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.
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.
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.
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.
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.
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.
Amazon SageMaker JumpStart offers a curated catalog of AI models, templates, and notebooks, streamlining ML model selection to deployment. Leading providers like Alibaba, NVIDIA, and Google contribute diverse models for model discovery, deployment, and customization.
Deepgram leverages AWS AI chips to enhance efficiency, processing 11-70% more audio per dollar for customers. Deepgram and AWS collaborate to optimize Nova-3 on Trainium2, improving inference for speech-to-text models.
TwelveLabs releases Pegasus 1.5 on Amazon Bedrock, a video language model transforming video into structured metadata. Pegasus 1.5 offers time-based metadata, multimodal prompting, and on-the-fly processing, enhancing video analysis capabilities.
Amazon Bedrock now supports structured outputs for all Anthropic Claude models, ensuring schema-compliant JSON responses. This eliminates the need for custom parsing and post-processing, making tasks like data extraction and contract analysis more efficient and reliable.
German Chancellor Friedrich Merz and NVIDIA CEO Jensen Huang discuss Germany's AI roadmap at Kraftwerk, emphasizing AI applications in manufacturing and automotive. Germany aims to merge engineering expertise with AI technology, collaborating with NVIDIA to advance industrial AI models and establish a cutting-edge ecosystem in Europe.
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.
vLLM introduces push-based NIXL connector for efficient KV transfer, reducing TTFT and improving TPOT in LLM inference. Benchmark shows up to 3x better TTFT and 30% better TPOT with push mode on Amazon EC2 P5en instances using Qwen3-32B model.
NVIDIA RTX Spark laptops, with powerful AI capabilities, now available for $2,399 from top PC makers. Jensen Huang surprises fans at launch events in Berlin, sparking excitement worldwide.