The Hard Part of AI Starts After the Demo Works

The Hard Part of AI Starts After the Demo Works Enterprise investment in artificial intelligence continues to accelerate. Recent McKinsey surveys show that more than 90% of large organizations plan to increase AI spending, often significantly. At the same time, fewer than 1% of enterprises describe themselves as AI-mature, meaning

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Smart Wearables Challenges

Inside the Engineering Stack – Why Building Smart, Secure Wearables Remains a Hard Engineering Problem

This article explains the technical realities of building AI-ready wearable devices by orchestrating three constraints – power, latency, and trust – through edge/on-device AI, disciplined power budgeting, and secure-by-design updates. It clarifies why many wearables PoCs stall and offers an in-depth investigation into challenges hindering product advancement, finally scanning predictions and emerging trends in the wearables market.

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The Hard Part of AI Starts After the Demo Works

The Hard Part of AI Starts After the Demo Works Enterprise investment in artificial intelligence continues to accelerate. Recent McKinsey surveys show that more than 90% of large organizations plan to increase AI spending, often significantly. At the same time, fewer than 1% of enterprises describe themselves as AI-mature, meaning

Read More »
data modernization services
application modernization

Data Modernization: Inside Rinf.tech’s Approach 

Showcasing rinf.tech’s comprehensive approach to data modernization, highlighting strategies that help transform traditional data systems into robust, agile, and future-proof platforms.

fleet management solutions
automotive

Top 10 Fleet Management Technology Trends

From integrating AI and 5G to adopting renewable energy sources, fleet management tech trends promise enhanced operational efficiency and align with broader sustainability and safety goals.