President Rick Whitted's personal experience drives his leadership in using Amazon Quick to explore organizational data efficiently.
AAIF uses small language models for local tasks, reducing costs and latency. Cloud models handle complex requests via Amazon Bedrock.
Connect on-premises data securely to Amazon Quick with AWS PrivateLink, keeping sensitive data off the public internet. Amazon Quick offers AI-powered search, analytics, and automation in a private network environment, ensuring compliance and reducing attack surface.
Tempodrom, near Anhalter Bahnhof since 2001, hosts GTC Berlin with NVIDIA CEO Jensen Huang's keynote on European AI partnerships and AI factory innovations. NVIDIA unveils DSX POD for rapid AI factory deployment, promising efficiency and sustainability gains in data centers.