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Towards ML-enabled cleaning robots

Posted by Thomas Lew, Research Intern, and Montserrat Gonzalez Arenas, Research Engineer, Google Research, Brain Team Over the past several years, the capabilities of robotic systems have improved dramatically. As the technology continues to improve and robotic agents are more routinely deployed in real-world environments, their capacity to assist in day-to-day activities will take on …

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Deploy pre-trained models on AWS Wavelength with 5G edge using Amazon SageMaker JumpStart

With the advent of high-speed 5G mobile networks, enterprises are more easily positioned than ever with the opportunity to harness the convergence of telecommunications networks and the cloud. As one of the most prominent use cases to date, machine learning (ML) at the edge has allowed enterprises to deploy ML models closer to their end-customers …

Generative AI for SMS Marketing and MMS Marketing

Marketing via SMS (short message service) or MMS (multimedia message service) is massively popular because it takes advantage of mobile technology almost everyone owns and uses constantly—a smartphone. Research from Constant Contact shows that both sides benefit: 91% of consumers show interest in signing up for texts while 95% of marketers find that texts help …

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Interactive Fleet Learning

Figure 1: “Interactive Fleet Learning” (IFL) refers to robot fleets in industry and academia that fall back on human teleoperators when necessary and continually learn from them over time. In the last few years we have seen an exciting development in robotics and artificial intelligence: large fleets of robots have left the lab and entered …

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How Project Starline improves remote communication

Posted by Greg Blascovich and Eric Gomez, User Researchers, Google As companies settle into a new normal of hybrid and distributed work, remote communication technology remains critical for connecting and collaborating with colleagues. While this technology has improved, the core user experience often falls short: conversation can feel stilted, attention can be difficult to maintain, …

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Import data from over 40 data sources for no-code machine learning with Amazon SageMaker Canvas

Data is at the heart of machine learning (ML). Including relevant data to comprehensively represent your business problem ensures that you effectively capture trends and relationships so that you can derive the insights needed to drive business decisions. With Amazon SageMaker Canvas, you can now import data from over 40 data sources to be used …