Historically, AI in industrial automation was separate from the machines responsible for productivity, reliability, and safety. Data was captured on the factory floor, analyzed elsewhere, and provided after the fact as insights for operators. This architecture worked in an era when AI focused on reporting, optimization, and longer-cycle decision support. That era is ending.
Today, AI is expected t...
The narrative presents a compelling case for the shift toward edge AI in industrial automation, emphasizing practical constraints like latency, power efficiency, and security. The strongest version of this argument highlights the necessity of localized processing for real-time decision-making, reducing reliance on cloud infrastructure while maintaining hybrid architectures for scalability. However, the discussion assumes that edge AI is universally superior without addressing potential trade-off...