Arnold Ness, P.Eng, MBA’s Post

Hello Dear Network, I share with you this Computerworld article about smaller language models for enterprise applications, an entry point into the future of GenAI. We, at #redhat, noticed that Customers want to leverage the power of Gen AI in their enterprise IT environments, but are struggling with the cost of procuring large proprietary models and model services, the complexity of aligning these models to their enterprise data and use cases, and they need the flexibility to deploy and manage these models across a hybrid cloud environment. RHEL AI offers customers the confidence to begin their AI journey with an easy point of entry delivered on our trusted, comprehensive, consistent platform

IBM has launched Granite 3.0, the most advanced family of AI models built for business! These high-performance AI models are game-changers for enterprises looking to personalize and transform customer and associate experiences using Hybrid Cloud and AI solutions. Key highlights: New Granite 3.0 Models: 8B & 2B models, outperforming similar-sized models with flexible Apache 2.0 licensing. Granite Guardian: Most comprehensive AI guardrails, ensuring safe and trustworthy AI. Mixture-of-Experts: Extremely efficient, low-latency AI for edge computing and CPU deployments. Time Series Excellence: State-of-the-art zero/few-shot forecasting, outperforming models 10x larger. Plus, Granite 3.0 will power IBM Consulting Advantage platform, helping IBM’s 160,000 consultants deliver AI-driven solutions faster! #IBMAI #HybridCloud #AIForBusiness #ConsultingAdvantage #AITransformation

Enterprise AI news from AWS re:Invent: Open Platform for Enterprise AI (OPEA) is now available on AWS Marketplace: https://lnkd.in/gfBr3kA5 ✨ What is Open Platform for Enterprise AI (OPEA)? OPEA is a Linux Foundation project that enables enterprises to develop and deploy GenAI solutions powered by an open ecosystem that delivers on security, safety, scalability, cost efficiency, and agility. The OPEA platform includes: 1️⃣ Detailed framework of composable building blocks for state-of-the-art generative AI systems including LLMs, data stores, and prompt engines 2️⃣ Architectural blueprints of retrieval-augmented generative AI component stack structure and end-to-end workflows 3️⃣ A four-step assessment for grading generative AI systems around performance, features, trustworthiness and enterprise-grade readiness Special thanks to Arun Gupta, Victoria Kouyoumjian, Mike Mariani, Dina Habib OMara. To learn more on OPEA on AWS Marketplace: https://lnkd.in/gfBr3kA5 #OpenSource #EnterpriseAI #LinuxFoundation #IntelAI #AWSreinvent #GenAI #OPEA

Paired with Azure Policy, this update enables organisations to enforce governance at scale, ensuring compliance, security, and data residency, no matter where your AI models are deployed.

#AzureopenAi service a new model of deployment for models: Global provisioned managed, what is it ❓ ✅ Access to the Latest Models Everywhere ✅ Simplified Deployment and Management ✅ Data Residency and Compliance Flexibility ✅ Transparent and Flexible Pricing ✅ Dual Deployment Options for Greater Flexibility take a look at this link for deepdive : 🔗 https://lnkd.in/gqXN_qaS You want to challenges and understood the difference between each type ? 🔗 https://lnkd.in/g-rt6GXs And don't forget a good ÃI product is to begin with a good architecture for a landing zone with AI Take a look at this repo from Frédéric A. https://lnkd.in/gs6t4MHw https://lnkd.in/gqXN_qaS #Microsoftfrance #models #ai #azure #genai #provisionned

Document classification and extraction of information gets easier with the growth of the WatsonX AI solution.

Integrating generative AI into your existing IT setup presents a complex challenge. Legacy systems are not designed to handle the advanced requirements of AI, creating significant compatibility issues. These systems often lack the computational power and scalability needed to run AI processes effectively, resulting in performance bottlenecks. Conducting a thorough assessment of your current IT architecture is essential to identify integration issues and computational limitations. Developing custom APIs, webhooks, data warehousing, and data pipelines can bridge the gap between your old systems and new AI technologies, ensuring smoother data integration and streamlined information flow. #cloud #ai #firney

it's a fentastic transformation and modernization the way ECM FileNet product running ahead in automation and digitalization...

Microsoft Azure 's new Phi models are boosting speed and computational efficiency. 📈 Bruce McMahon, CallMiner's Chief Product Officer, shares the impact of Phi models on CallMiner’s GenAI architecture. "As we evaluate different models, we’ve continued to prioritize accuracy, speed, and security. The small size of Phi models makes them incredibly fast, and fine tuning has allowed us to tailor to the specific use cases that matter most to our customers at high accuracy and across multiple languages." Read more in the blog from Eric Boyd, Corporate Vice President, Azure AI Platform, Microsoft. https://lnkd.in/ejBv7K7s