Generative AI and physics simulation can improve warehouse efficiency by 5%, says Zebra | Imaging and Machine Vision Europe

Abstract The rapid development of AI-based products and their underlying models has led to constant innovation in deep learning frameworks. Google has been pioneering machine learning usage across dozens of products. Maintaining the multitude of model source codes in different ML frameworks and versions is a significant challenge. So far the maintenance and migration work

The Hariri Institute for Computing at Boston University has named Boston University alumni Mona Jalal as the new lead of its Data Science Mentoring Circles Program (DSMC), effective September 2026. Jalal was selected for her passion for mentoring and experience in bridging cutting-edge AI research and real-world engineering. As a Computer Vision Research Engineer III

Generative AI inference is uniquely hard: models are tens to hundreds of gigabytes, latency requirements are measured in tokens per second, cold starts can span multiple minutes as containers and weights transfer, GPU capacity is constrained, and traditional monitoring tools expose none of the token-level signals that matter in production. Amazon SageMaker AI offers customers