Kadir Tas’ Post

The evolution of VAST Data's unified platform marks a significant shift towards a comprehensive AI operating system. Modelled to streamline data management, this innovative system combines storage, database, and compute engines into a singular cohesive platform, inherently designed to maintain the pace with the ever-expansive demands of AI applications. At its core, the VAST DataStore provides scalable storage solutions, ensuring that data remains readily accessible. The VAST DataBase facilitates structured data management, while VAST DataEngine empowers global function execution. This triad forms a symbiotic relationship, collectively simplifying data capture, synthesis, and learning processes. For businesses leveraging AI, these advancements are not just about keeping up but leaping ahead, enabling faster and more insightful AI-driven initiatives. Harnessing the power of this integrated platform, organizations can unlock unprecedented value from their data, pushing the boundaries of what's possible in AI deployments. #AI #DataManagement #DataStorage #ArtificialIntelligence #BusinessAutomation #VASTData Visit https://workflo.agency for your edge in automation. Secure a free consultation and see how automation can redefine your operations. Don't miss the opportunity to advance your business with the latest in automation technology.

What is the AI Technology Sandwich framework? This framework by Gartner is closely tied to the challenge of scaling AI effectively within organizations. Here's how it connects to different approaches for scaling AI: ➡️ Bottom layer - Centralized Foundation represents centralized technologies -  cloud platforms, MLOps tools, model registries, data lakes; operating models (e.g., centralized DataOps teams); and metrics (e.g., data latency, cost of infrastructure, cost to serve data). ➡️ Middle layer - Governance: Trust, Risk, and Security Management (TRiSM), is crucial for scaling AI responsibly. Include guidelines for how teams will meet compliance, privacy, bias audits, model explainability, and security requirements—preferably integrated into an existing software development lifecycle or MLOps workflow. ➡️ Top layer - Decentralized AI Integration reflecting the trend of AI being adopted across various business units. Provide how different business units can propose, pilot, and scale AI use cases—along with guardrails, budgets, and reporting lines. 💡 Key Insight: The “AI Technology Sandwich” sounds neat, but frameworks aren’t enough. You need: 💠 Clear roles and processes. 💠 Strong data foundations. 💠 Embedded trust, risk, and security. 💠 A culture that supports AI everywhere. Otherwise, your sandwich collapses.  The most successful AI strategies blend centralized control with decentralized creativity. #AIstrategy #scalingAI #innovation #digitaltransformation #gartner

No doubt the GenAI bandwagon is rolling, but ensuring robust infrastructure and data foundations remains a critical prerequisite for unlocking AI’s transformative power. 🚀  Over 60% of organizations grapple with significant gaps in AI readiness. These gaps primarily revolve around infrastructure and poor data governance. It can be a herculean effort to modernize both. Ensono can offer a 2-week assessment to provide you the roadmap to AI enlightenment (like a Sherpa monk). Let's chat! #AI #Data

Is Your AI Initiative Ready for Launch? Planning an AI initiative involves months of preparation—ensuring your data center is ready, governance is in order, and strategy is aligned. You might have some excellent use cases lined up, but are you truly ready to pull the trigger? The success or failure of an AI initiative hinges on meticulous planning. Investing time and effort upfront to ensure your infrastructure is not just capable but scalable is crucial. Introducing **AI Ignite** by ePlus inc. – a comprehensive suite of AI-focused solutions and services designed to support organizations at any stage of their AI journey. Our offerings include: 🔹 **Envisioning Workshops:** Discover AI opportunities tailored to your business. 🔹 **Readiness Assessments:** Evaluate and prepare your current state for AI. 🔹 **Data Strategy Assessments:** Align your data strategy with AI goals. 🔹 **Infrastructure Builds:** Create a scalable AI foundation. 🔹 **Modern Platform Management:** Ensure seamless platform operations. 🔹 **Implementation and Support Services:** Benefit from expert guidance and ongoing support. With decades of experience, the ePlus team is equipped to help you assess, enable, secure, implement, and amplify AI technologies for your success. We’d love to discuss your next steps and how we can ensure they lead to success. Reach out to schedule a call! #AI #AIIgnite #ePlus #ArtificialIntelligence #TechInnovation #DigitalTransformation Tony Leonardo ☁️Todd Wolff☁️ Danny St.Onge Michael DeMuro https://lnkd.in/e3Mpm8x6

