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Healthcare and life sciences decision making increasingly relies on multimodal data to diagnose diseases, prescribe medicine and predict treatment outcomes, develop and optimize innovative therapies accurately. Traditional approaches analyze fragmented data, such as ‘omics for drug discovery, medical images for diagnostics, clinical trial reports for validation, and electronic health records (EHR) for patient treatment. As …

Applying multimodal biological foundation models across therapeutics and patient care Read More »

Learn how Google’s TPUs power increasingly demanding AI workloads with this new video. ​ 

Google has been a proud part of Austria’s landscape for years, and today, we’re announcing our first data center in Kronstorf, generating 100 direct jobs. This facility … ​ 

Many organizations are archiving large media libraries, analyzing contact center recordings, preparing training data for AI, or processing on-demand video for subtitles. When data volumes grow significantly, managed automatic speech recognition (ASR) service costs can quickly become the primary constraint on scalability. To address this cost-scalability challenge, we use the NVIDIA Parakeet-TDT-0.6B-v3 model, deployed through …

Cost-effective multilingual audio transcription at scale with Parakeet-TDT and AWS Batch Read More »

Organizations are racing to deploy generative AI models into production to power intelligent assistants, code generation tools, content engines, and customer-facing applications. But deploying these models to production remains a weeks-long process of navigating GPU configurations, optimization techniques, and manual benchmarking, delaying the value these models are built to deliver. Today, Amazon SageMaker AI  supports …

Amazon SageMaker AI now supports optimized generative AI inference recommendations Read More »

Getting an agent running has always meant solving a long list of infrastructure problems before you can test whether the agent itself is any good. You wire up frameworks, storage, authentication, and deployment pipelines, and by the time your agent handles its first real task, you’ve spent days on infrastructure instead of agent logic. We …

Get to your first working agent in minutes: Announcing new features in Amazon Bedrock AgentCore Read More »

This post is cowritten by Shawn Tsai from TrendMicro. Delivering relevant, context-aware responses is important for customer satisfaction. For enterprise-grade AI chatbots, understanding not only the current query but also the organizational context behind it is key. Company-wise memory in Amazon Bedrock, powered by Amazon Neptune and Mem0, provides AI agents with persistent, company-specific context—enabling …

Company-wise memory in Amazon Bedrock with Amazon Neptune and Mem0 Read More »

The eighth generation of Google’s TPU includes two specialized chips that will power the future of AI. ​ 

Today, we’re excited to announce Claude Cowork in Amazon Bedrock. You can now run Cowork and Claude Code Desktop through Amazon Bedrock, directly or using an LLM gateway. From startups to global enterprises across every industry, organizations build with Claude Code in Amazon Bedrock to boost developer productivity and accelerate delivery. With Amazon Bedrock you …

From developer desks to the whole organization: Running Claude Cowork in Amazon Bedrock Read More »

Production machine learning (ML) teams struggle to trace the full lineage of a model through the data and the code that trained it, the exact dataset version it consumed, and the experiment metrics that justified its deployment. Without this traceability, questions like “which data trained the model currently in production?” or “can we reproduce the …

End-to-end lineage with DVC and Amazon SageMaker AI MLflow apps Read More »