AI Articles and Analysis about Automation and robotics

This article is based on a talk by Emerj.com (formerly TechEmergence) CEO Daniel Faggella at a recently held independently organized TEDxURI event. Part of the talk was on the impact of artificial intelligence on job security.

In May 2018, Bard College’s Center for the Study of the Drone released a report estimating that 910 “state and local police, sheriff, fire, and emergency services agencies” had acquired drones in the United States by the end of 2017.

With an ongoing nurse shortage in the United States and other areas, startups and global companies have begun developing methods for handling time-consuming responsibilities traditionally held by nurses, ranging from daily operations to diagnosis.

Garment and textile manufacturing have historically been labor-intensive industries, as seen in how many of world’s largest fashion, clothing and apparel brands seem to have a significant portion of their products manufactured in Asian countries such as China, India, Bangladesh, Vietnam, etc.

Episode summary: This week on AI in Industry, we speak to Rana el Kaliouby, Co-founder and CEO of Affectiva about how machine vision can be applied to detecting human emotion - and the business value of emotionally aware machines.

Over the past decade, the industrial sector has seen major advancements in automation and robotics applications. Automation in both continuous process and discrete manufacturing, as well as the use of robots for repetitive tasks are both relatively standard in most large manufacturing operations (this is especially true in industries like automotive and electronics).

In this episode of AI in Industry, we speak with Brendan Kohler, the CTO of Co-founder of Boston-based startup Sentenai. Brendan speaks about how businesses today can effectively leverage the data being collected by their existing IoT and automation systems. Though example applications and use-cases, Brendan elaborates on what kinds businesses might use this technology today and what they can expect in the near future.

Relative to banking, finance or healthcare, construction is still a small market for artificial intelligence and emerging applications are focused on finding patterns in large datasets which would either be too difficult for humans to process or would take them too long. Over the course of this article, we aim to answer the following questions: