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Applying multimodal biological foundation models across therapeutics and patient care

Favorite 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

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Shared by AWS Machine Learning April 23, 2026

Company-wise memory in Amazon Bedrock with Amazon Neptune and Mem0

Favorite 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

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Shared by AWS Machine Learning April 22, 2026

Amazon SageMaker AI now supports optimized generative AI inference recommendations

Favorite 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

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Shared by AWS Machine Learning April 22, 2026

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

Favorite 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

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Shared by AWS Machine Learning April 22, 2026