Operational Report


Deep Learning AI Listens to Machines For Signs of Trouble

#artificialintelligence

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.


[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. I was wondering if these are actually used today, or if it still just something people have researched. I have tried searching for it, but i cannot find any reliable source confirming that machine learning is infact used to detect oil spills.


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

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The technology, which gives companies the ability to predict future problems, is estimated to save the industry trillions of dollars and lead to a new wave of highly sophisticated jobs. "We know the industrial internet quite simply is the future of efficiency and productivity in the oil and gas industry. "We know there will be a shift in the oil and gas industry similarly to create a space where we use data analytics to provide predictability." "We know the industrial internet quite simply is the future of efficiency and productivity in the oil and gas industry.


Oil and Gas companies pin hopes on artificial intelligence

#artificialintelligence

With oil and gas prices hovering at decade lows, companies are turning to artificial intelligence to cut costs and boost productivity. The technology, which gives companies the ability to predict future problems, is estimated to save the industry trillions of dollars and lead to a new wave of highly sophisticated jobs. "We know the industrial internet quite simply is the future of efficiency and productivity in the oil and gas industry. "We know there will be a shift in the oil and gas industry similarly to create a space where we use data analytics to provide predictability."


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

IEEE Spectrum Robotics Channel

In order to build up a complete view of the world, a LIDAR needs to send out laser pulses all over the place. And because it's all solid-state electronics, you can steer each pulse completely independently, sending out one pulse in one direction and another pulse in a completely different direction just one microsecond later. Frame rate is usually a big deal for LIDAR systems that spin, but with the S3, you just get a million points per second and you can decide what frame rate you want to deal with them at, since it's all software controlled. Private jet or no private jet, Quanergy is planning to have a preproduction S3 sensor ready to go at the end of September 2016 so that they can spend Q4 ramping up production, with deliveries to OEMs scheduled for early 2017.