Nvidia has finalized its acquisition of Run:ai, a company located in Tel Aviv that simplifies the management and enhancement of AI hardware infrastructure for developers and operational teams. Nvidia is spending $700 million for this transaction, though the cost could […]
Source: aibeat.co
LG is currently engaged in exploratory discussions with NVIDIA concerning physical AI, data centres, and mobility. Following a meeting in Seoul between LG CEO Ryu Jae-cheol and Madison Huang, Senior Director of Product Marketing for Omniverse and Robotics at NVIDIA, the core operational dependencies required to run complex automated systems are becoming apparent. While the…
Many companies are taking a slower, more controlled approach to autonomous systems as AI adoption grows. Rather than deploying systems that act on their own, they are focusing on tools that assist human decision-making while keeping tight control over outputs. This approach is especially clear in sectors where errors carry real financial or legal risk….
To stop automation waste, enterprises must deploy interaction infrastructure that physically governs how independent AI agents operate. AI agents now populate corporate networks, reasoning through tasks and executing decisions with increasing autonomy. Yet, when these independent actors attempt to coordinate work, exchange context, or operate across varied cloud environments, the interaction framework degrades quickly. Human…
To protect enterprise margins, business leaders must invest in robust AI governance to securely manage AI infrastructure. When evaluating enterprise software adoption, a recurring pattern dictates how technology matures across industries. As Rob Thomas, SVP and CCO at IBM, recently outlined, software typically graduates from a standalone product to a platform, and then from a…
Joe Rose, president at strategic technology provider JBS Dev, wants to cut through one of the myths of working with generative and agentic AI systems. “It’s a common misconception that your data has to be perfect before you do any of these types of workloads,” he explains. As a recent article in AI Fieldbook outlines,…
Cloud migration becomes much harder when teams are not moving workloads, but also trying to make every environment reproducible and deployment-ready through Infrastructure as Code. The challenge is not limited to copying applications from one platform to another. It includes validating architecture decisions, controlling drift, enforcing policies, coordinating approvals, and making sure deployment logic can…