Operational Report


Deep Learning AI Listens to Machines For Signs of Trouble

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The service of 3DSignals, a startup based in Kefar Sava, Israel, relies on the artificial intelligence technique known as deep learning to understand the noise patterns of troubled machines and predict problems in advance. The startup has even chatted with companies about using their service to automatically detect problems in future taxi fleets of driverless cars. The deep learning algorithms train on sound patterns that can signal general problems with the machines. Before this can happen, though, the clients need to help train the deep learning algorithm by first labeling certain sound patterns as belonging to specific types of problems.


Deep Learning AI Listens to Machines For Signs of Trouble

IEEE Spectrum Robotics Channel

The service of 3DSignals, a startup based in Kefar Sava, Israel, relies on the artificial intelligence technique known as deep learning to understand the noise patterns of troubled machines and predict problems in advance. The deep learning algorithms train on sound patterns that can signal general problems with the machines. On top of all this, 3DSignals has the chance to pioneer the advancement of deep learning in listening to general sounds. "It's important for us to be specialists in general acoustic deep learning, because the research literature does not cover it," Lavi says.


Artificial Intelligence Takes Shape In Oil, Gas Sector

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When artificial intelligence technology intersects with abundant oil and gas seismic data, the outcome could yield a more accurate depiction of what lies beneath the surface, enabling cash-strapped drillers to better target sweet spots and maximize returns.


IntelliFlux Artificial Intelligence-Based Control System from Water Planet Powers Demonstrations

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The project, which is being done with Sweetwater Tech Resources, utilizes Water Planet's IMS-5000 Integrated Produced Water Treatment Solution powered by IntelliFlux. The IMS-5000 technology used in the pilot is an integrated mechanical and membrane filtration system that incorporates ceramic membranes to filter the water. It was developed to perform in oil & gas produced water treatment, one of the most challenging water treatment applications on the planet. As part of the project, Water Planet is also running a standard reverse osmosis unit to desalt the brackish water that is left after treatment by the ceramic ultrafiltration membranes.


[Question] Is machine learning actually used to detect oil-spills or is it only been researched? • /r/MachineLearning

@machinelearnbot

Hello, so I am writing a paper on machine learning and I found this very interesting articale from 1998 where they researched on how machine learning could be used to detect oil spills from radar satellite images.


Oil & Gas Companies Turn to Artificial Intelligence to Save Money - Stochastic Simulation Community

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With oil and gas prices hovering at decade lows, companies are turning to artificial intelligence to cut costs and boost productivity.


Oil and Gas companies pin hopes on artificial intelligence

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With oil and gas prices hovering at decade lows, companies are turning to artificial intelligence to cut costs and boost productivity.


Quanergy Announces 250 Solid-State LIDAR for Cars, Robots, and More

IEEE Spectrum Robotics Channel

Yesterday at CES, Quanergy, an automotive startup based in Sunnyvale, Calif., held a press conference to announce the S3, a solid-state LIDAR system designed primarily to bring versatile, comprehensive, and affordable sensing to autonomous cars. The S3 is small, has no moving parts, and in production volume will be US 250 or less. According to Quanergy, the S3 is better than traditional LIDAR systems in every single way, and will make it easier and cheaper for robots of all kinds to sense what's going on in the world around them.