We’ve celebrated an extraordinary breakthrough while largely postponing the harder question of whether the architecture we’re scaling can sustain the use cases promised.
If your AI feels slow, expensive or risky, the problem isn’t the models — it’s the data, and cognitive data architecture is ...
Physicists at Silicon Quantum Computing have developed what they say is the most accurate quantum computing chip ever ...
AI initiatives don’t stall because models aren’t good enough, but because data architecture lags the requirements of agentic systems.
Abstract: Dynamic gesture recognition serves as a critical foundation for next-generation immersive virtual/augmented reality (VR/AR) systems and human-computer interaction (HCI). To address the ...
What it takes to operationalize entities and schema across large organizations, without breaking governance or increasing technical debt.
1. Risk: AI Monoculture (Shared Blind Spots). This is the most critical and overlooked systemic vulnerability. Building your ...
A key lesson was to measure what matters. From the outset, we defined clear success metrics—latency reduction, resource ...
EAS Station is a software-defined drop-in replacement for commercial EAS encoder/decoder hardware, built on commodity hardware like Raspberry Pi. It provides comprehensive alert processing with ...
Apple’s “App Intents” and Huawei’s “Intelligent Agent Framework” allow the OS to expose app functionalities as discrete actions the AI can invoke. More aggressive implementations use multimodal vision ...
Kaya is bringing that level of applied AI sophistication to construction, one of the world's largest yet least-digitized industries. With demand for data centers, clean energy, and semiconductor ...
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