Sriram Narasimhan’s Post

Data Pipelines and the age of AI and ML by Robert Rocco – Lead Cloud Engineer at Midnyte City. Data pipelines are vital to an organisation’s data infrastructure. They facilitate the efficient transfer of data from collection to storage while preparing and structuring the data to ensure it is clean and ready for analysis. A robust and scalable data pipeline is essential for timely processing for businesses dealing with increasing data volumes. In this blog, Robert discusses the anatomy of data pipelines, covering their components and the processes of data extraction, transformation, and loading. He addresses various topics, including the operational efficiency gained through data pipelines, the role of AI and machine learning in enhancing these pipelines, the advantages of implementing efficient data pipelines, best practices for managing them, and strategies for securing your data pipelines. https://lnkd.in/gyCnVCru

🚀 Discover How Generative AI is Transforming Data Migration!   In 2024, over 60% of businesses are migrating data to the cloud to reduce costs, improve scalability, and enhance analytics. But what if you could streamline this process and mitigate risks effortlessly?   Stay tuned to learn how Generative AI is revolutionizing data migration with predictive issue identification, automated data mapping, and more!   Read the full article for in-depth insights! 🔗 https://lnkd.in/gzzeEiEu

“Cahn believes the industry must temper expectations of quick profits from AI advancements, recognizing the speculative nature of current investments and the need for sustained innovation and value creation. If it does not, the bubble worth hundreds of billions of dollars is set to blow, potentially leading to a global economic crisis, but we are speculating here, of course.” I believe one of the biggest issues we’re facfacing is the misconception that “AI” is a single large resource that needs to be rolled out to an enterprise. I think in many leader’s minds, this is like deploying Oracle in the early 2ks or migrating from on-premises to the cloud. It’s not and shouldn’t be. It’s much closer to a library a developer uses to easily convert machine generated date and time stamps to human relatable dates. 20240708:14:22:00 becomes “yesterday at 2:22 pm”. This seems far less sexy than an organization-wide assistant that can basically write all your code, infer great insights about business decisions by reading ten years worth of excel and word docs from your shared corporate drive that some people charitably call a knowledge repository, and also automatically replace half your work force for half the price. I believe this misconception is everywhere, even at the leadership level of organizations who should know better, but it’s hard to make a windfall profit selling code libraries. It’s much easier if you’re selling something like an Oracle license. I don’t agree with some critics that these LLM models are useless just because they hallucinate, or because they primarily truck in generalities and mediocre output, because they are very useful at small tasks at the local user level. And this is part of the problem. The tech giants want to sell you a herd of cows for dinner, when all you really need is a chicken. But the right set of ML models deployed strategically within your organization could save your employees time, enhance collaboration, and manage a few mundane tasks related to documentation and internal communication, but that’s not as easy to sell as a big shiny box of brand new “AI.”

AI is the hot topic for my accounts. Secure, accessible storage with NetApp can be the foundation of your AI journey!

Alluxio Enterprise AI 3.2: Enhancing GPU Utilization and Data Access for AI Workloads https://ift.tt/dMq7UFo In an era where AI and machine learning are pushing the boundaries of computational power, efficient GPU utilization, and data access have become critical bottlenecks. Alluxio, a pioneer in data orchestration for analytics and AI, has unveiled its latest offering, Alluxio Enterprise AI 3.2, to address these challenges head-on. This release promises to transform how organizations leverage their GPU resources and manage data for AI workloads, offering a blend of performance, flexibility, and ease of use that could reshape the landscape of AI infrastructure. Unleashing GPU Power: Anywhere, Anytime One of the standout features of Alluxio Enterprise AI 3.2 is its ability to enable GPU utilization anywhere. This capability is a game-changer in a world where GPU resources are often scarce and distributed across various environments. Organizations can now run AI workloads wherever GPUs are available, whether on-premises, in the cloud, or in a hybrid setup. via DZone AI/ML Zone https://dzone.com/ai-ml July 15, 2024 at 11:00AM

I've had a busy morning of discovery calls with organisations that are asking how/if they can use Microsoft Fabric... In our live demo, we use real but anonymised data from our previous Fabric engagements to demonstrate the power of the solution and how organisations are leveraging it to deliver extraordinary insights and automation within their business. We also look further ahead at what's possible with Copilot, Open AI and predictive modelling. If you have a spare hour, consider registering. No hard sell, just value! https://lnkd.in/ew8h8gyS #microsoftfabric #azure #fabric #openai #azureopenai #copilot #businessintelligence #microsoft

The latest update for #Continual includes "Continual is #SOC2 compliant" and "Microsoft Copilot: A Tour". #analytics #BusinessIntelligence #BI #AI https://lnkd.in/esCHHFbC

Alluxio Enterprise AI 3.2: Enhancing GPU Utilization and Data Access for AI Workloads https://buff.ly/467fVTP In an era where AI and machine learning are pushing the boundaries of computational power, efficient GPU utilization, and data access have become critical bottlenecks. Alluxio, a pioneer in data orchestration for analytics and AI, has unveiled its latest offering, Alluxio Enterprise AI 3.2, to address these challenges head-on. This release promises to transform how organizations leverage their GPU resources and manage data for AI workloads, offering a blend of performance, flexibility, and ease of use that could reshape the landscape of AI infrastructure. Unleashing GPU Power: Anywhere, Anytime One of the standout features of Alluxio Enterprise AI 3.2 is its ability to enable GPU utilization anywhere. This capability is a game-changer in a world where GPU resources are often scarce and distributed across various environments. Organizations can now run AI workloads wherever GPUs are available, whether on-premises, in the cloud, or in a hybrid setup.

Driven by the widespread adoption of AI across industries, the AI server market is set to expand significantly. 💻 According to projections from Fundamental Business Insights & Consulting, it could reach approximately $183 billion by 2032. Curious about the key trends and growth drivers in this rapidly evolving sector? Dive into the latest insights: 🔗 https://lnkd.in/eCY_3f2b #AIServers #MarketTrends #DataCenters