Presented by Tata Communications Continuous inference, agent-to-agent communication, and real-time data pipelines are generating unpredictable, always-on traffic that legacy architectures were never built to support. As AI moves from pilot project to operational backbone, the network is emerging as a critical control layer that determines performance, reliability, and cost. The shift is forcing organizations to question assumptions that have held for decades. Legacy systems were static and rigid, and lacked the ability to manage network demand efficiently or dynamically, while AI-ready networks need to adapt in real time. A study by Cisco notes that 80% of executives believe their company’s competitive survival will depend on agentic AI, and consumer usage of AI is already prevalent and [...]
The Dfinity Foundation on Wednesday released Caffeine, an artificial intelligence platform that allows users to build and deploy web applications through natural language conversation alone, bypassing [...]
For the last 24 months, one narrative justified every over-provisioned data center and bloated IT budget: the GPU scramble. Silicon was the new oil, and H100s traded like contraband. Reserve capacity [...]
Presented by SAPThe enterprise software industry has undergone a fundamental shift, and vendors are adapting their approaches to better protect the customers who rely on them. For years, every global [...]
A doctor in a hospital exam room watches as a medical transcription agent updates electronic health records, prompts prescription options, and surfaces patient history in real time. A computer vision [...]
DeepSeek’s announcement over the weekend that it has made its 75% price cut permanent on its flagship V4 Pro model is a disruptive assault on the capital-heavy business models of Silicon Valley’s [...]
A core element of any data retrieval operation is the use of a component known as a retriever. Its job is to retrieve the relevant content for a given query. In the AI era, retrievers have been used a [...]