The Convergence of AI and Real-Time: IBM Acquires Confluent
The deal signals a broader industry trend in which AI and real-time systems must converge to deliver on AI's true potential.
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The Evolution of Real-Time Intelligence at the Edge
Adaptive edge intelligence transforms edge nodes into mini real-time decision hubs, reducing reliance on centralized cloud decision pipelines and enabling …
Why Modern AI Needs NaaS
Enterprises and the providers delivering services to support AI efforts essentially need AI connectivity as a service. That’s where network-as-a-service …
Inside the New Wave of AI Adoption in Manufacturing
Manufacturers are entering a phase where AI is less about exploration and more about embedding it into the core fabric of operations.
Data Gravity and Its Impact on Cloud Strategy
Data gravity is inevitable. Decentralized storage, AI-driven orchestration, and provider-agnostic data fabrics can help make mobility a real option
Turning Unstructured Data into a Manageable Enterprise Asset
For data analysts, engineers, and scientists, automation can support AI and machine learning initiatives by giving them increased control, reduced overhead, …
Why Intelligence at the Edge is No Longer Optional
By processing data locally, organizations can filter and act on the most important insights immediately, while sending only relevant or aggregated data …
Can Vibe Coding Survive the New Era of Security
Vibe coding, which is the process of generating or modifying code through natural language prompts instead of writing every line manually, is gaining favor. …
Next Role for AI Agents: Recommending and Acting on Real-Time Choices
Use of AI agents is transitioning from systems that learn from decisions to systems that learn to improve the decision environment
New Study Unveils a Framework for Smarter MDA Implementation
Modern manufacturing requires more than traditional management strategies, specifically it needs manufacturing data analytics (MDA). However, a recent study …