Big Data IoT Forum
Big Data IoT Forum's Latest Posts
A Deep Dive Into MCP and the Future of AI Tooling
By Yoko Li–Since OpenAI released function calling in 2023, I’ve been thinking about what it would take to unlock an ecosystem of agent and tool use. As the foundational models get more intelligent, agents’ ability to interact with external tools, data, and APIs becomes increasingly fragmented: Developers need to implement agents with special business logic […]
AI Quantum Chips vs Traditional Processors: What’s the Difference?
By Newsdeck–Quantum computing has emerged as one of the most revolutionary advancements in modern technology. At the heart of this innovation lies quantum ai chips, which operate fundamentally differently from traditional processors. In this article, we’ll explore the contrasts between quantum chips and classical processors, breaking down how each operates, their advantages and limitations, and real-world […]
5 Ways to Achieve Cost Efficiency with IoT
By Lyn Church—Organizations today are under a lot of pressure. Using existing resources to deliver high-quality products and services at lower costs. To do so, they must continually innovate to drive growth. One approach to achieving high growth with cost efficiency is with the adoption of IoT. Implementing and developing new technologies like IoT can unlock […]
AI-Driven Compliance: The Key to Cloud Security
By Michael Massimi and Abhijit Chakravorty—-The growth of cloud computing continues unabated, but it has also created security challenges. The acceleration of cloud adoption has created greater complexity, with limited cloud technical expertise available in the market, an explosion in connected and Internet of Things (IoT) devices and a growing need for multi-cloud environments. When clients migrate to the […]
How to Rethink Storage for AI Workloads
By Weka—New technologies are emerging in the AI world, and if you do not embrace them, you will be left behind. Gartner research found that 85% of companies are embarking on AI projects even though AI workloads present unique challenges, things that even data storage veterans have never faced before. This means that IT infrastructure […]
Computing Security in the Age of AI
By Richard Grisenthwaite, EVP, Chief Architect & Fellow, Arm Many existing foundational security technologies and standards will be more relevant and important than ever in the age of AI. As with any technology revolution, AI presents both opportunities and challenges to people’s digital experiences. Alongside its potentially transformative impact, AI also presents unique security threats, with a vast […]
Unleashing innovation via Composable Cloud: Customizing AI tech stacks for inference at the edge
By Kevin Cochrane—-Edge operations dominate the CTO agenda today, and as artificial intelligence (AI) and machine learning grow increasingly important across business operations, the CIO, CAIO, CDO, and other leaders are joining the conversation, leaning into edge operations to deliver AI at scale. However, the traditional edge operations designed to support distributed web apps can’t […]
Top 5 Enterprise Hybrid Cloud SDS NAS Solutions
By Todd Dorsey, DCIG senior storage analyst— An outcome of Data Center Intelligence Group (DCIG) research in Software Defined Storage for file storage, this report provides guidance on its Top 5 enterprise SDS NAS solutions with analysis of Ctera Enterprise File Services Platform, IBM Storage Scale, Nasuni File Data Platform, NetApp Cloud Volumes, and OSNexus […]
AI Evolution: Challenges Persist Despite Growing Optimism
By Ali Azhar —The majority of business leaders and technical analysts believe that AI is an essential tool for business sustainability. Nearly 3 in 4 decision-makers believe that not investing in AI puts their business at risk of failure, according to a report by Exasol, a high-performance analytics database provider. The Exasol report is based […]
The Future of AI Is Hybrid
By Alex Woodie—Artificial intelligence today is largely something that occurs in the cloud, where huge AI models are trained and deployed on massive racks of GPUs. But as AI makes its inevitable migration into to the applications and devices that people use every day, it will need to run on smaller compute devices deployed to […]
