Convergent Intelligence Architecture: An AI Framework For Telecoms

As global carriers in aggressively pursue AI-driven automation, U.S. operators require architectural frameworks that enable innovation and manage infrastructure.

Conversational AI doesn’t understand users — 'Intent First' architecture does

The sooner an organization realizes this as an architectural imperative, the sooner they will be able to capture the ...
IEEE

Developing an Adaptive Enterprise Architecture Model Integrating Business Capabilities, Value Streams, and IT for Strategic Alignment in Complex Organizations

Abstract: This study presents the development of an adaptive enterprise architecture (EA) model designed to enhance strategic alignment in large, complex organizations. Developed through design ...

Humans& thinks coordination is the next frontier for AI, and they’re building a model to prove it

Humans&, a new startup founded by alumni of Anthropic, Meta, OpenAI, xAI, and Google DeepMind, is building the next ...

‘India is working on all 5 layers of the AI architecture: application, model, chip, infra and energy,’ Ashwini Vaishnaw

India is on track to become the world’s third-largest economy within the next few years, says Union Minister Ashwini Vaishnaw ...
EDN

The AI-tuned DRAM solutions for edge AI workloads

The evolution of DDR5 and DDR6 represents a inflexion point in AI system architecture, delivering enhanced memory bandwidth, lower latency, and greater scalability.
Cloud Security Alliance

Reimagining the Browser as a Critical Policy Enforcement Point: A Zero Trust Security Architecture for Modern Enterprises

Explores turning the browser into a policy enforcement point within a Zero Trust framework, covering governance, MFA, device ...
blockonomi

DeepSeek Introduces mHC Architecture to Improve Large Model Training

DeepSeek introduced Manifold-Constrained Hyper-Connections (mHC) to improve large-model training scalability and efficiency. The mHC method was tested on 3B, 9B, and 27B parameter models, showing ...
IEEE

SConvNSys: Accelerating Spiking Convolutional Neural Networks With a Reconfigurable Neuromorphic Architecture for Diverse Applications

Abstract: In recent years, spiking neural networks (SNNs) have progressively closed the performance gap with convolutional neural networks (CNNs), which are renowned for their success in complex ...