2023-03-22, 03:55 PM
I'm really interested in this idea. I think a google coral board might be an ideal platform to run models trained in the cloud. https://coral.ai/docs/edgetpu/models-int...-on-device
I'd love to see a solution developed that would be aware of the weather forecast and local observations, potentially sharing local observations with nearby vessels to modify the responsiveness to the current weather situation. I have the feeling that the ability to judge sea state could be a key factor in improving performance over the basic polar data.
I'm not a machine learning expert and in my naivety it seems like it would be easier to solve than many machine learning problems that have had much success such as car autopilot and large language models.
Could the first step to this be a more advanced polar chart creator, based on observations of average real world progress in various conditions? can the current method of recording a polar chart be used as a hint for a machine learning model ?
I'd love to see a solution developed that would be aware of the weather forecast and local observations, potentially sharing local observations with nearby vessels to modify the responsiveness to the current weather situation. I have the feeling that the ability to judge sea state could be a key factor in improving performance over the basic polar data.
I'm not a machine learning expert and in my naivety it seems like it would be easier to solve than many machine learning problems that have had much success such as car autopilot and large language models.
Could the first step to this be a more advanced polar chart creator, based on observations of average real world progress in various conditions? can the current method of recording a polar chart be used as a hint for a machine learning model ?