Granite 3.0. IBM’s third-generation Granite flagship language models can outperform or match similarly sized models from leading model providers on many academic and industry benchmarks, showcasing strong performance, transparency and safety. The IBM Granite 1B and 3B models are the first mixture of experts (MoE) Granite models from IBM designed for low latency usage. The models are trained on over 10 trillion tokens of data, the Granite MoE models are ideal for deployment in on-device applications or situations requiring instantaneous inference. We’ve just published a step-by-step guide on How to deploy Granite MOE 1B and 3B in the Cloud? ✔Read more here: https://lnkd.in/gTFAfaWM #Aimodels #GraniteMoE #Opensource #Cloud
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Thrilled to announce that our first blog of the IBM Granite series is now live on NodeShift Blog! This post covers "How to Deploy Granite MOE 1B and 3B Models in the Cloud" with hands-on instructions and insights. 🛠️ The results we achieved running these models on the NodeShift GPU Virtual Machine have been nothing short of extraordinary! Read the full blog here: https://lnkd.in/gg5ngtNe Stay tuned – next, we’ll dive into Granite Dense 2B and 8B. More power, more insights, and more impact to come. 👀 #Granite3 #Aimodels #Opensource
Granite 3.0. IBM’s third-generation Granite flagship language models can outperform or match similarly sized models from leading model providers on many academic and industry benchmarks, showcasing strong performance, transparency and safety. The IBM Granite 1B and 3B models are the first mixture of experts (MoE) Granite models from IBM designed for low latency usage. The models are trained on over 10 trillion tokens of data, the Granite MoE models are ideal for deployment in on-device applications or situations requiring instantaneous inference. We’ve just published a step-by-step guide on How to deploy Granite MOE 1B and 3B in the Cloud? ✔Read more here: https://lnkd.in/gTFAfaWM #Aimodels #GraniteMoE #Opensource #Cloud
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There is a reason the interface on all of the VSP storage interfaces look the same, because it is the same. Midrange, mainframe, mission critical high, end, all running the same software. This experience is now being brought to software defined storage and file workloads through #VSPOne simplifying end to end administration and integration of your platforms wherever and whatever they are.
Excited to announce availability of Hitachi Virtual Storage Platform One for SDS Block, SDS Cloud and File. #VSPOne redefines #HybridCloud data management and availability with ONE unified data ecosystem across block and file, simplifying infrastructure for mission critical apps. Read the news: https://lnkd.in/ghwcJ-FZ
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Memory Machine Cloud (MMC)'s team had an amazing time at this year's Nextflow Summit Boston 2024, pushing the boundaries with our exciting new product lineups! Check out my talk on unleashing the potential of Memory Machine Cloud Snapshot Engine here - (https://lnkd.in/eRxCh_z4). Highlights: 1️⃣ JUICEFLOW (MMC's high-performance JuiceFS integration for Nextflow) * Enables researchers to achieve cost savings through reduced CPU-hours and improved workflow wall-time. 2️⃣ MMC SNAPSHOT ENGINE (MMC's standalone checkpoint & restore for AWS Batch) * AWS Batch users can add MMC's standalone snapshot engine (AMI) to their compute environments and gain spot-insurance against reclaims. 3️⃣ MMC AIR (MMC's easy-to-use, low-cost, cloud-based Omics-as-a-Service) * Flat fee per run with predictable wall clock time. * Users can leverage our infrastructure or deploy Air in their own infrastructure. 4️⃣ MMC MANAGED SERVICES (Proactively monitored, secure cloud infrastructure with support) * Deploy AWS account -> IAM -> VPC -> Networking -> MMC Opcenter in minutes. * Users get special pricing lower than listed spot prices and peace of mind without the need for Cloud IT expertise. Book a meeting to know more here - (https://lnkd.in/eas_Ukzg). Join us on this journey to simplify cloud computing and achieve more with less effort! #NextflowSummit2024 #CloudComputing #MemVerge #MemoryMachineCloud #Juiceflow #SnapshotEngine #MMC #Nextflow #AWS #cloud303
