If you need to quickly remove the background of an image you know how it can be boring, even with access to software like Photoshop. Remove.bg is a single-purpose website that uses AI to do the job for you. Just upload any image and the site will automatically identify any people in it, cut around the foreground, and let you download a PNG of your subject with a transparent background.
It’s the latest example of how machine learning techniques that were once cutting-edge are being turned into simple consumer tools. In the case of removing an image’s background, there are already a few open-source algorithms that can handle this particular task.
Other similar tools include Deepart.io which applies the style of one image (like a painting) to another, and LetsEnhance.io, which uses AI to automatically upscale pictures.
AWS (Amazon Web Services) has launched AWS RoboMaker, a new cloud service for developers to develop, test, and deploy robotics applications, as well as build intelligent robotics functions using its cloud services.
For this services, AWS has chosen Robot Operating System (ROS) and integrated the same with its cloud environment as an AWS cloud service named RoboMaker. AWS integration of Robot Operating System (ROS) will help developers leverage other AWS’s cloud services such as machine learning, monitoring, and analytics services to enable a robot to stream data, navigate, communicate, comprehend and learn.
RoboMaker essentially serves as a platform to help speed up the time-consuming robotics development process. Among the tools offered by the service are Amazon’s machine learning technologies and analytics that help create a simulation for real-world robotics development. The system can also be used to help manage fleet deployment for warehouse-style robotics designed to work in tandem. “AWS RoboMaker automatically provisions the underlying infrastructure and it downloads, compiles, and configures the operating system, development software, and ROS,” the company writes. “AWS RoboMaker’s robotics simulation makes it easy to set up large-scale and parallel simulations with pre-built worlds, such as indoor rooms, retail stores, and racing tracks, so developers can test their applications on-demand and run multiple simulations in parallel.
Following the data of at least eight companies in the robot delivery space with headquarters or operations in North America that have secured seed or early-stage funding in the past couple of years.
They range from heavily funded startups to lean seed-stage operations. Silicon Valley-based Nuro, an autonomous delivery startup founded by former engineers at Alphabet’s Waymo, is the most heavily funded, having raised $92 million to date. Others startups have raised a few million.
In the chart, we look at key players, ranked by funding to date, along with their locations and key investors.
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