Displaying posts in the categoryAI
AI articles
Special Reports
From electronic mirrors to predictive perception: how cameras, silicon, connectivity and AI are reshaping the intelligent vehicle. Automotive cameras have moved from simple reversing aids to the main source of meaning in ADAS perception: lanes, signs, traffic lights and road users. Over five overlapping generations they went from one camera serving one function to many cameras feeding a central AI platform alongside radar and LiDAR. The next …
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Murugavel Ganesan
October 28, 2026
Top10
The semiconductor industry is adopting AI-assisted design tools faster than it is changing the teams that use them. The tools now help with RTL, verification, physical design, power and test, but hiring, job roles, training and performance metrics still reflect how chips were built a decade ago. That gap between 2026 tools and 2015 team structures is where expensive mistakes happen, and closing it is a leadership and organisational design task,…
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Murugavel Ganesan
June 24, 2026
Special Reports
Special report, February 2026, reviewed and corrected in November 2026. Market figures are as published by the sources named; most are forecasts and have not been re-verified. Edge AI means running AI models on the device where the data is created, such as a phone, a car, a robot, a camera or a sensor, instead of sending everything to a cloud data centre. In 2025 and 2026 it moved from pilots to real deployment, driven by three things together…
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Murugavel Ganesan
February 02, 2026
Opinion
The hidden cost of agentic AI is everything an autonomous agent needs to keep running: always-on inference in data centres, the electricity and water those centres consume, the advanced chips and the fragile supply chain that makes them, and the human workers who label, test and correct the models. Because agents loop through many model calls for every task, their running cost grows with use, not just with training. Autonomy for the user rests o…
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Murugavel Ganesan
November 01, 2025
Top10
Why learning AI prompting as a career skill is the wrong bet, and what to do instead How LinkedIn influencers mislead millions, and where the real opportunities in AI lie. Prompting is a useful everyday skill, but it is a poor thing to build a career on. It is easy to copy, it changes every time the models change, and the tools are increasingly doing it for you. The lasting value in AI sits in the layers around the prompt: data, integration…
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Murugavel Ganesan
August 26, 2025