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We know you've seen our posts, but what does it mean that Wilmac Tech's Continuity Replay Cloud integrates with Five9? It means opportunities, including: 📊Seamless data extraction, conversion, & ingestion ☎️Decommission legacy platforms 💡Complete control with legacy and production data in one place https://lnkd.in/ebhWVbE3
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Unlock the Power of Historical Data with FusionReactor Cloud! 🚀 Stay ahead of application performance issues with FusionReactor Cloud’s robust historical data tools. Whether you're troubleshooting or optimizing, you can easily access up to 13 months of metric data and 30 days of trace and log data. 🔍 Key Benefits: - Visualize Performance Trends: Diagnose both live and historical issues. - Anomaly Detection: Set precise thresholds to catch real anomalies. - Comprehensive Insights: Use detailed metrics, traces, and logs to ensure smooth operations. #Observability #Cloud #DataAnalysis #FusionReactor #APM #TechInnovation https://lnkd.in/eASQft6U
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CIOs are facing challenges navigating the AI era, balancing experimentation, cost control, and data security. Private cloud solutions are gaining traction due to concerns over cost uncertainty and data leaks, with a hybrid approach emerging as a long-term strategy. VMware is best in class to create your secure private AI strategy. Here's why: 1. A single private cloud on-premises, co-location or hyperscaler, choice of hardware, LLM and Container platforms 2. AI-enabled private cloud can be located directly next to your data ensuring your IP never leaves your network or private cloud tenant 3. Zero latency high-speed storage which scales horizontally as you train and inference your on-prem LLM’s with your confidential IP 4. Native Data Services to deliver Postgres, MySQL, and Alloy DB Vector Databases for Modern Apps and AI/ML use cases 5. API-driven with Kubernetes, or Aria Automation to deliver a frictionless developer experience for all applications As AI reshapes cloud strategies, enterprises must assess the optimal mix of public and private clouds to meet evolving needs while ensuring data integrity and cost efficiency. #VCF a fully automated Private Cloud. #VMware Private AI. https://lnkd.in/evA8jZk4
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Why Dual Execution? MotherDuck’s unique architecture takes advantage of the untapped processing power at your fingertips. Take full advantage of advances in hardware and network speeds to reclaim unused compute on users’ local machines. Workloads shouldn't default to a time-consuming, expensive round trip to the cloud for everything. Support local analytics - save the cloud for added scale: https://lnkd.in/e6zj-NaD
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The performance and optimization of your EKS clusters and Auto Scaling Groups is easier to see than ever. Visualize how Copilot is managing and optimizing your workloads in real time. Easily track your savings with all essential information consolidated into one unified dashboard. No more chasing down individual resources — get everything you need in one place. Read more here: #eks #asg #aws https://lnkd.in/g7k-SXk3
New EKS Cluster and ASG Dashboards
https://www.nops.io
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As Chris Mellor has written about in his Block and Files (B&F) Storage news ticker on June 7th 2024: "AFM also serves as a caching layer that can deliver higher performance access to data deployed as a high-performance tier on top of less performant storage tiers. AFM can connect to on-prem, cloud, and edge storage deployments. A Storage Scale file system with AFM provides a consistent cache that provides a single source of truth with no stale data copies supporting multiple use cases." By enabling IBM Storage Scale v5.2.0 multi-site replication (by using AFM), you can move data across multiple object storage providers. This feature provides high availability, fault tolerance, reduced latency, parallel access, and migration between clouds. Also, you can move datasets within regions for AI and hybrid cloud environments, which allow you to access data on a cheaper storage and where compute is available. Jochen Zeller from IBM partner SVA in Wiesbaden, Germany has presented this picture about AFM at the Scale User Group meeting in 2022. For me it gives a very good understanding of the complex topic.
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