NEWS IN BRIEF: AI/ML FRESH UPDATES

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Automating SageMaker AI endpoints scaling using AWS CDK

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...

Bayer Crop Science's Decision Engine on Amazon Bedrock AgentCore: Powered by AWS Unified Operations

Bayer Crop Science uses machine learning models to analyze data from genomics, field trials, imagery, and environmental conditions for plant breeding. To manage and make repeatable and governable these ML model configurations, Bayer developed the Connected Decision Engine (CDE). As the usage increased, understanding the results became a challenge, leading to the creation of the Agentic Decision...

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NVIDIA founder and CEO Jensen Huang recently visited Astana, Kazakhstan, where he discussed the country's push to build a strong ecosystem for artificial intelligence (AI). Kazakhstan's goal is to create AI that reflects its language and culture, utilizing its abundant energy resources to support homegrown AI and transforming energy into intelligence for export. The conversation also touched on...

NVIDIA Unveils Tools for Training, Evaluating, and Deploying World Models with Cosmos

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...

Use Kokoro TTS on Amazon SageMaker for Real-Time Speech Output from AI Agents

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...

IskayPet's Integration of Corporate Knowledge with Amazon Bedrock: Unified Management of Knowledge Bases

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...

Deploying AI in HIPAA-Compliant Way with Amazon QuickSight

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, ...

Streamline Your Training with Amazon SageMaker APIs

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.

Implementing Random Forest and Extra Trees Regression with C#: A Comparative Study

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...

Automatically Optimizing TTS Model Scaling in Amazon SageMaker using AI

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...

Live Updates from NVIDIA CEO Jensen Huang at GTC Berlin 2026

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.

Master AWS Trainium Training with torchtitan

TorchNeuron on AWS Trainium integrates seamlessly with torchtitan, offering flexibility in pre-training and customization. Qwen3 is trained three ways on a single trn2. 48xlarge, showcasing the use of Transformers v5 and Neuron Kernel Interface for model optimization.

Enhancing Network Security with AWS PrivateLink

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.