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...
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.
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 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, ...
AAIF uses small language models for local tasks, reducing costs and latency. Cloud models handle complex requests via Amazon Bedrock.
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.
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.
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.
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.
i14 developed Laplace 3B, a linear attention model, to address the scalability issues of traditional LLMs. Working with AWS, they optimized the model for Trainium2, achieving high training speeds and fixed memory usage for inference.
Establishing cryptographic identity through X.509 PKI is crucial for AI agents accessing sensitive data. Keyfactor EJBCA and AWS services provide secure authentication for multi-agent AI frameworks, preventing unauthorized access and ensuring trust in machine identities.
GPT-OSS-20B reasoning model thinks in English, struggles with multilingual reasoning. Fine-tuning with SFT and GRPO on Amazon SageMaker HyperPod shows promising results.
My C# GBR matches scikit-learn's results, predicting income based on sex, age, city, height, and psychology with high accuracy. The C# implementation allows for detailed prediction explanations, showcasing its effectiveness and transparency in machine learning regression.
Canadian organizations utilizing Amazon Bedrock can now access the latest OpenAI models, including GPT-6, from Canadian AWS Regions with cross-Region inference. The models available in Canada offer a range of capabilities, from strong reasoning to fast, low-cost inference, supporting text and image inputs with a 1-million-token context window.
Researchers at MIT and Boston Children’s Hospital developed E(3)-Pose, a deep learning model that tracks fetal brain motion during MRI scans to improve image quality and accuracy. The model embeds physics principles to enhance brain orientation identification, aiding in early detection of abnormalities in fetal brain development.