In robotics and industrial detection use cases, your vision AI is only as good as the raw data it receives. A mismatched sensor, poor resolution, or wrong frame rate can introduce motion blur, harsh shadows, and blind spots that no amount of AI model tuning can fix post-deployment.
New research from QNX (based on a survey of 1,000 developers worldwide), “Inside the Robot: Architecture Benchmark Report,” reveals a massive shift in robotics innovation: hardware is no longer the primary system constraint; software is now the bottleneck.
AI advances, labor shortages, and other drivers necessitate new ROI calculations. Robotic automation has seen significant adoption across various industries recently, driven by advancements in computer vision and artificial intelligence, persistent labor shortages, corporate mandates, and other factors. Fizyr’s new white paper – authored by Chief Commercial Officer Tibor van Melsem Kocsis – highlights the limitations of traditional ROI calculations in capturing the full value of these technologies and proposes an updated ROI model that includes output projections that address not only financial returns but also factors like worker safety; environmental, social and governance (ESG) impacts; supply chain resilience; and risk mitigation.
.jpg)