Discover how to build a culture of #data excellence and propel your #AI success. In the age of digital transformation, data excellence is the cornerstone of successful AI initiatives. Ensuring high-quality, well-managed data can unlock the full potential of AI, driving innovation and efficiency across your organization. Some of the benefits are: ↪︎ Quality Data Management: Clean, accurate data is essential for effective AI models. ↪︎ Data Governance: Implement robust frameworks to ensure data integrity and compliance. ↪︎ Scalable Infrastructure: Adapt your data infrastructure to support growing AI demands. ↪︎ Continuous Improvement: Regularly refine your data strategies to stay ahead. ↪︎ Enhanced Decision-Making: Leverage accurate data for informed business strategies. ↪︎ Operational Efficiency: Streamline processes and reduce costs with reliable data. ↪︎ Competitive Edge: Stay ahead of the curve by maximizing AI's potential through superior data management. The success of AI initiatives heavily relies on the four pillars of data excellence. While an emerging perspective suggests that enterprise data quality may already be sufficient for initial AI adoption, there are risks. Read the full article to dive deeper into how data excellence is crucial for AI success: https://lnkd.in/eKrJe8Ec #DataExcellence #AISuccess #DataManagement #DigitalTransformation #TechInnovation #AI #MachineLearning #DataGovernance #DataOps #Encora

Read the full article to dive deeper into how data excellence is crucial for AI success: https://lnkd.in/euxU5RJ4

As I'm watching the rapid evolution of AI and data governance, I'm struck by a powerful insight from the DataHub team: We're not just facing a technological shift – we're experiencing a fundamental transformation in how enterprises manage their AI and data assets. Three game-changing trends are emerging: 1. AI Governance Automation: We're seeing AI solve its own governance challenges, with potential to automate 90% of traditional governance activities. The key? A human-in-the-loop approach for high-stakes decisions. 2. Unified Metadata Platforms: The days of fragmented metadata management are over. Modern enterprises need a single source of truth that can handle everything from traditional data assets to AI models, features, and prompts. 3. Open Source Innovation: The future of AI governance must be collaborative. No single organization can solve these challenges alone – we need transparent, community-driven solutions. Most exciting? Good governance isn't about restriction – it's about enabling safe innovation. As we move into 2025, organizations that embrace this mindset will lead the AI revolution. What governance challenges is your organization facing in the AI era? Read more about these significant trends for 2025 in the comments! #datagovernance #datalineage #aigovernance

Looking beyond many of the recent trendy innovations in AI technology, many business leaders are looking at the current market landscape and asking themselves: “What now?” and "What next?". It can be a perplexing place to find oneself as a leader, as for the most part, there are no beaten paths or clear examples that can be followed when it comes to capturing AI value at scale. To complicate matters, many businesses still need support when it comes to data engineering and data structure, as their current IT infrastructure has not been designed, built and optimized for the AI-driven landscape. Facing this barrage of oncoming challenges requires leaders to be prudent not only in big-picture thinking regarding long-term investments but also in the day-to-day operations where AI is beginning to be implemented to capture business value. These challenges cannot ignore the interrelated nature of existing infrastructure and potential IT outcomes. To do so does a disservice to existing highly efficient operational models. Instead, a way forward that builds on the advantages of the "as is" and progressively integrates key features of the "to be" operating model is a pragmatic approach. Innovate, test, scale and invest in what works. This is the recipe for success in Data Science and AI. #AI #DataScience #DataEngineering #Innovation

[Hot News] Claude's 500K Token Leap: Enterprise AI Gets a Massive Memory Boost 🧠📈 Anthropic has just raised the bar in AI capabilities with Claude's new 500,000 token context window for Enterprise users. This groundbreaking update allows Claude to process and respond to enormous volumes of data, including extensive documents and complex codebases, without frequent segmentation. While regular users can access a generous 200,000 token context window for free, with options for more through paid plans, the full 500K power is currently reserved for enterprise-level subscriptions. This move signifies a major leap in AI's ability to handle and analyze large-scale information seamlessly. The expansion of context windows in LLMs like Claude represents a clear trend: AI systems are rapidly evolving to manage increasingly larger volumes of data. This progression is set to revolutionize how businesses process and extract insights from their vast information repositories. Key Takeaway: As LLMs grow smarter and more capable of handling massive data volumes, businesses should prepare to leverage these advancements. Stay ahead by exploring how expanded AI capabilities can transform your data analysis and decision-making processes. #AITransformation #EnterpriseAI #LLM #DataProcessing #Claude