CEREBRIU is using Oracle #cloud with NVIDIA GPUs to develop a groundbreaking #AI-based tool that accelerates the analysis of MRI brain scans, saving time on diagnoses and lives. 🧠 Learn more: https://lnkd.in/dgeFJGiY
CEREBRIU uses Oracle cloud for MRI brain scans
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🚀 SandboxAQ launches SAIR, the largest open dataset of protein-ligand structures with binding affinities, powered by NVIDIA DGX Cloud for breakthrough AI drug discovery. Access now: https://bit.ly/46r1UCu
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🚀 SandboxAQ launches SAIR, the largest open dataset of protein-ligand structures with binding affinities, powered by NVIDIA DGX Cloud for breakthrough AI drug discovery. Access now: https://bit.ly/4k2LmEk
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🚀 SandboxAQ launches SAIR, the largest open dataset of protein-ligand structures with binding affinities, powered by NVIDIA DGX Cloud for breakthrough AI drug discovery. Access now: https://bit.ly/3Glc9hc
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Curious how to bring AI/ML into digital pathology workflows? We just dropped the recording of our recent webinar: “Integrating AI and Data Science in Digital Pathology”—and it's packed with practical strategies and live demos using real-world pathology datasets. Watch the webinar to learn how to: ✅ Integrate AI models (including MONAI zoo + custom models) into HistomicsTK ✅ Improve model training with high-quality annotations ✅ Customize workflows with tools like Guided Labeling ✅ Deploy across laptops, cloud, and HPC ✅ Use real pathology data for hands-on insight https://lnkd.in/gecCcY4A
Integrating AI and Data Science in Digital Pathology
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Singapore unveils Southeast Asia’s first hybrid quantum AI testbed at BDx’s SIN1 data centre, blending quantum computing with AI to boost innovation.
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🔦 Project highlight: ENERGETIC 🔦 🔋 The ENERGETIC project aims to develop the next generation BMS for optimising battery systems' utilisation in the first (transport) and the second life (stationary) in a path towards more reliable, powerful and safer operations. 📊 The project contributes to the field of translational enhanced sensing technologies, exploiting multiple Artificial Intelligence models, supported by Edge and Cloud computing. 🤖 ENERGETIC’s vision not only encompasses monitoring and prognosis of the remaining useful life of a Li-ion battery with a digital twin, but also encompasses diagnosis by scrutinising the reasons for degradation through investigating the explainable AI models. ➡️ Find out more about ENERGETIC and the other #BATT4EU projects here: https://lnkd.in/eDiYQy6u
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Ubitus K.K. joins Yonsei University and Trident Zoetic to launch Asia’s first quantum-GPU hybrid platform, advancing AI, biotech, and materials research - https://lnkd.in/gZnAWjPC “This partnership reflects our commitment to next-generation infrastructure,” said Wesley Kuo, CEO of Ubitus. #Biotech #MaterialsScience #GPUaaS #TechIntelPro
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Shakti Clusters offer robust performance for deep learning, simulations, and analytics, leveraging NVIDIA H100 & L40S GPUs. Our Kubernetes + SLURM orchestration ensures cost-efficient, auto-scalable resource management, optimizing your AI/ML workloads. Learn more: https://shakticloud.ai/
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From LLM training to real-time inference, GPU data centers are accelerating the AI revolution. Explore how the GPU ecosystem, from hardware like NVIDIA GB200 to stacks supporting RAG and multimodal AI, is transforming the way we build, scale, and deploy intelligent systems. #Neocloud #AIInfrastructure #GPUComputing #LLM #DataCenter
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SAIR sets a new bar for scientific data infrastructure—5 million protein-ligand structures, labeled and ready for AI. Built with our Large Quantitative Models. Available now. https://lnkd.in/eBEUQEV4
Today we’re releasing SAIR, the Structurally Augmented IC50 Repository. SAIR is the Largest Publicly Available Binding Affinity Dataset with Cofolded 3D Structures. It includes more than 5 million protein-ligand structures, generated using our Large Quantitative Models and labeled with binding affinity data. By providing this unprecedented scale of structure-activity data, we aim to enable researchers to train and evaluate new AI models for drug discovery, bridging the historical gap between molecular structures and drug potency prediction. The SAIR dataset was created using the NVIDIA DGX Cloud and is now publicly available on the Google Cloud Platform. Access and build with SAIR today! 📄 Read the Press Release: https://lnkd.in/dPPJv4W8 📩 Learn More and Download the Dataset at https://lnkd.in/d4f9MdJB #DrugDiscovery #LQMs #SAIR #AIforScience #SandboxAQ
Access and build with SAIR today!
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